from Guide to the PhD on Oct 16, 2022

How to write your personal statement, for PhD admissions

Most personal statements make for great origin stories — the prodigal 5 year-olds born to love deep reinforcement learning. Few, however, tell the stories PhD admissions committees are actually looking for: telltale signs of research savvy.

Like most PhD students, I've reviewed hundreds of applications for my university's PhD admissions committee. I've seen a large number of personal statements, both formally and informally. Fortunately, I've seen a number of great personal statements, better than my own. However, admissions is a crap shoot — there's a ton of luck involved, so your personal statement can't just be "good"; your statement has to be as pixel perfect as it can be — you're the opportunity of a lifetime and a PhD student no adviser will want to miss.

This post is written broadly for any applicant — you could have a modicum of research experience1, tangentially related experience, or no experience at all. You could be an undergraduate, an industry veteran, or a master's student. Even for applicants with extensive research experience, I highly recommend reading this post. No matter the research experience, candidates have made all sorts of mistakes in their personal statement that could cost them invaluable reader attention. It's important to note that your recommendation letters are paramount in the application process, but the personal statement is the most controllable portion. Note these tips are written with the AI field in mind, where publishing is accessible and there are many conferences; the rules may differ in, say, mathematics PhD admissions. I will try to provide tips as general as possible.

In the section below, we'll start with the mindset of an application reader. This is the most important part, so you can understand the context for later suggestions and understand subtle tweaks I don't get to here.

Qualities we look for, in you.

Application readers are looking for candidates that would make great PhD students. This is an obvious end goal, but what makes a great PhD student is more nebulous. Here is a rough breakdown of the qualities we're trying to assess; I'll address several points you may have heard about admissions:

  1. Show research readiness: Are you ready to conduct "high caliber" research? All of the below qualities are proxies for this. One obvious indication of readiness is to already be conducting research, published at known venues for your field. For AI admissions, you may have heard that top conference papers are necessary — NeurIPs, ICML, ICLR, CVPR, E/ICCV, ICRA, CORL, EMNLP etc. Unfortunately, given the number of applicants for AI admissions, having publications at these venues is almost an unvoiced requirement. However, you can still demonstrate research readiness without publications at these venues, or any venue for that matter. Below are several proxies for research readiness; I've certainly seen applicants get accepted by having one or more of these categories, in lieu of publications.
  2. Deeply understand a problem space: Do you understand what an "interesting" problem is? This is often the basis for accepting applicants with industry experience, when the personal statement exemplifies this deep understanding. Notice I did say "a" problem space. It could be a problem space that academics are familiar with or, even more impressive, a problem space that academics are not actively working on but should be. For example, I knew one applicant who spent several years working on compiler optimizations at Tesla Autopilot; he subsequently had no problems applying to PhD programs, as he understood problems associated with real-world model deployments. Most importantly, this candidate brought a unique perspective on edge AI models that is difficult to obtain in academia.
  3. Recognize and distill takeaways: Can you recognize an interesting insight? This is important for two reasons: (1) to pitch your own work and (2) to sift through large bodies of research, to find the nuggets you need for your work. The first facet of this quality is a bit simpler to assess: In your statement, how clearly do you communicate the insight for your own projects? This is the baseline: You should be able to communicate, at minimum, the technical insight that makes your work valuable. Given you've ideally spent many hours thinking about and working on those projects, these are the projects you should be best-equipped to distill into a few sentences. The second is difficult to convey and to assess in your statement, but the conclusion can be utilized for this. We'll discuss specific examples of this later on.

There are 3 meta-points to make about your personal statement. These aren't qualities we're looking for per se, but you'll need these properties to make your case:

At the end of the day, the PhD admissions committee is looking for researchers to invest in. They aren't picking applicants for their research agenda, for example, so really focus on exemplifying these qualities. Notice none of these qualities require publications per se; publications are, like most other things, just a proxy for these qualities that predict your future trajectory as a PhD student.

How we (try to) identify these qualities.

It's hard to assess and catch all nuances that justify your research readiness, so your goal is not just to state proof. Your goal is to make it extra extra clear that you are well-equipped to conduct high caliber research. In this section, I'll describe how I read the personal statement, so you can get an idea for where your reader's attention could falter or be reinvigorated:

  1. Read the introduction to see if I should continue reading. I skim the introduction to find evidence of readiness: publications, experience, etc.

    1. If I don't find clear statements of these, I'll skim the rest of the personal statement to find these indicators. Assuming I don't find any, I'll mark down that the personal statement does not add new perspectives or context to the application.
    2. If I do find clear statements of this evidence, I make a quick note of these. I'll then check them off, with extra notes as I proceed through the statement.
    3. Experience is relevant background for the field. For example, if applying for AI-CV (Computer Vision), the applicant could have spent significant amounts of time working with real-estate captures from professional and handheld cameras. In this case, research readiness comes from a working understanding of photos used in real-world applications. We value perspectives we don't have.
  2. For each project in the statement, I'll look for key parts of the "research story": problem, insight, and impact. Often times, the project description is a jumble of facts that partially or don't address these pieces. If I spot a familiar venue (e.g., one of the conferences listed above), then I'll let a less-clear statement of the problem or insight pass. In one scenario, I saw a paper that I had previously cited and read! This is of course very rare, but this left a very strong impression that I still remember today. Even (and maybe especially) in the absence of a known venue, always include the problem statement, technical insight, and quantifiable impact for your projects:

    1. Look for a problem statement. Is it interesting? Important? Is it even mentioned and clearly explained? Often, the paragraph jumps straight to the solution. For example, "we applied a 3D convolutional neural network to detect tumors". This is completely uninteresting. We'll talk about ways to fix this later on. At this point, I'm trying to assess the significance of the project.
    2. Once I understand the problem, I'll look for the main insight. Does it teach me something new? How is it used to solve the problem? At this point, I'm looking for cleverness that I can appreciate and remember. If so, I'll note that down.
    3. After the problem and insight, I'll look for results and impact. The result is ideally quantified in some form — an accuracy number or percentage latency reduction for example. Impact is a bonus here — it could be the new applications it enables, or in very rare cases, a real-world application it benefits.
    4. It's worth re-emphasizing here that the project doesn't need to be published to be interesting. A recognizable venue is (sometimes) an indicator that the project is already interesting, certified by another researcher in the field. However, there are certainly statements that do a good job of discussing non-published work, by addressing the points in the process above.
  3. For the conclusion, I'll look for a description of interests. Are they interested in sensible problems? I again look for problem and insight. For obvious reasons, I'm no longer look for results but a statement of the impact it could have, is important. At this point, provided I'm convinced the applicant is research-ready, I'm looking for reasons to be excited about their future. I'll make a note of their future research direction. Added bonus if I happen to think this candidate would be a great fit for my adviser's group. In which case, I'll also ping my adviser to let him know to check out this application.

The process above is pretty barebones. There are specific items I'm looking for, and the rest of this post will discuss mistakes and recommendations that optimize for these items.

Always include the problem statement, technical insight, and quantifiable impact for your projects.

Top 3 mistakes: Origin stories, non-problems, what instead of why.

Here are the top 3 mistakes in personal statements. Without sugar coating, these mistakes waste space by addressing none of the qualities readers are looking for.

To avoid all of these mistakes and more, do the following: For every piece of your personal statement, ask yourself: does it show research readiness? Here are the top mistakes that fail this criterion:

For every piece of your personal statement, ask yourself: does it show research readiness?

The most important takeaway is to avoid any sentences that do not suggest research readiness. Get to the point and do so concisely. Next, we'll discuss concrete tips and walk through examples.

Tips for writing your personal statement.

There are effectively 3 sections to your personal statement: the introduction, summarizing your research readiness; project descriptions; and the outro, expressing your research interests for future work. Below, I'll describe some general tips for writing each of these sections. For a collection of online personal statements, see Alex Lang's collection for the NSF GRFP, where you can judge how well each statement leaves an impression on you.

Introduction. The introduction is fairly simple. It simply summarizes all the facets of your research readiness. The most important part is to summarize the rest of the statement. There are 4 categories of topics to include at this stage, at least in the successful statements I've seen:

Your problem description should explain (a) why this problem is challenging to solve and (b) why this problem is important to solve.

Project. Each subsequent paragraph should effectively cover a new project. Every project should in turn feature the 3 parts of a problem that we discussed earlier: problem statement, technical insight, and quantifiable impact. Note that even if your project is not ultimately published, you can still use it to your advantage by following these guidelines. Making these parts clear is more important than the status of your project, as you ultimately need to convince your reader that your work is important.

Here are a few more notes about project paragraphs:

Outro. Your final paragraph should indicate your future research interests. Express interest in PhD-student activities, most definitely in research and possibly in teaching, mentorship, presenting technical content, and service to the research community.


There are certainly exceptions to the guidelines I've provided above. There are other fields that may be more interested in the origin stories. There may also be applicants that wrote a wishy washy personal statement and were still accepted; I would argue these are the exceptions and not the rule. The above tips gear your personal statement up to be the most efficient at communicating your work these past few years. If anything, it's worth putting in the extra time now, as an extra few hours now will matter disproportionately much.

You can find my own personal statement, which I used for both my fellowship applications2 and for PhD applications in general, at this webpage with fellowship application tips.

back to Guide to the PhD

  1. There's an ongoing debate about the amount of research an applicant should have — applicants already living the life of a PhD student are no-brainers to accept, but not all applicants have equal access to research; in these scenarios, it's hard to predict how well the student would perform when given the opportunity. I won't cover the debate in this post. Instead, regardless of your experience, this post is about maximizing the clarity and "impressive-ness" of your statement. 

  2. Different fellowships, such as the National Science Foundation's Graduate Research Fellowship Program may have guidelines that suggest a different approach. Following the above approach to make your personal statement clear won't hurt, but there may be more asks in the guidelines, depending on your year's prompt.