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The Ph.D. Grind: A Ph.D. Student Memoir
A Ph.D. Student Memoir
"This book (download PDF) chronicles my six years of working towards a Ph.D. in Computer Science at Stanford University from 2006 to 2012. " http://www.pgbovine.net/PhD-memoir.htm
"This book (download PDF) chronicles my six years of working towards a Ph.D. in Computer Science at Stanford University from 2006 to 2012. " http://www.pgbovine.net/PhD-memoir.htm
115 pages, ebook
First published July 16, 2012
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Displaying 1 - 30 of 123 reviews
June 28, 2023
Question: Is your book meant as a critique of academia or a call for reform?
Absolutely not. I don't have any agenda besides telling my own story as honestly as possible.
most Ph.D. students are directly training for a job that they will never get. (Imagine how disconcerting it would be if medical or law school graduates couldn’t get jobs as doctors or lawyers, respectively.)
Strange one. It's 100 pages of minor mental breakdowns, ten thousand hours of mind-numbing gruntwork, stupid status games, and disillusionment - all in plain, businesslike, affectless prose. Also, there's very little technical detail in it. You'd think he was describing painting a house, rather than a painful initiation into the partially-insane system of placing logic incarnate in harness (a system with surprisingly weak links to discovery and progress).
research was my only job, and I wouldn’t be able to earn a degree unless I succeeded at it. My mood was inextricably tied to how well I was progressing every day, and during those months, progress was painfully slow.
He spends two years of his life on nasty little problems, thousands of hours of config and debugging, nothing to show for it, no papers, no new results. The top CS schools don't let you graduate until you get 4 papers in "top" conferences: layers upon layers of luck and gatekeeping, only modestly correlated with your efforts. Oh, and you are unlikely to have much choice of project either. A recipe for misery. This is at the very top of the game, too: Stanford with full funding and annual internships at the big lads. It is both reassuring and horrifying to hear that elite groups waste months and submit total shit sometimes.
In the end, it took three attempts by four Ph.D. students over the course of five years before Dawson’s initial Klee-UC idea turned into a published paper. Of those four students, only one “survived”—I quit the Klee project, and two others quit the Ph.D. program altogether.
Guo is no Jeremiah: despite his suffering, despite his very penetrating analysis of the waste and the idiocies, he doesn't declaim the system. He just analyses the narrow, nonscientific incentives of those around him and gets on with winning the game. He talks like this: "i think that leveraging [software] and aligning with both of your interests and incentives will be the best way for me to both make a contribution and also to feel satisfied about making concrete forward progress every day.”. He uses 'top-tier' without scare quotes. At one point he dispassionately notes that half a dozen of his papers were rejected because he wasn't fluent in the specific sub-field's “rhetorical tricks, newfangled buzzwords, and marketing-related contortions required to satisfy reviewers". That is, he comes up against bullshit Bourdieuan micro-distinctions, boundary work, irrelevant to science, and shrugs and sets about learning how to pass as an insider. Look elsewhere for the relevant denunciations.
It would be cynical to think that he doesn't milk the politics of postgraduate pain because he landed well, is a professor now - instead just envy him his inner calm:
my six years of Ph.D. training have made me wiser, savvier, grittier, and more steely, focused, creative, eloquent, perceptive, and professionally effective than I was as a fresh college graduate. (Two obvious caveats: Not every Ph.D. student received these benefits—many grew jaded and burned-out from their struggles. Also, lots of people cultivate these positive traits without going through a Ph.D. program.)...
Pursuing a Ph.D. has been one of the most fulfilling experiences of my life, and I feel extremely lucky to have been given the opportunity to be creative during this time.
There is this to be said for the American seven year ditch: Guo was able to suffer and wander for three entire years before he had his first big idea. That's the other side: the incredible privilege of being paid to read, paid to talk to clever people, paid to think new thoughts. But who says privileges have to feel nice, or not drive you half-mad?
A very valuable warning for some tiny fraction of the world, a flat curio for some other tiny voyeur fraction.
February 5, 2017
Extremely well-written. More importantly, it resonates with my own experiences (though only a short eight-month attachment in Canada), where I felt the frustrations and mental breakdowns similar to those described in the article. Most crucially, the human voice in this article is extremely strong that I can literally hear the thoughts. Would recommend anyone reading --- whether you are pursuing academic route or not.
I started to have a grasp, partly thanks to a short chat with a friend, that perhaps PhD route which I have been constantly in fear of may well be a path worth taking despite all the monetary shortcomings and uncertain future. The academia may well be "worsening" in job prospects since there are more people and fewer vacancies, but in the end it is just another place for growth. Different people grow differently, but most importantly they grow well/badly in different places. I can foresee myself growing in non-academic related jobs, but perhaps (thanks to this article and my Canada experience) PhD is still the way to go, no matter what happens.
I did not bother scrutinizing the character or the perfection of this article, since it is pointless. A 115-page article cannot completely summarize the experience of a person, and a human writing his own mix of positive and negative experiences cannot hope to write perfectly --- and thus I will not be surprised to find people finding this article bad. After all, it is always easier to find faults from the perspective of third-person observer. Despite that possibility, I appreciate deeply this writing --- even if many parts of it do not apply nor is my field the same.
I started to have a grasp, partly thanks to a short chat with a friend, that perhaps PhD route which I have been constantly in fear of may well be a path worth taking despite all the monetary shortcomings and uncertain future. The academia may well be "worsening" in job prospects since there are more people and fewer vacancies, but in the end it is just another place for growth. Different people grow differently, but most importantly they grow well/badly in different places. I can foresee myself growing in non-academic related jobs, but perhaps (thanks to this article and my Canada experience) PhD is still the way to go, no matter what happens.
I did not bother scrutinizing the character or the perfection of this article, since it is pointless. A 115-page article cannot completely summarize the experience of a person, and a human writing his own mix of positive and negative experiences cannot hope to write perfectly --- and thus I will not be surprised to find people finding this article bad. After all, it is always easier to find faults from the perspective of third-person observer. Despite that possibility, I appreciate deeply this writing --- even if many parts of it do not apply nor is my field the same.
April 7, 2013
Đây là tự truyện của một PhD student sau khi tốt nghiệp khoa CS ở Stanford. Very insightful about the process!! Philip Guo đã làm rất tốt việc miêu tả quá trình làm PhD đầy gian khổ nhưng cũng đầy thỏa mãn. Như tác giả nói: "It [the PhD] was fun at times, but more importantly, it was fulfilling".
Những point nổi bật mà tác giả đã nêu (20 of the most memorable lessons) :
- Đê thành công ở PhD nhất định phải có kết quả. Philip tốt nghiệp PhD CS vì anh ta đã sản sinh ra 5 prototype tool và hàng chục publish papers. PhD is not for "students with the most idealistic of intentions - dreamy and passionate hopes of revolutionizing their field - who produce few results and then end up disillusioned"
- PhD thành công không phải vì read cực nhiều publication on the field. Philip rơi vào trap này vào năm thứ nhất khi anh đọc hàng trăm bài báo không vì mục đích cụ thể nào cả. Ngược lại, đọc paper rất có lợi trong trường hợp đã tìm được project cho mình, đi tìm những related word để xác định competitors, cũng như thêm những idea vào trong project của mình.
- Phải có cách tìm relevant information riêng. Không phải lúc đi học trong lớp, không texbooks, không lecture notes, không instructors. Giờ đây, làm PhD là kiếm info trong research paper, trong một đoạn code, một website đâu đó, và ở trong cả trong đầu ai đó mà ta phải tìm ra và hỏi giúp đỡ.
- Phải biết cách tạo ra cơ hội. Philip đã làm rất nhiều việc - giving talks, chatting with collegues,asking for and offering helps, and expressing gratitudes. Từ đó mà dẫn đến nhiều cơ hội, như tìm đến được Fernado ở UCB để được inspired làm ra IncPy, rồi việc gặp gỡ, follow up, và cuối cùng là cơ hội làm việc với Margo ở Harvard làm ra Burrito.
- Phải biết luật chơi của "academic game", bị rất nhiều lần rejection trước khi biết cách publish hiệu quả.
- Biết động lưc, tính cách của các PhD students khác, của các profs, và senior collegues, từ đó mà biết tận dụng, dẫn dắt họ theo hướng của mình.
- Profs are human.
- Làm những nhiệm vụ bắt buộc. Với những PhD student mới, việc "pay some dues" là rất cần thiết, thay vì chỉ đạo ngay từ những ngày đầu tiên. Nhiệm vụ ở đây nghĩa là work on research projects của supervisor.
- Biết cách reject bad defaults. Ở memoir của Philips, default ở đây là làm việc liên tục theo project Klee của Dawson. Philip đã thử rất lâu nhưng không có kết quả. Defaults aren't usually in the best interests of those on the bottom (e.g. PhD students) so it's important to know when to reject them and to ask for something different.
- Biết khi nào nên quit. Như philip quit Klee thì mới có cơ hội làm ra IncPy, SlopPy,CDE, ProWranglerProWrangler, Burrito
- Recover from failures. Câu này Philip viết rất hay: "Grad school was a safe environment to practice recov-
ering from failures, since the stakes were low compared to failing in real jobs"
- Tìm và hợp tác với những insiders, là những người đã thông thuộc hết những tricks ở trong một subfield, do đó hơp tác với họ dễ publish hơn.
- Give many talks: là nơi để sản sinh ra những cơ hội hợp tác.
- Sell, sell, sell: thousands of hours of hard grinding would go to waste if I failed to properly pitch the
big-picture signi�cance of my research to my target audience. Dịch nôm na là làm ngon là chưa đủ, phải biết cách marketing !
- Hào phóng giúp đỡ.
- Tìm sự giúp đỡ đúng nơi.
- Biết cách thể hiện sự biết ơn.
- Ideas are always built upon other ideas.
- Grind hard and smart: ở đây Philip đã viết rằng mình đã grind đủ 10000 giờ trong quá trình làm Ph.D (là con số mà làm cho một người trở thành expert một thứ gì đó, xem trong Những kẻ xuất chúng - Malcomm Gladwell). Nhưng grind hard nhưng cũng phải grind smart. "It's sad to see students blindly
working themselves to death on tasks that won't get favorable re-sults: approaching a research problem from an unwise angle, using the wrong kinds of tools, or doing useless errands."
----
Một cuốn tự truyện dễ đọc, nhưng cũng nhiều thông tin hữu ích về một quá trình - The Ph.D. Thanks Philip!
Những point nổi bật mà tác giả đã nêu (20 of the most memorable lessons) :
- Đê thành công ở PhD nhất định phải có kết quả. Philip tốt nghiệp PhD CS vì anh ta đã sản sinh ra 5 prototype tool và hàng chục publish papers. PhD is not for "students with the most idealistic of intentions - dreamy and passionate hopes of revolutionizing their field - who produce few results and then end up disillusioned"
- PhD thành công không phải vì read cực nhiều publication on the field. Philip rơi vào trap này vào năm thứ nhất khi anh đọc hàng trăm bài báo không vì mục đích cụ thể nào cả. Ngược lại, đọc paper rất có lợi trong trường hợp đã tìm được project cho mình, đi tìm những related word để xác định competitors, cũng như thêm những idea vào trong project của mình.
- Phải có cách tìm relevant information riêng. Không phải lúc đi học trong lớp, không texbooks, không lecture notes, không instructors. Giờ đây, làm PhD là kiếm info trong research paper, trong một đoạn code, một website đâu đó, và ở trong cả trong đầu ai đó mà ta phải tìm ra và hỏi giúp đỡ.
- Phải biết cách tạo ra cơ hội. Philip đã làm rất nhiều việc - giving talks, chatting with collegues,asking for and offering helps, and expressing gratitudes. Từ đó mà dẫn đến nhiều cơ hội, như tìm đến được Fernado ở UCB để được inspired làm ra IncPy, rồi việc gặp gỡ, follow up, và cuối cùng là cơ hội làm việc với Margo ở Harvard làm ra Burrito.
- Phải biết luật chơi của "academic game", bị rất nhiều lần rejection trước khi biết cách publish hiệu quả.
- Biết động lưc, tính cách của các PhD students khác, của các profs, và senior collegues, từ đó mà biết tận dụng, dẫn dắt họ theo hướng của mình.
- Profs are human.
- Làm những nhiệm vụ bắt buộc. Với những PhD student mới, việc "pay some dues" là rất cần thiết, thay vì chỉ đạo ngay từ những ngày đầu tiên. Nhiệm vụ ở đây nghĩa là work on research projects của supervisor.
- Biết cách reject bad defaults. Ở memoir của Philips, default ở đây là làm việc liên tục theo project Klee của Dawson. Philip đã thử rất lâu nhưng không có kết quả. Defaults aren't usually in the best interests of those on the bottom (e.g. PhD students) so it's important to know when to reject them and to ask for something different.
- Biết khi nào nên quit. Như philip quit Klee thì mới có cơ hội làm ra IncPy, SlopPy,CDE, ProWranglerProWrangler, Burrito
- Recover from failures. Câu này Philip viết rất hay: "Grad school was a safe environment to practice recov-
ering from failures, since the stakes were low compared to failing in real jobs"
- Tìm và hợp tác với những insiders, là những người đã thông thuộc hết những tricks ở trong một subfield, do đó hơp tác với họ dễ publish hơn.
- Give many talks: là nơi để sản sinh ra những cơ hội hợp tác.
- Sell, sell, sell: thousands of hours of hard grinding would go to waste if I failed to properly pitch the
big-picture signi�cance of my research to my target audience. Dịch nôm na là làm ngon là chưa đủ, phải biết cách marketing !
- Hào phóng giúp đỡ.
- Tìm sự giúp đỡ đúng nơi.
- Biết cách thể hiện sự biết ơn.
- Ideas are always built upon other ideas.
- Grind hard and smart: ở đây Philip đã viết rằng mình đã grind đủ 10000 giờ trong quá trình làm Ph.D (là con số mà làm cho một người trở thành expert một thứ gì đó, xem trong Những kẻ xuất chúng - Malcomm Gladwell). Nhưng grind hard nhưng cũng phải grind smart. "It's sad to see students blindly
working themselves to death on tasks that won't get favorable re-sults: approaching a research problem from an unwise angle, using the wrong kinds of tools, or doing useless errands."
----
Một cuốn tự truyện dễ đọc, nhưng cũng nhiều thông tin hữu ích về một quá trình - The Ph.D. Thanks Philip!
January 23, 2020
What I find really interesting about this is that regardless of how much of a success or failure you look from the outside, from the inside it tends to feel much the same. My experiences as a thoroughly mediocre masters student have had essentially the same ups, downs, insecurities, and learning experiences as an elite PhD student.
Really good for learning the tips and tricks for navigating the non-ideal parts of academia.
I found this line funny because it reminds me of recursive self-improvement, AI take-off scenarios:
> My job was to use Klee to find bugs in Linux device driver code,but ironically, all I ended up doing in the first month was finding bugs in Klee itself. (Too bad Klee couldn’t automatically find bugs in its own code!)
Apparently the best advice for PhD students is:
> Be proactive in talking with professors to find research topics that are mutually interesting, and no matter what, don’t just hole up in isolation.
Page 24 has a good example of "if you care about a goal enough, then you'll find a way to power through all obstacles to get to it":
> Rather than cold-emailing (I didn’t even know who to email!), I decided to drive to the Mozilla headquarters and walk in the front door.
My favourite quotes:
> In the cutthroat world of academic publishing, simply being passionate about a topic is nowhere near sucient for success; one must be well-versed in the preferences of senior colleagues in a particular subfield who are serving as paper reviewers.> I cannot re-emphasize this point enough times: Properly calibrating your pitch to the academic sub-community you’re targeting is crucial for getting a paper accepted.
> In hindsight, I can see why this project was likely to fail because of misaligned incentives, but back then, I lacked the wisdom toforesee such a failure. Recall that I decided to become a Klee assistant for Cristi and Dawson since I wanted to join an older Ph.D. student and professor who were experienced in publishing papers in their given subfield. I did so because this plan worked marvelouslyduring the previous year when I helped Joel (an older Ph.D. student) and Scott (a professor) on their HCI project, which led to a top-tier awardnominated paper. 36 The Ph.D. Grind So what was di↵erenthere? In short, neither Cristi nor Dawson were truly hungry to publish. They had already published several Klee papers together, and a cross-checking paper coauthored with me would have been a “nice-to-have” but not mandatory follow-up publication. Cristi was in his final year of Ph.D. and didn’t need to publish any more papers to graduate, and Dawson already had tenure, so he wasn’t in a rush to publish either. In contrast, Joel was a mid-stage Ph.D. student who was itching to publish the first paper of his dissertation, and Scott was an assistant professor who needed to publish prolifically toearn tenure. These two opposing experiences taught me the importance of deeply understanding the motivations and incentives of one’s potential collaborators before working with them.
> From a professor’s perspective, though, Klee-UC was a rousing success! Since Dawson had tenure, his job was never in danger. In fact, one of the purposes of tenure is to allow professors to take risks by attempting bolder project ideas. However, the dark side of this privilege is that professors will often assign students to grindon risky projects with low success rates. And the students often can’t refuse, since they are funded by their advisors’ grants. Thankfully, since I Fellowships are important not for the money, but rather for the freedom from grant-related constraints. was funded by fellowships, it was much easier for me to quit Klee. The professor might need to go through several rounds of student failures and dropouts before one set of students eventually succeeds. Sometimes thatmight take two years, sometimes five years, or sometimes even ten years to achieve. Many projects last longer than individual Ph.D. student “lifetimes.” But as long as the original vision is realized and published, then the project is considered a success. The professor is happy, the university department is happy, the grant fundingagency is happy, and the final surviving set of students is happy.But what about the student casualties along the way? A tenured professor can survive several years’ worth of failures, but a Ph.D. student’s fledgling career—and psychological health—will likely be ruined by such a chain of disappointments.
> The best way to think of MSR is as a giant research university without any students. The full-time researchers are like professors,except that they can focus nearly all of their time on research since they don’t have teaching or advising duties. But perhaps their favorite job benefit is that they don’t need to apply for grant funding, which is a tedious recurring activity that saps professors’ time. Since Microsoft is an immensely profitable company, it allocates hundreds of millions of dollars each year to funding academic (paper-producing) research. Microsoft is betting that some of the intellectual property created by its researchers might inspire future products, and it also wants the best minds in computer science on sta↵ for consultation. That’s why the company gives its researchers access to all of the resources required to do their best work.
> That said, having workshop papers can be a path toward “pity graduation” because it’s still better than having no published papers.
> It costs about as much to send a student to a workshop as to a conference, and conference papers are much more prestigious both forthe student and the professor. Thus, top-tier com- puter science professors strongly encourage students to publish more selective conference papers and eschew workshops altogether
> Part of luck is always keeping your eyes open for new opportunities while simultaneously focusing enough to make consistent progress.
> But rather than moving on to a new project idea like a prudent researcher would do, I dedicated most of my fifth year to turning CDE into a production-quality piece of software. I had an urge to make CDE useful for as many people as possible. I didn’t want it to languish as yet another shoddy research prototype that barely worked well enough to publish papers. I knew my e↵orts to polish up CDE wouldn’t be rewarded by the research community and might even delay my graduation since I could’ve spent that time developing new dissertation project ideas.
> Reject bad defaults: Defaults aren’t usually in the best interests of those on the bottom (e.g., Ph.D. students), so it’s importantto know when to reject them and to ask for something di↵erent. Of course, there’s no nefarious conspiracy against students; the defaults are just naturally set up to benefit those in power. For example, famous tenured professors like Dawson are easily able to get multi-year grants to fund students to work on “default” projects like Klee. As long as some papers get published from time to time, then the professor and project are both viewed as successful, regardlessof how many students stumbled and failed along the way. Students must judge for themselves whether their default projects are promising, and if not, figure out how to quit gracefully.
> Sell, sell, sell: I spent the majority of my grad school days headsdown grinding on implementing research ideas, but I recognized that convincingly selling my work was the key to publication, recognition, and eventual graduation. Due to the ultra-competitive natureof the paper publication game, what often makes the di↵erence between an accept and a reject decision is how well a paper’s “marketing pitch” appeals to reviewers’ tastes. Thus, thousands of hours of hard grinding would go to waste if I failed to properly pitch the big-picture significance of my research to my target audience: senior academic colleagues. More generally, many people in a field have good ideas, so the better salespeople are more likely to get their ideas accepted by the establishment. As a low-status grad student, one of the most e↵ective ways for me to “sell” my ideas and projects was to get influential people (e.g., famous professors such as Margo) excited enough to promote them on my behalf.
Really good for learning the tips and tricks for navigating the non-ideal parts of academia.
I found this line funny because it reminds me of recursive self-improvement, AI take-off scenarios:
> My job was to use Klee to find bugs in Linux device driver code,but ironically, all I ended up doing in the first month was finding bugs in Klee itself. (Too bad Klee couldn’t automatically find bugs in its own code!)
Apparently the best advice for PhD students is:
> Be proactive in talking with professors to find research topics that are mutually interesting, and no matter what, don’t just hole up in isolation.
Page 24 has a good example of "if you care about a goal enough, then you'll find a way to power through all obstacles to get to it":
> Rather than cold-emailing (I didn’t even know who to email!), I decided to drive to the Mozilla headquarters and walk in the front door.
My favourite quotes:
> In the cutthroat world of academic publishing, simply being passionate about a topic is nowhere near sucient for success; one must be well-versed in the preferences of senior colleagues in a particular subfield who are serving as paper reviewers.> I cannot re-emphasize this point enough times: Properly calibrating your pitch to the academic sub-community you’re targeting is crucial for getting a paper accepted.
> In hindsight, I can see why this project was likely to fail because of misaligned incentives, but back then, I lacked the wisdom toforesee such a failure. Recall that I decided to become a Klee assistant for Cristi and Dawson since I wanted to join an older Ph.D. student and professor who were experienced in publishing papers in their given subfield. I did so because this plan worked marvelouslyduring the previous year when I helped Joel (an older Ph.D. student) and Scott (a professor) on their HCI project, which led to a top-tier awardnominated paper. 36 The Ph.D. Grind So what was di↵erenthere? In short, neither Cristi nor Dawson were truly hungry to publish. They had already published several Klee papers together, and a cross-checking paper coauthored with me would have been a “nice-to-have” but not mandatory follow-up publication. Cristi was in his final year of Ph.D. and didn’t need to publish any more papers to graduate, and Dawson already had tenure, so he wasn’t in a rush to publish either. In contrast, Joel was a mid-stage Ph.D. student who was itching to publish the first paper of his dissertation, and Scott was an assistant professor who needed to publish prolifically toearn tenure. These two opposing experiences taught me the importance of deeply understanding the motivations and incentives of one’s potential collaborators before working with them.
> From a professor’s perspective, though, Klee-UC was a rousing success! Since Dawson had tenure, his job was never in danger. In fact, one of the purposes of tenure is to allow professors to take risks by attempting bolder project ideas. However, the dark side of this privilege is that professors will often assign students to grindon risky projects with low success rates. And the students often can’t refuse, since they are funded by their advisors’ grants. Thankfully, since I Fellowships are important not for the money, but rather for the freedom from grant-related constraints. was funded by fellowships, it was much easier for me to quit Klee. The professor might need to go through several rounds of student failures and dropouts before one set of students eventually succeeds. Sometimes thatmight take two years, sometimes five years, or sometimes even ten years to achieve. Many projects last longer than individual Ph.D. student “lifetimes.” But as long as the original vision is realized and published, then the project is considered a success. The professor is happy, the university department is happy, the grant fundingagency is happy, and the final surviving set of students is happy.But what about the student casualties along the way? A tenured professor can survive several years’ worth of failures, but a Ph.D. student’s fledgling career—and psychological health—will likely be ruined by such a chain of disappointments.
> The best way to think of MSR is as a giant research university without any students. The full-time researchers are like professors,except that they can focus nearly all of their time on research since they don’t have teaching or advising duties. But perhaps their favorite job benefit is that they don’t need to apply for grant funding, which is a tedious recurring activity that saps professors’ time. Since Microsoft is an immensely profitable company, it allocates hundreds of millions of dollars each year to funding academic (paper-producing) research. Microsoft is betting that some of the intellectual property created by its researchers might inspire future products, and it also wants the best minds in computer science on sta↵ for consultation. That’s why the company gives its researchers access to all of the resources required to do their best work.
> That said, having workshop papers can be a path toward “pity graduation” because it’s still better than having no published papers.
> It costs about as much to send a student to a workshop as to a conference, and conference papers are much more prestigious both forthe student and the professor. Thus, top-tier com- puter science professors strongly encourage students to publish more selective conference papers and eschew workshops altogether
> Part of luck is always keeping your eyes open for new opportunities while simultaneously focusing enough to make consistent progress.
> But rather than moving on to a new project idea like a prudent researcher would do, I dedicated most of my fifth year to turning CDE into a production-quality piece of software. I had an urge to make CDE useful for as many people as possible. I didn’t want it to languish as yet another shoddy research prototype that barely worked well enough to publish papers. I knew my e↵orts to polish up CDE wouldn’t be rewarded by the research community and might even delay my graduation since I could’ve spent that time developing new dissertation project ideas.
> Reject bad defaults: Defaults aren’t usually in the best interests of those on the bottom (e.g., Ph.D. students), so it’s importantto know when to reject them and to ask for something di↵erent. Of course, there’s no nefarious conspiracy against students; the defaults are just naturally set up to benefit those in power. For example, famous tenured professors like Dawson are easily able to get multi-year grants to fund students to work on “default” projects like Klee. As long as some papers get published from time to time, then the professor and project are both viewed as successful, regardlessof how many students stumbled and failed along the way. Students must judge for themselves whether their default projects are promising, and if not, figure out how to quit gracefully.
> Sell, sell, sell: I spent the majority of my grad school days headsdown grinding on implementing research ideas, but I recognized that convincingly selling my work was the key to publication, recognition, and eventual graduation. Due to the ultra-competitive natureof the paper publication game, what often makes the di↵erence between an accept and a reject decision is how well a paper’s “marketing pitch” appeals to reviewers’ tastes. Thus, thousands of hours of hard grinding would go to waste if I failed to properly pitch the big-picture significance of my research to my target audience: senior academic colleagues. More generally, many people in a field have good ideas, so the better salespeople are more likely to get their ideas accepted by the establishment. As a low-status grad student, one of the most e↵ective ways for me to “sell” my ideas and projects was to get influential people (e.g., famous professors such as Margo) excited enough to promote them on my behalf.
January 9, 2019
هو مذكرات "باحث دكتوراه" عن رحلة الدكتوراة! هناك الكثير من الفوائد في هذا الكلام! أولها أنك لابد ان تجتهد، وأنه مهما يكن مستواك العقلي فالاجتهاد يوصلك لحيث تريد. هناك في الطريق عدة عوامل مساعدة أهمها التوفيق ومنها الحظ.
أما عن العوامل المادية، فبالسنبة للجامعات الأجنبية تحتاج للتمويل، والمشرفين، ونشر اوراق بحثية في المجلات أو المؤتمرات الكبرى؛ التي من "الدرجة الأولى".
من هذه المذكرات يجب أن نتعلم تقديرنا لموقفنا وقدراتنا على حقيقتها دون مبالغة أو تهوين، فالكاتب يصف نفسه أنه "متوسط" ما بين زملائه، ويجب أن نحاول دائما أن نفهم طبيعة المجال الأكاديمي والتجاري، ونوفق بينهم وبين رغباتنا وطموحاتنا وما نحبه. ومن صدق الكاتب مع نفسه قرر أنه لا يصلح للعمل الأكاديمي الطاحن الذي وصفه، فهو "ما صدق" أن انتهى من بحث الدكتوراة، ولم يرغب أن يكمل في مجال التأهل للعمل الأكاديمي، لأن الحياة الأكاديمية عندهم شديدة التنافسية.
وبعد أذكر أن بدأت قراءة هذا الكتاب في 2016 بناء على ترشيح أحد الأشخاص على الفيس بوك، لما فيه من معاناة يلقاها الباحث، وقد كنت آنذاك أمر بمرحلة قاسية في لماجستير، فقد كنت سجلت منذ عامين، ولم أفعل شيء في بحثي، وكنت أقرأ ف��ط، وقد سبق أن جمعت المصادر والمراجع، لكني كنت أحاول أن أتعلم النظرية وأقرأ بمنهجية مستعينا ببعض الإرشادات من هنا وهناك. لكن عمل فعلي في لارسالة، لم يكن موجود منه شيء، وكنت كأني في حلقة مفرغة من الإحباط. واتجهت لقراءة كتب التنمية لابشرية وبعض النصائح عن إكمال البحوث ورسائل الماجستير والدكتوراة، وقد نفع هذا شيئا ما مع الاستعانة بالله، ومحاولة التواصل مع الجو الأكاديمي، والتخلي عن بعض الأفكار الخاطئة (مثل الرغبة في الكمال، ومثل التأجيل والتسويف).
أما عن العوامل المادية، فبالسنبة للجامعات الأجنبية تحتاج للتمويل، والمشرفين، ونشر اوراق بحثية في المجلات أو المؤتمرات الكبرى؛ التي من "الدرجة الأولى".
من هذه المذكرات يجب أن نتعلم تقديرنا لموقفنا وقدراتنا على حقيقتها دون مبالغة أو تهوين، فالكاتب يصف نفسه أنه "متوسط" ما بين زملائه، ويجب أن نحاول دائما أن نفهم طبيعة المجال الأكاديمي والتجاري، ونوفق بينهم وبين رغباتنا وطموحاتنا وما نحبه. ومن صدق الكاتب مع نفسه قرر أنه لا يصلح للعمل الأكاديمي الطاحن الذي وصفه، فهو "ما صدق" أن انتهى من بحث الدكتوراة، ولم يرغب أن يكمل في مجال التأهل للعمل الأكاديمي، لأن الحياة الأكاديمية عندهم شديدة التنافسية.
وبعد أذكر أن بدأت قراءة هذا الكتاب في 2016 بناء على ترشيح أحد الأشخاص على الفيس بوك، لما فيه من معاناة يلقاها الباحث، وقد كنت آنذاك أمر بمرحلة قاسية في لماجستير، فقد كنت سجلت منذ عامين، ولم أفعل شيء في بحثي، وكنت أقرأ ف��ط، وقد سبق أن جمعت المصادر والمراجع، لكني كنت أحاول أن أتعلم النظرية وأقرأ بمنهجية مستعينا ببعض الإرشادات من هنا وهناك. لكن عمل فعلي في لارسالة، لم يكن موجود منه شيء، وكنت كأني في حلقة مفرغة من الإحباط. واتجهت لقراءة كتب التنمية لابشرية وبعض النصائح عن إكمال البحوث ورسائل الماجستير والدكتوراة، وقد نفع هذا شيئا ما مع الاستعانة بالله، ومحاولة التواصل مع الجو الأكاديمي، والتخلي عن بعض الأفكار الخاطئة (مثل الرغبة في الكمال، ومثل التأجيل والتسويف).
January 18, 2013
I really like this book. I'm surprised that I can find it here, in Goodreads. I read The Ph.D. Memoir somewhen between June and July, 2012, during my critical time of writing a master thesis. It helped me a lot.
I got an interview recently for a Ph.D position, and I was asked many unexpected questions about how I think about working as a Ph.D, supervisors, teamworks, time management, and so on. It's hard to answer questions about experience that I haven't suffered. Well, thank to the book.
If you are seriously considering doing a Ph.D, this is the book for you.
I got an interview recently for a Ph.D position, and I was asked many unexpected questions about how I think about working as a Ph.D, supervisors, teamworks, time management, and so on. It's hard to answer questions about experience that I haven't suffered. Well, thank to the book.
If you are seriously considering doing a Ph.D, this is the book for you.
July 28, 2022
This is a realistic and multi-dimensional portrayal a PhD, and it throws light on many external factors that decide the success or the failure of a project. The motivation and incentives that drive various stakeholders, the marketing and pitching of a research idea, finding strategic collaborators and allies, all of these are not something a typical student knows before signing up to a PhD program. And that's where this book adds value, and would definitely lend additional perspectives to a prospective/current PhD student to better evaluate their decisions. Very insightful read!
June 10, 2017
It gives an insider's perspective to prestigious US PhD programs in CS but could have been shorter (Too much self-love?)
August 28, 2016
Gives some solid description of what doing a PhD is like (from at least one student's experience and perspective).
Points that resonated with me:
- Combining one's research project to practical needs but not end up maintaining it forever (which can hinder generation of new research)
- How many students drop out and that almost all the PhDs I meet are probably the exceptions (of course, because they went through the grind and chose to not give up).
- It can be full of rejections and one needs to develop an ability to (swiftly) recover from failure.
- How much of a role funding can play in one's freedom and research decisions.
- One may not be as dependent on their advisor as is usually said. Though, this can depend a lot on financial freedom (see previous point).
- Most of it is solitary, focused, hard work but if done successfully should result in immense fulfilment.
Points that resonated with me:
- Combining one's research project to practical needs but not end up maintaining it forever (which can hinder generation of new research)
- How many students drop out and that almost all the PhDs I meet are probably the exceptions (of course, because they went through the grind and chose to not give up).
- It can be full of rejections and one needs to develop an ability to (swiftly) recover from failure.
- How much of a role funding can play in one's freedom and research decisions.
- One may not be as dependent on their advisor as is usually said. Though, this can depend a lot on financial freedom (see previous point).
- Most of it is solitary, focused, hard work but if done successfully should result in immense fulfilment.
July 23, 2019
In this book, the author has included all his beautiful experiences and lesson he had learned from his Ph.D. days. It motivates you to work hard towards your goal and teaches you to never give up.
March 22, 2017
It was a very useful book for me, that gave me a deeper perspective on the PhD students' life and struggle, explaining the different steps and challenges he has encountered through his 6 years PhD experience.
January 29, 2019
Highly recommend for all who is thinking about doing a PhD in computer science or has been started already.
It’s motivating. It’s realistic. It’s well written.
And all of it is true.
Indeed might be also useful for understanding such people. If your girlfriend/boyfriend/wife/husband/partner is doing a PhD - this book might help you to understand they better.
It’s motivating. It’s realistic. It’s well written.
And all of it is true.
Indeed might be also useful for understanding such people. If your girlfriend/boyfriend/wife/husband/partner is doing a PhD - this book might help you to understand they better.
May 30, 2014
The Ph.D. Grind A Ph.D. Student Memoir is both a memoir and an analysis, by Philip Guo, of his years spent as a Ph.D. student at Stanford. Overall, I found the intention of the book laudable and the memoir useful, but the analysis biased and incredibly bad. In short, I think Philip, who struggled often during his Ph.D. despite being obviously smart, identified many important problems but mis-analyzed most of them.
First, a message to Philip: I think you have done a big service to the research community, by creating this book. I am also impressed by your courage to reveal the whole process and, why not, what you have perceived as problems. However, I also think you have treated many people in this book unfairly, that you have broken your promise of neutrality, and that you have presented research in your field in an undeserved bad light. (I wish you success at Rochester and hold no grudges, but I believe I can show that, often, the contrary of what you have written here is true.)
On the positive side, this is a well-written, short enough to maintain a high tempo, intriguing work on a much needed topic -- the trials and tribulations of young researchers in grad school; ok, ok, it's the story of an aspiring Ph.D. There are numerous interesting accounts, of the competition for resources, of the tough life on the cutting edge of research, of how to be unconventional and still succeed, of various kinds of perils, and, perhaps most importantly, on what the major problem of becoming dispirited (the "second-year dip", the depression, etc.) can mean to a Ph.D. student. These positive elements are all related to the memoir part.
On the negative side, it's the analysis. First, the claim that doing a memoir is novel. Most Ph.D. theses include a short memoir, written just after the completion of the main content, and presented as foreword or afterword of the published thesis. Such memoirs include thanks to colleagues (and reminisces on first meetings or memorable moments), discusses help for various chapters and main events in the process of conducting research for them, etc. In other words, I find Philip's claims presumptuos or uninformed (or both) from get-go.
This is the first time I felt deeply hurt by the writing of someone; I though it was impossible that Philip got it so wrong without malicious intent. From the starting pages, which present Philip's opinion that his writing is original and preferable to previous works on the topic, to the ending pages, where Philip is inconsistent in his lessons and quite pleased with himself, I found this book very difficult to bear. In simple words, I thought Philip was lazy at work, poorly skilled until very late in his PhD work, immature and full of double think throughout, presumptuous in strong claims, misinterpreting the process of research, and misleading in his analysis. I will give examples in this review.
I felt deeply, personally attacked by the way he casts a bad light on research very close to my field -- I work in distributed systems, where the period starting in the early 2000s has led to very significant progress, including in servicing scientists with low programming skills, which is at the center of Philip's thesis ---; he does this through an incredibly long (120+ pages) of white lies (omissions), games with statistics, incomplete and incorrect analysis, etc. I will also give examples about these.
I also felt Philip did a hatchet job on Dawson, whom I do not know, and on Cristi, whom I've had the pleasure of being high school and university colleague (and honored to be friends with) back in Romania. So call me biased---although I am used to review the work of people I know, some of which are friends, and still reject what I consider to deserve being rejected---, but, please, only after assessing my claims -- you owe me this if you did give the same benefit of the doubt to Phil.
Now for the numerous, yet selected negative examples:
1. Claims about the value of the book
- In general, claims of one's work's superiority over the others are common in the academia, but generally should be accompanied by quantitative and qualitative evidence. Philip rarely does so. In the words of Katie Roiphe, ''t is always satisfying to read a writer who sharply and deftly attacks the hypocrisies and delusions of the world around him, but we trust that writer more completely when he also attacks himself'' (a href="http://www.slate.com/articles/double_... to write a good memoir)
- On page vi, the author claims that writing immediately after finishing the Ph.D. is the ideal time to write such a memoir. I believe this is an unprovable claim at best. Intuitively, writing very close to a bad or elating experience is too biased.
- On page vi, the author claims ''balanced tone throughout'', in contrast to ''many people''. Which are the others who achieve balance? Why does he compare only to the most extreme (and thus less believable) of the authors who published similar writing? Why doesn't he give a couple of exemplary references for each of the un-balanced types? Most importantly: what is the support for the claim of balanced tone?
- On page vi, Philip identifies several sources of diversity. He does not include here personality, personal background (family, in particular), cultural background, prior education. He also mentions the department, but there is a very large difference between the research systems built across continents, and even countries, e.g., research in computer science in the US is not very similar with that in Western Europe, and both differ greatly from research in Asial; research in compsci is very different in India and China; etc.
2. Major issues I had with Philip Guo's book.
Hatchet job
- "I was not yet capable of submitting a respectable paper on this topic without their expertise and assistance, since I was merely an assistant doing manual labor" (p.35). Here, Philip claims there was no way he could contribute to research. But who prevented him to create new concepts? Who prevented him to even just adapt or extend the existing ideas?
- "This project fizzled due to a combination of my own lack of technical expertise and insufficient mentorship from senior colleagues." (p.35) This is another misleading analysis. During their 3rd year of Ph.D., students are certainly expected to be independent. In other words, the help he refers to here as "mentorship" should not be available anymore after so many years, so Philip should not be complaining about it.
- "In short, neither C. nor D. were truly hungry to publish." (p.36) I am not sure what "truly hungry" means, but I can only congratulate C. and D. for not wanting to give a Ph.D. an unfair advantage over other Ph.D. students at his seniority. In other words, Philip should have stopped complaining about others and should have found resources and skills in himself, after so many years of support.
- "We also experienced isolation and loneliness from spending day and night grinding on obscure, ultra-specialized problems that few people around us understood or even cared about." (p.37) This is a true hatchet job. First, the "spending nigth and day" turns out to be no more than 5 hours per day (p.114, next to "30 vacation days"). Second, Philip implies by association that specialization is bad; however, specialization is required to make significant worldclass advances and is common also in US engineering. Third, that only few people understand is exactly the reason for which automation and tools are necessary; in other words, it is a good motivation for Philip's work. Fourth, that few people care is an issue that also depends on the persuasion skills of the researcher. In other words, it is Philip's problem that he could not inform more people about why they should care.
- "They created a rough first draft, submitted a shoddy paper hastily written in three days (a debacle I remember all too well)" (p.39) This is true hatchet job. First, it is unlikely that the draft was created in 3 days, because he himself admits that the article structure (first step in creating the draft) was created early; in many processes it is also common to create the graphs and tables throughout the process, so not during the last 3 days. Second, even if the article was written in 3 days, there is no golden rule that relates the amount of days spent on an article and final quality; it may be better to write and polish for weeks, but there is no proof that I know that more than 3 days is a necessity.
- "The groundbreaking initial Klee work had already been done; all that remained were follow-up incremen- tal enhancements" (p.43) This is a hatchet job because it claims the work that was assigned to him by the professor could not lead to impactful publications. This is blatantly incorrect, as the initial paper has attracted over 600 citations, so there was enough room for another, and shows that Philip does not believe in creativity even for starting fields.
- "he knew how to advise me as a technical mentor and also how to craft the nuances of our paper submissions to maximize their chances of acceptance. In contrast, Dawson was an outsider [...] it felt amazing to finally experience what it was like to be on the winning team working alongside one of those professionals." (p.50) This is a true hatchet job. Philip started a phd w his own money. He refused to work on D's topics. He asked D for help on a topic on which D was not an expert; Philip knew this when he asked, but perhaps did not understand the implications. D agreed to help, likely hoping for Philip to learn enough and quickly about the target community. Philip didn't and, as Philip was given the responsibility to lead the project, the entire process failed badly. Then, Philip joined MSR and worked there under the close supervision of an expert. This is not D.'s fault and the comparison is idiotic. In other words, when working with D. at Stanford, Philip failed to act independently in creating new algorithms, which is a very challenging new task. When working with Tom at MSR, Philip succeeded in analyzing data under very close (daily) supervision.
Research Process
- He does not understand that a Ph.D. is like a start-up comany, with the founder(s) needing to worry about process, products, convincing customers, planning own deadlines, all against the winding down clock of financial resources. When the money runs out, the start-up founders have to move back to mommy's basement or get a job.
- There is no citation of a useful reference. There is, however, a dismissal from the preface of general books about doing a Ph.D.
- Unconventional research is perhaps this Finder of New Worlds.
- He never mentions second- and third-tier conferences. However, I have seen many Ph.D. students from MIT, Harvard, Stanford at these conferences. (Yes, I and my Ph.D. students also publish there. We also publish better.)
- He does not understand how finding bugs could be a research contribution (p.9). He seems to miss the point that the method of finding them is the research contribution. He also seems to miss the point that an experiment design can also be a research contribution, especially in fields where there are no benchmarks and standard methodologies for comparing alternatives.
- He seems unaware with theories of how scientific discovery occurs, in particular, with the role of scientific communities. He does not consider even Thomas Kuhn's The Structure of Scientific Revolutions; he seems to not understand that communities organize conferences and publication venues, and select for them work that adheres to the axioms, body of common knowledge, and norms of research method; it is not insiders and gray hairs, but ability to conform with these norms by anyone who is skilled enough. Big departures from these norms, if credible, cause revoutions. Incoherent departures cause just rejection of the applicant.
- He does not seem to understand that the "tremendous amount of unglamorous, grungy labor to produce results" (p.12) occurs in many other fields -- he often complains that he cannot understand how the tedious experimental work is leading to scientific contribution. I would remind him of Rutherford and of Curie's physics and chemistry experiments, of social and medical sciences, and of the testing part of engineering commercial products.
- He does not seem to understand that all-nighters, missed or barely made deadlines, and crunch time occur in most projects related to computer software, both in industry and academia. (I still remember producing gold disks for our software clients...) In fact, there is this saying that over 90% of the software projects fail.
- He obeys to the supervisor only because he believes strongly he will need his help to graduate. But this discounts that he needs help with the process of creating (so, not only of completing) a thesis... He also asks himself why he spent the first four months on working for some project, instead of "arrogantly demanding to do my own project from the beginning." Here is a far-fetched idea: could he have created most of the material first, with the money he got from NSF, and only then looked for a good supervisor?
- He receives from D. much help; among others, a list of adequate research questions (p.27), a challenge to think broader about the CDE (p.74), funding to go work with M. on M's topic (p.90), but there is no acknowledgement of D.'s help and ability. In contrast, there is plenty of failure attributed to the team, and for each major rejected article D.'s name appears before his own when listing the reasons for failure.
- The insiders are terrible when they prevent (in his opinion) his work to get published, but are excellent when they help him get an internship despite not deserving it achievement-wise ("I learned about the importance of being endorsed by an influential person").
- The schmoozing is disgusting, but only when done by others. Him going to Margo to ask for funding was just curtesy talk. This is double think at its best.
- After deciding to quit the academia, Philio has returned... at Rochester (at least this part I can understand -- it was not a turn-around in the span of a few pages of the same document).
Presumptuous in strong claims
- He is bored by "normal" engineering internships. (But then he fails with the more challenging assignments.)
- He consideres a top-end company to be large and successful, Google or Microsoft as examples. What about startups, for example Twitter and Pinterest? (Both grew while he was finishing his PhD.)
- He often claims that the system is built to "milk" the starting Ph.D.s (e.g., "There was no way to avoid paying my dues.") I find this presumptuous, and propose that instead the system recognizes merit. I believe he could have avoided working on doing technical work for others by (i) finding another group and work with them on a fun project for which he was in the lead -- this assumes he had excellent, recognizable tech skills; (ii) convincing others he is a desirable partner, using excellent social skills; (iii) could have agreed with the supervisor on doing something, but then have minimal or zero progress and focus instead on own top articlesl -- this assumes excellent research skills; (iv) could have tried to agree with the supervisor on a topic of his own choice, as he manages to do later with J. and M., and even with D.
- He claims that small improvements are never rewarded ("these kinds of minor improvements simply don't look impressive in a paper submission", p.37). This is contradicted by evidence -- for example, improving the accuracy of movie recommendations for Netflix users from say 91 to 94 percent means millions more happy users and tens of millions of dollars, and such seemingly small improvements trigger public competitions (e.g., Kellog's) and papers about successful attempts.
- He claims that "simply doing good work isn't enough to get noticed [nb: invited to a research internship in a top company] in a hyper-competitive field." (p.48) This ignores that many internships are gained by demonstrating the right skills -- a good presentation at a conference, a visit for a few hours prior to presenting in a major conference, an email informing of newly published work. Of course, this presumptuous claim cannot be verified, because Philip did not have good work to show; instead, he relied on connections and insider recommendation.
- "Back when he was a Ph.D. student, Jeff published 19 papers mostly in top-tier conferences, which is five to ten times more than typical computer science Ph.D. students. That's the sort of intensity required to get a faculty job at a top-tier university like Stanford." (p.83) Hmhm. If only the number would be 19. Or 42...
Misinterpreting the process of research
- He ranks conferences by acceptance ratio; tier 1 is for him the set of conferences with 8-16% acceptance ratio, tier 2 includes all conferences at 20-25%. What about the range 17-20%? What about conferences whose acceptance ratios fluctuate over the years between the two? What about conferences below 25%? This model misses out also on the location factor, where the same conference would receive way more submissions in places with few resources and lots of local researchers than in expensive places with few local researchers. The modern process, as credible researchers understand it, is different---in database research, VLDB and SIGMOD are the flagship (tier 1) conferences even if their acceptance ratios have exceeded those of EDBT and ICDE (tier 2). There are other models that also consider the impact, for which sometimes workshops are more impactful than some of the top conferences!
- He believes that the process is hierarchical because of the power conveyed by seniority and money: "In a typical research group, the professor and senior Ph.D. students create the high-level project plans and then assign the junior students to grind on making all of the details work in practice. First- and second-year students are rarely able to affect the overall direction of the group's project." (p.12). Could it be that the system is actually meritocratic? Could the alternative reason for the low impact of junior students on the direction of the project be that the junior students do not have the skill, expertise, and experience to change the direction? Could it also be that those few are actually the ones who have high chances of finishing early, of winning accolades and awards, and of getting the most competitive jobs? I have personally witnessed this at U Wisconsin-Madison, at UC Berkeley, at TU Delft, etc. I am sure there are other places that act as a meritocracy.
- He believes that it would have been impossible for him to get into a top-level conference without being aided by an insider. This does not explain how conferences such as SIGCOMM and SIGMETRICS get to accept work from groups that do not publish regularly there, does not explain how conferences gain and lose in prominence, etc.
etc. etc. etc.
To conclude
I would recommend this book to anyone wishing to learn about research. But be warned about the deeply flawed analysis.
First, a message to Philip: I think you have done a big service to the research community, by creating this book. I am also impressed by your courage to reveal the whole process and, why not, what you have perceived as problems. However, I also think you have treated many people in this book unfairly, that you have broken your promise of neutrality, and that you have presented research in your field in an undeserved bad light. (I wish you success at Rochester and hold no grudges, but I believe I can show that, often, the contrary of what you have written here is true.)
On the positive side, this is a well-written, short enough to maintain a high tempo, intriguing work on a much needed topic -- the trials and tribulations of young researchers in grad school; ok, ok, it's the story of an aspiring Ph.D. There are numerous interesting accounts, of the competition for resources, of the tough life on the cutting edge of research, of how to be unconventional and still succeed, of various kinds of perils, and, perhaps most importantly, on what the major problem of becoming dispirited (the "second-year dip", the depression, etc.) can mean to a Ph.D. student. These positive elements are all related to the memoir part.
On the negative side, it's the analysis. First, the claim that doing a memoir is novel. Most Ph.D. theses include a short memoir, written just after the completion of the main content, and presented as foreword or afterword of the published thesis. Such memoirs include thanks to colleagues (and reminisces on first meetings or memorable moments), discusses help for various chapters and main events in the process of conducting research for them, etc. In other words, I find Philip's claims presumptuos or uninformed (or both) from get-go.
This is the first time I felt deeply hurt by the writing of someone; I though it was impossible that Philip got it so wrong without malicious intent. From the starting pages, which present Philip's opinion that his writing is original and preferable to previous works on the topic, to the ending pages, where Philip is inconsistent in his lessons and quite pleased with himself, I found this book very difficult to bear. In simple words, I thought Philip was lazy at work, poorly skilled until very late in his PhD work, immature and full of double think throughout, presumptuous in strong claims, misinterpreting the process of research, and misleading in his analysis. I will give examples in this review.
I felt deeply, personally attacked by the way he casts a bad light on research very close to my field -- I work in distributed systems, where the period starting in the early 2000s has led to very significant progress, including in servicing scientists with low programming skills, which is at the center of Philip's thesis ---; he does this through an incredibly long (120+ pages) of white lies (omissions), games with statistics, incomplete and incorrect analysis, etc. I will also give examples about these.
I also felt Philip did a hatchet job on Dawson, whom I do not know, and on Cristi, whom I've had the pleasure of being high school and university colleague (and honored to be friends with) back in Romania. So call me biased---although I am used to review the work of people I know, some of which are friends, and still reject what I consider to deserve being rejected---, but, please, only after assessing my claims -- you owe me this if you did give the same benefit of the doubt to Phil.
Now for the numerous, yet selected negative examples:
1. Claims about the value of the book
- In general, claims of one's work's superiority over the others are common in the academia, but generally should be accompanied by quantitative and qualitative evidence. Philip rarely does so. In the words of Katie Roiphe, ''t is always satisfying to read a writer who sharply and deftly attacks the hypocrisies and delusions of the world around him, but we trust that writer more completely when he also attacks himself'' (a href="http://www.slate.com/articles/double_... to write a good memoir)
- On page vi, the author claims that writing immediately after finishing the Ph.D. is the ideal time to write such a memoir. I believe this is an unprovable claim at best. Intuitively, writing very close to a bad or elating experience is too biased.
- On page vi, the author claims ''balanced tone throughout'', in contrast to ''many people''. Which are the others who achieve balance? Why does he compare only to the most extreme (and thus less believable) of the authors who published similar writing? Why doesn't he give a couple of exemplary references for each of the un-balanced types? Most importantly: what is the support for the claim of balanced tone?
- On page vi, Philip identifies several sources of diversity. He does not include here personality, personal background (family, in particular), cultural background, prior education. He also mentions the department, but there is a very large difference between the research systems built across continents, and even countries, e.g., research in computer science in the US is not very similar with that in Western Europe, and both differ greatly from research in Asial; research in compsci is very different in India and China; etc.
2. Major issues I had with Philip Guo's book.
Hatchet job
- "I was not yet capable of submitting a respectable paper on this topic without their expertise and assistance, since I was merely an assistant doing manual labor" (p.35). Here, Philip claims there was no way he could contribute to research. But who prevented him to create new concepts? Who prevented him to even just adapt or extend the existing ideas?
- "This project fizzled due to a combination of my own lack of technical expertise and insufficient mentorship from senior colleagues." (p.35) This is another misleading analysis. During their 3rd year of Ph.D., students are certainly expected to be independent. In other words, the help he refers to here as "mentorship" should not be available anymore after so many years, so Philip should not be complaining about it.
- "In short, neither C. nor D. were truly hungry to publish." (p.36) I am not sure what "truly hungry" means, but I can only congratulate C. and D. for not wanting to give a Ph.D. an unfair advantage over other Ph.D. students at his seniority. In other words, Philip should have stopped complaining about others and should have found resources and skills in himself, after so many years of support.
- "We also experienced isolation and loneliness from spending day and night grinding on obscure, ultra-specialized problems that few people around us understood or even cared about." (p.37) This is a true hatchet job. First, the "spending nigth and day" turns out to be no more than 5 hours per day (p.114, next to "30 vacation days"). Second, Philip implies by association that specialization is bad; however, specialization is required to make significant worldclass advances and is common also in US engineering. Third, that only few people understand is exactly the reason for which automation and tools are necessary; in other words, it is a good motivation for Philip's work. Fourth, that few people care is an issue that also depends on the persuasion skills of the researcher. In other words, it is Philip's problem that he could not inform more people about why they should care.
- "They created a rough first draft, submitted a shoddy paper hastily written in three days (a debacle I remember all too well)" (p.39) This is true hatchet job. First, it is unlikely that the draft was created in 3 days, because he himself admits that the article structure (first step in creating the draft) was created early; in many processes it is also common to create the graphs and tables throughout the process, so not during the last 3 days. Second, even if the article was written in 3 days, there is no golden rule that relates the amount of days spent on an article and final quality; it may be better to write and polish for weeks, but there is no proof that I know that more than 3 days is a necessity.
- "The groundbreaking initial Klee work had already been done; all that remained were follow-up incremen- tal enhancements" (p.43) This is a hatchet job because it claims the work that was assigned to him by the professor could not lead to impactful publications. This is blatantly incorrect, as the initial paper has attracted over 600 citations, so there was enough room for another, and shows that Philip does not believe in creativity even for starting fields.
- "he knew how to advise me as a technical mentor and also how to craft the nuances of our paper submissions to maximize their chances of acceptance. In contrast, Dawson was an outsider [...] it felt amazing to finally experience what it was like to be on the winning team working alongside one of those professionals." (p.50) This is a true hatchet job. Philip started a phd w his own money. He refused to work on D's topics. He asked D for help on a topic on which D was not an expert; Philip knew this when he asked, but perhaps did not understand the implications. D agreed to help, likely hoping for Philip to learn enough and quickly about the target community. Philip didn't and, as Philip was given the responsibility to lead the project, the entire process failed badly. Then, Philip joined MSR and worked there under the close supervision of an expert. This is not D.'s fault and the comparison is idiotic. In other words, when working with D. at Stanford, Philip failed to act independently in creating new algorithms, which is a very challenging new task. When working with Tom at MSR, Philip succeeded in analyzing data under very close (daily) supervision.
Research Process
- He does not understand that a Ph.D. is like a start-up comany, with the founder(s) needing to worry about process, products, convincing customers, planning own deadlines, all against the winding down clock of financial resources. When the money runs out, the start-up founders have to move back to mommy's basement or get a job.
- There is no citation of a useful reference. There is, however, a dismissal from the preface of general books about doing a Ph.D.
- Unconventional research is perhaps this Finder of New Worlds.
- He never mentions second- and third-tier conferences. However, I have seen many Ph.D. students from MIT, Harvard, Stanford at these conferences. (Yes, I and my Ph.D. students also publish there. We also publish better.)
- He does not understand how finding bugs could be a research contribution (p.9). He seems to miss the point that the method of finding them is the research contribution. He also seems to miss the point that an experiment design can also be a research contribution, especially in fields where there are no benchmarks and standard methodologies for comparing alternatives.
- He seems unaware with theories of how scientific discovery occurs, in particular, with the role of scientific communities. He does not consider even Thomas Kuhn's The Structure of Scientific Revolutions; he seems to not understand that communities organize conferences and publication venues, and select for them work that adheres to the axioms, body of common knowledge, and norms of research method; it is not insiders and gray hairs, but ability to conform with these norms by anyone who is skilled enough. Big departures from these norms, if credible, cause revoutions. Incoherent departures cause just rejection of the applicant.
- He does not seem to understand that the "tremendous amount of unglamorous, grungy labor to produce results" (p.12) occurs in many other fields -- he often complains that he cannot understand how the tedious experimental work is leading to scientific contribution. I would remind him of Rutherford and of Curie's physics and chemistry experiments, of social and medical sciences, and of the testing part of engineering commercial products.
- He does not seem to understand that all-nighters, missed or barely made deadlines, and crunch time occur in most projects related to computer software, both in industry and academia. (I still remember producing gold disks for our software clients...) In fact, there is this saying that over 90% of the software projects fail.
- He obeys to the supervisor only because he believes strongly he will need his help to graduate. But this discounts that he needs help with the process of creating (so, not only of completing) a thesis... He also asks himself why he spent the first four months on working for some project, instead of "arrogantly demanding to do my own project from the beginning." Here is a far-fetched idea: could he have created most of the material first, with the money he got from NSF, and only then looked for a good supervisor?
- He receives from D. much help; among others, a list of adequate research questions (p.27), a challenge to think broader about the CDE (p.74), funding to go work with M. on M's topic (p.90), but there is no acknowledgement of D.'s help and ability. In contrast, there is plenty of failure attributed to the team, and for each major rejected article D.'s name appears before his own when listing the reasons for failure.
- The insiders are terrible when they prevent (in his opinion) his work to get published, but are excellent when they help him get an internship despite not deserving it achievement-wise ("I learned about the importance of being endorsed by an influential person").
- The schmoozing is disgusting, but only when done by others. Him going to Margo to ask for funding was just curtesy talk. This is double think at its best.
- After deciding to quit the academia, Philio has returned... at Rochester (at least this part I can understand -- it was not a turn-around in the span of a few pages of the same document).
Presumptuous in strong claims
- He is bored by "normal" engineering internships. (But then he fails with the more challenging assignments.)
- He consideres a top-end company to be large and successful, Google or Microsoft as examples. What about startups, for example Twitter and Pinterest? (Both grew while he was finishing his PhD.)
- He often claims that the system is built to "milk" the starting Ph.D.s (e.g., "There was no way to avoid paying my dues.") I find this presumptuous, and propose that instead the system recognizes merit. I believe he could have avoided working on doing technical work for others by (i) finding another group and work with them on a fun project for which he was in the lead -- this assumes he had excellent, recognizable tech skills; (ii) convincing others he is a desirable partner, using excellent social skills; (iii) could have agreed with the supervisor on doing something, but then have minimal or zero progress and focus instead on own top articlesl -- this assumes excellent research skills; (iv) could have tried to agree with the supervisor on a topic of his own choice, as he manages to do later with J. and M., and even with D.
- He claims that small improvements are never rewarded ("these kinds of minor improvements simply don't look impressive in a paper submission", p.37). This is contradicted by evidence -- for example, improving the accuracy of movie recommendations for Netflix users from say 91 to 94 percent means millions more happy users and tens of millions of dollars, and such seemingly small improvements trigger public competitions (e.g., Kellog's) and papers about successful attempts.
- He claims that "simply doing good work isn't enough to get noticed [nb: invited to a research internship in a top company] in a hyper-competitive field." (p.48) This ignores that many internships are gained by demonstrating the right skills -- a good presentation at a conference, a visit for a few hours prior to presenting in a major conference, an email informing of newly published work. Of course, this presumptuous claim cannot be verified, because Philip did not have good work to show; instead, he relied on connections and insider recommendation.
- "Back when he was a Ph.D. student, Jeff published 19 papers mostly in top-tier conferences, which is five to ten times more than typical computer science Ph.D. students. That's the sort of intensity required to get a faculty job at a top-tier university like Stanford." (p.83) Hmhm. If only the number would be 19. Or 42...
Misinterpreting the process of research
- He ranks conferences by acceptance ratio; tier 1 is for him the set of conferences with 8-16% acceptance ratio, tier 2 includes all conferences at 20-25%. What about the range 17-20%? What about conferences whose acceptance ratios fluctuate over the years between the two? What about conferences below 25%? This model misses out also on the location factor, where the same conference would receive way more submissions in places with few resources and lots of local researchers than in expensive places with few local researchers. The modern process, as credible researchers understand it, is different---in database research, VLDB and SIGMOD are the flagship (tier 1) conferences even if their acceptance ratios have exceeded those of EDBT and ICDE (tier 2). There are other models that also consider the impact, for which sometimes workshops are more impactful than some of the top conferences!
- He believes that the process is hierarchical because of the power conveyed by seniority and money: "In a typical research group, the professor and senior Ph.D. students create the high-level project plans and then assign the junior students to grind on making all of the details work in practice. First- and second-year students are rarely able to affect the overall direction of the group's project." (p.12). Could it be that the system is actually meritocratic? Could the alternative reason for the low impact of junior students on the direction of the project be that the junior students do not have the skill, expertise, and experience to change the direction? Could it also be that those few are actually the ones who have high chances of finishing early, of winning accolades and awards, and of getting the most competitive jobs? I have personally witnessed this at U Wisconsin-Madison, at UC Berkeley, at TU Delft, etc. I am sure there are other places that act as a meritocracy.
- He believes that it would have been impossible for him to get into a top-level conference without being aided by an insider. This does not explain how conferences such as SIGCOMM and SIGMETRICS get to accept work from groups that do not publish regularly there, does not explain how conferences gain and lose in prominence, etc.
etc. etc. etc.
To conclude
I would recommend this book to anyone wishing to learn about research. But be warned about the deeply flawed analysis.
June 11, 2017
I found the book very interesting. Although the Ph.D story is different from one student to another and from one field to another, I think Philip captured the main theme for what it takes to get the Ph.D. I think it is a good book and experience to read which gives a closer look and insight on the world of academia and research.
I truely felt a lot of the points he talked about. Also, I got many good advice to consider in the future.
I truely felt a lot of the points he talked about. Also, I got many good advice to consider in the future.
August 17, 2019
While going through the frustrations of a grad student this book motivated me a lot. This one is about the journey of a Ph.D. student in Computer Science, I am neither a Ph.D. student nor in computer science background still it overall gives a detailed description of a graduate student with all the challenges during the process and outcomes once you graduate!
July 20, 2017
Like the author said, this does not apply across all fields of PhD study but there are lessons one can glean from the experience of the author that applies across board.
Very nice memoir.
Very nice memoir.
May 20, 2020
Illuminating and surprisingly entertaining
July 1, 2020
A worthy read.
January 26, 2019
I wish I could have read it earlier.
I marked this book as want to read on another reading app some 400 days ago - around the time I stepped into the grad school. Back then, I still had a very simplistic view of research and what it takes. So I thought having passion on the subject was the most important factor in doing research. But my passion didn’t carry me far enough. I was rejected 4 times in my various scholarships application to a Ph.D offer at Imperial. The closest I have come to is a waiting list place at the last round of the President Scholarship - and I never get it.
Looking back, my advisor Stelios has done everything he could trying to help me secure the funding. Besides going through my proposal, CV and PS word by word, he also asked his colleague who is in the decision panel to offer me some suggestions. They did offer me some very useful suggestions such as how to pitch my proposal such that it would have a better fit to the industrial problems. However, my laziness, arrogance and the sole belief in passion has predetermined my failure. I did modify it a little, but never came to the extent of rewriting it to make it more appealing. (Just as the author says in the book, papers and funding applications need to be properly pitched)
In the end when it has become clear that I couldn’t stay in Stelio’s group which I have been working for a year (and love it!!), Stelios was disappointed but still wanted to make sure I could go to a good place. So he introduced me to a few of his colleagues who are in various research areas and has offered to write me reference letters and emails to his colleagues if I need. I was, too, disappointed and even heartbroken. However, I didn’t know such kind of failure in funding applications was normal in academia and I couldn’t see it from a positive light. I was simply heartbroken and didn’t take any of his suggestions serious enough to go through the painstaking application process again. I thought it was over.
The other reasons is that I thought I was so passionate on computational research that venturing into another field (especially groups doing experiments) would be a betrayal to the field I have been passionate about for so long. However, this seems so naive by now. I am now working on a multiphase flow Ph.D project in the industry. It has become so clear to me that be it experimental or numerical, it is nothing more than the methodology in solving the problems! And to understand the physics of the problem, the thinking hat as an experimentalist of how different variables are measured in real life experiments is extremely important even if you are (as I am) a modeler.
Being in the industry has also transformed me from an idealist to a pragmatist. Just as the author pointed out, results trump intentions. Developing something that maybe eventually useful in real life gives me the great motivation to work on the project.
And I have stopped trying to direct my project into certain ways that allow ‘’more enjoyable ‘’ methodology (such as coding rather than commercial software). I have realised what works the best (in terms of computational accuracy and cost) is the best solution. And making the fair choice is actually a morality requirement.
I wish I could have read it earlier and maybe things could have been different. However, even if I read it, I wonder if the words would resonate with me in such a strong way. That’s how life is - lessons are usually learnt the hard way.
I marked this book as want to read on another reading app some 400 days ago - around the time I stepped into the grad school. Back then, I still had a very simplistic view of research and what it takes. So I thought having passion on the subject was the most important factor in doing research. But my passion didn’t carry me far enough. I was rejected 4 times in my various scholarships application to a Ph.D offer at Imperial. The closest I have come to is a waiting list place at the last round of the President Scholarship - and I never get it.
Looking back, my advisor Stelios has done everything he could trying to help me secure the funding. Besides going through my proposal, CV and PS word by word, he also asked his colleague who is in the decision panel to offer me some suggestions. They did offer me some very useful suggestions such as how to pitch my proposal such that it would have a better fit to the industrial problems. However, my laziness, arrogance and the sole belief in passion has predetermined my failure. I did modify it a little, but never came to the extent of rewriting it to make it more appealing. (Just as the author says in the book, papers and funding applications need to be properly pitched)
In the end when it has become clear that I couldn’t stay in Stelio’s group which I have been working for a year (and love it!!), Stelios was disappointed but still wanted to make sure I could go to a good place. So he introduced me to a few of his colleagues who are in various research areas and has offered to write me reference letters and emails to his colleagues if I need. I was, too, disappointed and even heartbroken. However, I didn’t know such kind of failure in funding applications was normal in academia and I couldn’t see it from a positive light. I was simply heartbroken and didn’t take any of his suggestions serious enough to go through the painstaking application process again. I thought it was over.
The other reasons is that I thought I was so passionate on computational research that venturing into another field (especially groups doing experiments) would be a betrayal to the field I have been passionate about for so long. However, this seems so naive by now. I am now working on a multiphase flow Ph.D project in the industry. It has become so clear to me that be it experimental or numerical, it is nothing more than the methodology in solving the problems! And to understand the physics of the problem, the thinking hat as an experimentalist of how different variables are measured in real life experiments is extremely important even if you are (as I am) a modeler.
Being in the industry has also transformed me from an idealist to a pragmatist. Just as the author pointed out, results trump intentions. Developing something that maybe eventually useful in real life gives me the great motivation to work on the project.
And I have stopped trying to direct my project into certain ways that allow ‘’more enjoyable ‘’ methodology (such as coding rather than commercial software). I have realised what works the best (in terms of computational accuracy and cost) is the best solution. And making the fair choice is actually a morality requirement.
I wish I could have read it earlier and maybe things could have been different. However, even if I read it, I wonder if the words would resonate with me in such a strong way. That’s how life is - lessons are usually learnt the hard way.
February 21, 2019
I read this book when my PhD journey came to an end. It definitely provides me great insights when I look back what I have been through. Totally recommended for people intending to pursue a PhD degree, also who is on the way to obtain it.
September 22, 2018
I don't think I've ever read a book more made for me. I am computer science undergraduate student, with a passion for research. After graduation I plan to contribute to the field that lies in the intersection between computer science and psychology. But there's one problem. I have no idea what graduate school is like.
Enter "The PhD Grind," a chronicle of Phillip J. Guo's six years as a computer science PhD student at Stanford University. At only around 100 pages, Phillip (now Dr. Guo) doesn't waste time communicating anything other than essential information. He details what he spends his days doing (usually coding for 12+ hours a day), what's going through his head (usually fear he'll never graduate), and what's working out and what's not. Mixed in with all of this is him detailing how the connections he made ended up having a large impact on his success later in life. There's also interesting notes in the margin of the book which were written a few years after the PhD Grind was published and serve to give his thoughts in retrospect and provide updates as to what people mentioned are doing nowadays.
After reading this book, I left with a new general understanding of the intricacies of graduate school: how networking works at conferences, the keys to getting published, how students are restricted to work on certain projects due to grant funding, which professors to align oneself with, what it takes to graduate, and even why so many people drop out of PhD programs. I'd recommend this book to anyone who is curious to know more about what graduate school is like from a first person point of view that is detailed and not super generic like a lot of blog posts out there. Be warned though, as the experiences of graduate school for someone getting a doctorate degree in computer science is very different than someone getting a doctorate in say, anthropology.
Enter "The PhD Grind," a chronicle of Phillip J. Guo's six years as a computer science PhD student at Stanford University. At only around 100 pages, Phillip (now Dr. Guo) doesn't waste time communicating anything other than essential information. He details what he spends his days doing (usually coding for 12+ hours a day), what's going through his head (usually fear he'll never graduate), and what's working out and what's not. Mixed in with all of this is him detailing how the connections he made ended up having a large impact on his success later in life. There's also interesting notes in the margin of the book which were written a few years after the PhD Grind was published and serve to give his thoughts in retrospect and provide updates as to what people mentioned are doing nowadays.
After reading this book, I left with a new general understanding of the intricacies of graduate school: how networking works at conferences, the keys to getting published, how students are restricted to work on certain projects due to grant funding, which professors to align oneself with, what it takes to graduate, and even why so many people drop out of PhD programs. I'd recommend this book to anyone who is curious to know more about what graduate school is like from a first person point of view that is detailed and not super generic like a lot of blog posts out there. Be warned though, as the experiences of graduate school for someone getting a doctorate degree in computer science is very different than someone getting a doctorate in say, anthropology.
November 17, 2018
Ah haa finished this 115-page book about Dr. Philip Guo's Ph.D. journey on a super busy but procrastinating sunny Sunday.
The memoir was written as Dr. Guo reflected on his 6-year experience as a CS Ph.D. student in Stanford. As I read the book, his years were filled with SO MANY ups and downs yet he kept on pushing pushing working working and he succeeded! At the end of the book, he described his experience as "funny at times but fulfilling".
This book is short but is so REAL. Anyone who is a Ph.D. student, or considers to do a Ph.D. definitely should read it!!
Funny enough I have been starting to use his tool (pythontutor.com) to support my daily Java study without knowing the tool's founder has such inspiring research story.
My boyfriend suggested me the book when I was feeling stressed with my work and was crying messaging him about how much I questioned my decision to walk on this path (seems too soon for a 90-day-old Ph.D. student). But yeah who knows just a day after that whining night things started to work out as I kept on and pushed myself a little bit harder and woalaaa now I have time to read it!
The memoir was written as Dr. Guo reflected on his 6-year experience as a CS Ph.D. student in Stanford. As I read the book, his years were filled with SO MANY ups and downs yet he kept on pushing pushing working working and he succeeded! At the end of the book, he described his experience as "funny at times but fulfilling".
This book is short but is so REAL. Anyone who is a Ph.D. student, or considers to do a Ph.D. definitely should read it!!
Funny enough I have been starting to use his tool (pythontutor.com) to support my daily Java study without knowing the tool's founder has such inspiring research story.
My boyfriend suggested me the book when I was feeling stressed with my work and was crying messaging him about how much I questioned my decision to walk on this path (seems too soon for a 90-day-old Ph.D. student). But yeah who knows just a day after that whining night things started to work out as I kept on and pushed myself a little bit harder and woalaaa now I have time to read it!
October 5, 2019
Guo lucidly talks about his experience as a PhD student at Stanford in this short memoir. I found that a lot of it reflected my wife's experience as a PhD student (biotech), and I think the insights are far more widely applicable than what the author would admit in his humility. I would also couple this book with Cal Newport's books on research productivity (Deep Work, So Good they can't ignore you).
But I wonder how he ended up as a faculty at UCSD after he decides to leave academia at the end of this book =)
But I wonder how he ended up as a faculty at UCSD after he decides to leave academia at the end of this book =)
July 24, 2012
It's neither inspiring, nor discouraging. It's just a summary of the author's life as a PhD scholar. It was interesting to know what actually happens behind the scenes of this penultimate stage of an academic career. Apparently it's not about free food and free travels to different different places to attend conferences. There is a large chunk of boring stuff involved.(Sorry for the spoiler :P)
March 24, 2019
Tự truyện của một nghiên cứu sinh Khoa học máy tính tại Stanford. Cả cuốn sách là chặng đường chinh chiến nặng nề chông gai, nhiều lúc mình phải bỏ sách xuống để thở.
February 9, 2014
Excellent read! A must for all those interested in pursuing a PhD degree in the US.
January 3, 2017
Brutally honest!
December 17, 2015
If you are in grad school, you should read this book. Though the grad life experience might differ from person to person, some of the stuffs you can relate to yourself for sure.!!!
January 6, 2023
Did not finish (stopped halfway through year 4 and skipped to epilogue - hopefully not foreshadowing) but what I read had good information.
September 9, 2019
Read it in a single night through multiple sittings; me being at the cross road of my transition from an undergraduate to a (prospective?) graduate student.
Quick paced, descriptive yet not boring. It provided an alternative reality check to my self conceived notions of grad life. Would call it an honest attempt to make you aware of the rather not-so-straightforward journey a PhD might turn out be. Nevertheless it does highlight the untold joys, satisfactions and (soft-skill based) learnings of the journey itself.
Some interesting #Takeaways
* Contrary to romanticized notions of a lone scholar sitting outside sipping a latte and doodling on blank sheets of notebook paper, real research is never done in a vacuum. There needs to be solid intellectual, historical, and sometimes even physical foundations (e.g., laboratory equipment) for developing one’s innovations.
* "...it’s going to be really hard for me to push ahead with a Ph.D. project unless I feel a strong sense of ownership and enthusiasm about it, so I really want to work to find the intersection of what I feel passionate about and what is actually deemed ‘research-worthy’ by professors and the greater academic community.”
".. I’d also add fundable as an extra criteria for success. "
* "..I discovered over the past 5 years that I love being a spectator of research, but the burden of being a continual producer of new research is just too great for me."
* Here is an imperfect analogy: Why would anyone spend years training to excel in a sport such as the Ironman Triathlon....
this experience pushes people far beyond their physical limits and enables them to emerge stronger as a result.
# Some points from his 20-point summary :
1. Results trump intentions
2. Outputs trump inputs
4. Create lucky opportunities
5. Play the game
9. Pay some dues
10. Reject bad defaults
12. Recover from failures
18. Express true gratitude
19. Ideas beget ideas
20. Grind hard and smart
Quick paced, descriptive yet not boring. It provided an alternative reality check to my self conceived notions of grad life. Would call it an honest attempt to make you aware of the rather not-so-straightforward journey a PhD might turn out be. Nevertheless it does highlight the untold joys, satisfactions and (soft-skill based) learnings of the journey itself.
Some interesting #Takeaways
* Contrary to romanticized notions of a lone scholar sitting outside sipping a latte and doodling on blank sheets of notebook paper, real research is never done in a vacuum. There needs to be solid intellectual, historical, and sometimes even physical foundations (e.g., laboratory equipment) for developing one’s innovations.
* "...it’s going to be really hard for me to push ahead with a Ph.D. project unless I feel a strong sense of ownership and enthusiasm about it, so I really want to work to find the intersection of what I feel passionate about and what is actually deemed ‘research-worthy’ by professors and the greater academic community.”
".. I’d also add fundable as an extra criteria for success. "
* "..I discovered over the past 5 years that I love being a spectator of research, but the burden of being a continual producer of new research is just too great for me."
* Here is an imperfect analogy: Why would anyone spend years training to excel in a sport such as the Ironman Triathlon....
this experience pushes people far beyond their physical limits and enables them to emerge stronger as a result.
# Some points from his 20-point summary :
1. Results trump intentions
2. Outputs trump inputs
4. Create lucky opportunities
5. Play the game
9. Pay some dues
10. Reject bad defaults
12. Recover from failures
18. Express true gratitude
19. Ideas beget ideas
20. Grind hard and smart
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