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Mor Naaman / Lab PhD Syllabus

While we give explicit guidance to our students in the classroom via our syllabi, we don’t do that for our PhD students. This document is meant to capture the expected experience – with its requirements and offerings, benefits and drawbacks – of a PhD student working with me as an advisor, as part of my lab at Cornell Tech.

Credits, Rights and Disclaimers

This document was authored by Mor Naaman, borrowing heavily from Eric Gilbert’s PhD syllabus, and takes inspiration (and some text) from Sarita Yardi Schoenebeck’s note about student advising as well as others. While I often borrowed their ideas and many of Eric’s own words (with permission), I stand behind the text in this document, which, in this instance, only represents my own views, practices, and attitudes. I encourage you to refer to their notes for their thoughtful texts and more comprehensive cover of some of the topics. For example, this document focuses on the technical aspects of a PhD, while Eric’s notes touch more deeply on some of the more, let’s say, existential questions around this experience, as well as adding some tips about PhD topics like giving talks. Eric’s syllabus also provides pointers to other sources of PhD advice.

This is intended as a living document. I will update it as new topics that represent a significant part of the PhD experience arise, and as a response to feedback from advisees and others (or as I change my mind and approach to PhD advising). As with all guidance you get in academia, take caution when applying it to your situations and contexts. Cornell students should view this document as complementary to the Cornell doctoral student resources and guidelines. The Cornell PhD programs pages in Information Science and Computer Science also have useful information and advice; if these pages have any information that contradicts my notes below, they are to be believed first.

This text is licensed under CC BY-NC 4.0. PhD advisors should feel free to borrow from this text (please also credit the past contributors), as was done for example in this excellent guide from the UW Makeability Lab.

The What and Why of a PhD

Advising and working with PhD students is perhaps the best part of my job. In fact, it is probably the main reason I chose to be a professor. PhD students are my most central and essential collaborators. The two main goals of my work with PhD students are (1) to produce great research and advance the world’s knowledge, and (2) to advise and train the student to become independent, knowledgeable, critical, and capable researchers.

The main requirement for your PhD is to be passionate about scientific inquiry – pursuing research ideas and questions – and being willing to develop the methodological depth and expertise to address these ideas in the most robust-yet-attainable manner.

This is also your PhD, by which I mean:

By contrast, I don’t believe the PhD is any of the following things:

Toward all these ends, I will aim to give you as much independence as I think you can handle (and maybe a little more), as early as you can and want to have it. I try to assess this on a case-by-case basis; if you feel like I misjudged it any time (e.g., too much or too little), please let me know. The general path is increasing independence over the PhD. You will see this philosophy echoed throughout this document.

How long is a PhD?

I tend to believe that the PhD is over when you:

  1. Have satisfied the minimum requirements of the program
  2. Have made significant academic contributions*
  3. Can get the job you want.

The PhD tends to take my students between 5 and 6 years—with students headed to the academic job market leaning toward the longer end. While not impossible, I have not had a PhD student finish in 4 years.

*This is the tricky one – to be decided by me as your advisor and your committee


Your PhD comes with guaranteed funding (i.e., stipend, tuition, health insurance) as long as you are in “good standing” according to the departments’ annual review, which generally tends to mean “while you are in the program” (more about dropping out below).

This means you are guaranteed to have a fellowship, Graduate Research Assistantship (RA, or GRA as Cornell calls it), or Teaching Assistantship (TA) to support you throughout your time at Cornell.

It is my role – in fact, one of my major tasks – to make sure that you are supported by a GRA or fellowship for as much as your PhD as possible. Your PhD program will require some (typically two) semesters of TA during your PhD, and you may be asked to do more of them – but ideally, you’d do TA semesters only as needed.

GRA/RA generally means some sort of grant, gift, or research award supports your work. Again it is my role to raise this money to support your research, or to fit your research into funding that I already have (more below on choosing research directions). While it is possible that you will be asked to do an RA role that is not related to your research, it is unlikely. It is also possible that later in the PhD I will ask you (or you will initiate) for your help in writing a grant proposal in your area. This would be great practice for you as a future academic.

GRA and TA both represent a certain, bounded amount of work in terms of hours per week. In both cases your PhD work should be filling the rest of your working hours. As mentioned above, it is very likely that you will have a GRA that overlaps with your PhD research; making the “weekly hours” GRA bounds less relevant, as it will be indistinguishable from your PhD work.

I do expect you to apply for appropriate fellowships during your PhD. Such fellowships include for example the NSF Graduate Fellowship, or corporate fellowships like Microsoft’s. Usually these applications are not too much work, and as a side benefit require you to articulate your research vision and interests. When you get one, everyone benefits: you are more flexible in your work to pursue your research direction without the pull of funding needs; I spend more time with you and less time getting grants; and you get a recognition that goes on your CV.


Your stipend is determined by the Graduate School at Cornell. The PhD stipend is by no means a lot of money, but I believe people have found that it supports a comfortable life that allows you to focus on your studies, even in NYC. Note that there is a stipend supplement for NYC-based students who get a slightly higher stipend than Ithaca-based students (see more about location below), recognizing the different cost of living.

Relatedly, there is an expectation that your PhD will be your full-time work. A part-time PhD with me is not an option, though internships are possible and even recommended (see below).

Doing Research

The most important thing you do in graduate school is your own research. It may seem obvious, but it’s easy to lose track of the importance of your own research amid all the other competing things you’ll be asked to do in grad school: take classes, review papers, help teach a class, run a working committee, organize various activities, etc. Some of these will be fun; many of them will feel more important at the time than making (what may seem like limited) progress on your research.

Selecting problems

I advise students to aspire for impact in their work. Not by accident, this is also what I hope for in my work (which of course intersects and overlaps with your work). It’s important to have impact in mind when you approach problems (that is, before you select and commit your time to them). Some guidelines on impact might include:

What difference will this work make if you succeed?

Who will care about it when you’re done?

How will this change what other people (defined broadly) are doing?

Eric Gilbert recommends Hamming’s lecture on this topic which one day I will read and endorse here more directly (or not).

Discipline, Methods, and Contributions

I am a professor of Information Science at Cornell, as well as a field member in Computer Science. This means I can be the main advisor for PhD students in both these programs.

Having said that, especially in Information Science, the type of contributions you make and the type of methods you might use vary significantly. I don’t like labels, but if I had to align myself with one research paradigm, I would point at pragmatism which is “based on the proposition that researchers should use the philosophical and/or methodological approach that works best for the particular research problem that is being investigated” (Kaushik and Walsh 2019).

As such, my students end up doing work that ranges from qualitative methods such as semi-structured interviews, to quantitative methods like online experiments and large-scale data collection and analysis, to computational methods such as system building and evaluation as well as developing computational techniques based on machine learning or algorithms of various types. Very often, it is the same student that applies more than one of these methods for their PhD work.

Expected Output

See Eric’s syllabus for an important discussion of quality vs. quantity.

This is a note about what you should strive to achieve in terms of output during your PhD. This is not necessarily what I expect to see as your output – but what you should expect to try to produce. These expectations are also averaged over multiple years. You should expect to produce less in your first and second years (for example, it’s totally ok to have only one project to begin with, possibly through a collaboration with a senior student), and more in your third and fourth (often dropping again in the final year while you are searching for jobs).

  1. Try to produce one very high-quality, high-risk paper per year. This should yield 3-4 actually published versions of these, on average, over the span of your PhD. Some of these papers won’t get in somewhere competitive, or may simply not work out well into the research process (e.g., approach didn’t work, context of the problem changed, etc.). That’s the nature of research work like this. This is the most important type of output you might produce in your PhD.

  2. Concurrently, try to have a straightforward project underway. This is the lower-risk, lower-reward paper. 1.5 of these every 2 years seems like about the right fit (i.e., slightly less than one of these projects ongoing, per year). More of these should get published, and fewer of them will fall apart along the way. That’s the nature of this work. This might be in collaboration with a larger group, but you should play a significant role. This is important for your sense of progress, as the more challenging work might stall and frustrate. This is also important to get exposure for you and your ideas in a wider set of venues.

  3. Concurrently, try to be a supporting author on at least one other project. This isn’t your core work: it’s being led by someone else. It should take less than ½-⅓ of a day of your time per week. But you have something to offer, and expect to be listed in a supporting author position. Also of the lower-risk, lower-reward variety. This type of contribution is important for you to become known (even locally) for your expertise; improve collaboration skills, and in general contribute to your immediate academic community.

Note that if all of these are going on, and with other tasks and roles you will be taking, you are likely to have your plate feel very full. You will need to make sure you balance your time, and not forget to take time off (more of these considerations below).

Research Ideas and Directions

Have ideas!

Seriously, I do not like supervising a student without their own ideas—nor do I think it’s good for your development as a scholar. As noted above, the major thing that we’re doing here is turning you into a world-class scholar. One key way you do that is by coming up with new ideas. Moreover, it’s important for being competitive in academic job applications; those evaluations are impacted by your future work ideas, not only your work to date.

Good ideas are rare and are hard to come by. Michael Bernstein’s writeup has ideas about ideas, making a strong argument “to go for volume”. You should read it. Most of my ideas, which you can expect to hear plenty of, are bad, and that’s OK (memorable quote from a student to me during their Cornell A (qualifying) Exam: “this is actually not a bad idea!”). I love to hear ideas, good or bad – some might turn out to be the opposite after a short (or long) discussion. Ideas are everywhere, and if you let yourself, you’ll have them all time. It can be easy in graduate school to find yourself submerged in the details of ongoing projects constantly, without popping up to think about and consider new projects, ideas, and directions. Both are important: a good scholar can move between levels of detail (i.e., “What’s the right statistical technique for these data in this paper?” to “Which of these 5 new ideas would have the most impact?”).

Where to find ideas Some concrete ways in which one might find good ideas:

I recommend finding a good way to keep track of ideas. Eric reports using a file called “ideas.txt” where he adds new ideas as they come to mind. I use Evernote, using a note for each new idea with the searchable text “research idea”. A research notebook (note: use a Moleskine for the “I know what I’m doing” look) is another way to keep track, although it’s perhaps not as easily searchable.

Importantly, while there is no such thing as “too many ideas”, you shouldn’t pursue more than a few at a time, and carefully balance new ideas with ongoing work. Which brings us to…

Deciding on Ideas to Pursue

I am often asked who decides which ideas and research direction to pursue. Can a PhD student choose any topic and research direction? Do I dictate research agendas and projects to the student? The reality is that we decide together on which ideas and directions to work on. It’s an iterative, long term process that results in the alignment. It starts when students pick to work with me – and I with them – because we have a shared interest. I am likely to steer new students towards directions and questions that I think are interesting (sometimes new, sometimes existing), especially projects which I have funding to work on. But I never “assign” projects – if the student is not excited and motivated about a research direction, the outcome is not likely to be good. Similarly, students can pursue a project that I am less interested in, but that results in me being less engaged and less helpful as an advisor. The process of coming up with ideas, research questions, and project decisions thus naturally gravitates towards mutually interesting directions that overlap with existing or potential funding.

At the same time, “interest splits” happen, and students often pursue questions and directions. If there’s no overlap, one option is to switch advisors. I have had students leave me to work with other advisors as it became clear that their pursuit and intellectual passion does not overlap with mine (two come to mind in recent years; both have done well after the switch, and our personal relationship was never jeopardized, although you should ask them if they feel the same way – I think they do).

The Where and When of Working

One of the biggest challenges in your PhD is time management. I will help you set long-term and short-term goals, but will never directly manage your time or your tasks. As a result, you will be the prime owner of your time and schedule – for better or worse!

I highly recommend that you structure your time in some way that works for you. For example, I believe that it will be helpful to you to work on research everyday: structures and routines can help you accomplish that, rather than frenzied effort right before deadlines.

Eric’s syllabus has some helpful tips for managing your time and schedule. At a high level, you should have a set of daily tasks, but also some higher level (weeks, month, semester, year) goals. I will help you set those, typically going to larger and larger time frames as your PhD advances. For time and task management, use whatever tool works for you: notebooks, task manager apps, text files, … but make sure to use something.

Work location

Cornell Tech has an open space layout where my students and I sit next to each other. You will have an assigned desk in that space. I spend most of my time in that space, or in my meeting huddle (a few steps away), or in other meetings. I expect most students to be working from that space regularly, which is not to say “most of the time” but perhaps a substantial portion of the working hours each week in that space. Most of the students come in at least 3 days a week. Frankly, if work and progress gets done I don’t mind where you are. But I find that progress and problem solving are more likely when you are surrounded by others (including me) who can help solve problems, answer questions, and point you in a helpful direction. This is in addition to providing an environment that helps you focus on work. It’s often the case that students vary their physical presence, e.g. when they have a writing task that requires focus not offered in a more busy environment. That’s totally acceptable, but you are expected to let the team (me, your collaborators) know when they should expect you.

Oh and if you find it hard to concentrate in the open space, we are happy to sponsor noise-cancelling headphones.

Ithaca and/or New York

The Cornell IS and CS PhD programs (as the other PhD programs represented at Cornell Tech) are split across New York and Ithaca. Some departments require PhD students to spend some time in Ithaca, while others are flexible. The general guideline is for PhD students to generally be on the same campus as their main advisor.

I think it’s a great idea for every student to spend some time in Ithaca, ideally their first semester or even first full academic year (two semesters) if possible. This is not a requirement, and if you are joining the program with me assigned as your initial advisor we will discuss this and come to a decision together. I have had students that spent their entire time in New York, and others who spent a semester or year in Ithaca. Some key reasons to start in Ithaca are: (1) getting to know your departmental PhD cohort, who will be your discipline-based network for years to come; (2) getting to know other faculty in the department and beyond; and having them know you: they will be potential committee members, letter writings, or just sources of advice and knowledge for your time in the program; (3) taking required classes in person (though they are often available remotely, and sometimes even offered from the Tech campus); (4) taking additional classes in Ithaca, where there is a broader set of courses offered that can provide a great foundation for your PhD; (5) getting a sense of the spirit and offerings of the Cornell “mothership”.

In New York, you will have a different PhD cohort (Cornell-Tech-based students from all the academic departments represented here) and faculty to interact with (similarly, across all departments). Their time will come when you come to New York in your second semester or year.

Other Places

Later in their PhD, some of my students spend a semester or more “somewhere else”, which could be in Ithaca but could also in absentia from Cornell (for example, students recently had spent time at MIT and Stanford). I recommend trying to do this for multiple reasons: you can get to deeply know and collaborate with faculty and PhD students from other departments, and have them know you; be exposed to different and new ideas, as well as spread your own ideas to them. You will collaborate with me remotely during that time, although perhaps not as closely as you would if you are here. This kind of visit is not trivial to execute. It requires a host – often a long-standing collaborator or a strong academic contact, appropriate and flexible funding, and logistical considerations (e.g. leaving that great apartment you found in New York). As a result, I cannot promise this will happen for you, but am happy to explore.

The When of Not Working

You do not need to work all the time to be a successful researcher. In fact, I think the current evidence suggests (and I strongly believe) that working all the time is counterproductive. Nevertheless, you may encounter a culture in academia of always-working; I recommend that you resist this.

The hardest thing about academic time off is ownership. When you are off, it is your research that does not advance. This is hard to contend with. But what is often left out is (a) that you are more productive and motivated in your working time when you have a good balance with your time off (b) that time off is critical for new insights, ideas, and reflections that are not otherwise available.

I recommend thinking about your PhD as work, with a work schedule (hopefully a “normal” one, i.e. weekdays) and time off work, even if you have to force yourself to do so. Please take care of yourself, in whatever way you need to that is meaningful to you, on a daily basis. For example, I will often take long multiple-weeks (or more) vacations, especially over the semester breaks.


There are specific guidelines provided by Cornell, but Ph.D. students in my group should feel free to spend up to 6 weeks (6x5=30 working days) every year on various holiday breaks and vacations. I strongly encourage that you take a total of at least 4-5 weeks (20-25 weekdays) off, which is roughly aligned with the official policy. If I could insist that you take at least 4 weeks, I would; if you need more than 6 weeks, well, frankly nobody is really counting but you still need to make progress. Vacation should mean vacation: no work email (or just monitoring for urgent needs), no working on papers, no analyzing data. Note that conference travel does not (and should not) count as vacation. You can also take leave, for example during summer if you are not funded (see note on internships below). I took the second summer of my PhD off to travel the world for three months.

What works best for vacation is scheduling time off well in advance. “Taking off next week” is never easy – you will have obligations, meetings, tasks. Planning a vacation six months away is easier, and you can plan around it as the time approaches (to make sure you have no meetings or pressing deadlines, for example).

Any ad-hoc days off you want to take are usually not a problem. Especially after big deadlines, I highly recommend taking a few days off to rest, reflect, and re-energize. When you want to take a longer break like a vacation, it can be helpful to give me a few weeks notice, but I’m usually flexible. The most important thing is to communicate your availability in advance. Things outside of work also come up related to health, family, emergencies, etc. Those often require work breaks, and at the very least, different work arrangements. You can let me know if that comes up for you.

Your breaks are not necessarily tied to the academic calendar, nor does “academic break” automatically mean you should treat this time as time off your work and research. It is useful to take time off during academic breaks (often that’s when I will be gone) and official university holidays. During my PhD I often traveled just past Christmas and until just before the semester started, mostly to save on airline costs. Of course, if you are taking courses or serving as a TA you should expect to need to be available during the semester.

Working with Me

The advisor-advisee relationship represents a significant responsibility and commitment on both our parts. I try to hold myself to high standards with students, but I also have high expectations from students who work with me. In general, we should all be responsive, respectful, honest, timely, and hard-working. When those things aren’t happening, we should talk to figure out how we can get there. Note that the failure –or perceived failure– could be due to my actions as well. I recognize that this is one of the most important and consequential relationships you will have; while I hope it would be at least as meaningful for me, it is less likely to be as consequential. As a result, I encourage you to let me know if something is not working.

Importantly, I am your advisor; I am not your manager, not your supervisor, not even your teacher. I am not here to “boss you around” or to tell you what to do when, but I do provide suggestions, recommendations, and sometimes even decisions (“this paper is not good enough to submit for this deadline”), and I do expect to see various outcomes (and progress) but I try to stay away from prescribing the details. Instead I help you set your own plans and goals and the best way to reach them. Of course, the power dynamics are somewhat tilted in my “favor” and I recognize that: I often fund your work; I sign your thesis; I report to the department on your progress. Still, I welcome pushback from PhD students (e.g. “I can’t attend to this data analysis this week”, “I don’t think we should run this experiment”), as well as healthy feedback and disagreement.

I also am not likely to directly teach you many of the specific skills you would need for your research tasks. I will not teach you R (or any other language for that matter). I will not teach you how to run logistic regression, or develop a deep learning model, launch a Mechanical Turk task, or do thematic analysis of interview text. I will help you get all these skills, though, sometimes by pointing you to the right resources (e.g. courses, papers, tutorials, or knowledgeable others), and sometimes by doing them with you.

Power Structures

Of course, the university (like most of society) has strong hierarchical structures. Professors are in positions of power over students and students are unfortunately not always able to speak up when something isn’t right. I welcome student input, especially if I or one of my colleagues has said or done something that makes a student feel uncomfortable. I do realize that it is a difficult proposition in many cases, especially if you feel I am the culprit. If you feel you suffered harassment, intolerance, or other injustices I encourage you to speak to me or other trusted individuals.


I welcome students from a wide range of backgrounds and experiences to work with me. I believe diversity of experiences, backgrounds, views, countries of origin, abilities, and opinions makes all of our work better. To use one (important) dimension, a majority of my past and present PhD students identify as women. While women are quite well represented in Information Science (less so in Computer Science), I recognize that the experiences that they have in academia and life are different than mine. I hope that our environment has been welcoming for them (you should certainly contact them to find out!) and encourage you to let me (or others) know if there is anything in our lab or campus environment that makes you in any way uncomfortable.


I am a big fan of co-advising PhD students, and some of my students have been co-advised. As long as the “trio” dynamics are healthy, including the relationship between the two advisors, this is a good idea: gives you another smart person to advise you and be invested in your future; broadens the set of ideas and knowledge you are exposed to. There are potential drawbacks – some overhead for you (scheduling, more weekly and lab meetings), potential friction when advisors disagree. But overall, if there are two faculty members whose work, vision, and interests align with yours, you should definitely explore co-advising.

Time with Me and Others

I try to make myself available to my PhD students as my first priority in terms of both calendar and attention. Having said that, there are sometimes other requirements on my time, often immutable and sometimes urgent. You should expect to be able to see me often or get fairly rapid responses, but do not expect to see me or be able to get my time and attention “on demand”. You are always welcome to try though! Often this would just mean turning your chair (or head) as I will be working at my desk right next to yours (OK I realize this might also present some challenges…).

Most importantly, we will have a 45-60 minutes long weekly one-on-one meeting slot in which we will talk about your work and progress, brainstorm ideas, and generally touch on any matter you want to discuss. You can also ask for my time at any other point, e.g. for a quick ad-hoc meeting, which I will be happy to do whenever possible.

Beyond the 1-1 meeting, you will be asked to attend the weekly lab meeting where students share progress as well as other updates (e.g. conference reports, cool papers etc; the format of these meetings is always in flux).

You may also see me in project-specific meetings (frequency depends on the project) where we are working with other collaborators.

How to find me

If I’m not there in person at work, you can try to find me in multiple ways. First, Slack. In particular, our lab’s Slack team is the best way to find me. I have alerts setup for this Slack (and only this Slack) on my phone, too, in case you need a quick response for a question or request (with the caveats above). I am also of course available by email. However, email is not a synchronous medium, and I often turn it off in order to get stuff done, and stuff tends to get lost there due to volume. Always expect that I may not respond for 24-48 hours to any email you send during normal times; it will take longer when I’m traveling.

If you need me to meet with you at a certain time, it’s best to contact me about it first, then when I’ve agreed to the time, send me a calendar invitation (this is true for everyone else you’d like to have a meeting with in professional settings!)

If you want me to be responsive to you, you should be responsive to me. However, I will not expect you to be responsive during non-working hours (unless we agreed to be working on a deadline). The sections above have other “time off” considerations.

When to Expect Being Able to Get My Attention

Typically, I am in the office most weekdays during standard hours (9ish-5ish). This is my rough schedule:

11:30pm: sleep 7:30am: wake up 7:30am-8:45am: help get kids ready for day 9am-5pm: in office for meetings, working, writing, etc. 5:30pm-9pm: family, dinner, home-related activities (i.e. little attention to any incoming requests) 9pm-11pm: Netflix, guitar, non-academic reading and watching activities, might pay attention to requests or do deadline/urgent work

On Ending the Advisor Relationship

It is not uncommon for the PhD to run into problems. When things don’t work, one option already mentioned above is switching advisors. Our relationship is “at will”, for both of us, and changes could happen when interests diverge but also for other reasons, for example when there are workstyle or expectation mismatches, or personal issues, or other issues and constraints (e.g. physical location). If anything like that happens, we can try to address the issues, or just let it go. Note that you can decide to switch advisors without requiring my approval, and that you will commonly need to find a new advisor who will be willing to take you on.

Another option is leaving the PhD altogether. I know some very, very smart and capable individuals, including my own former advisees, who had left the PhD program. This happens, and is also an acceptable and not entirely uncommon outcome. If anything, students who are truly unhappy, or discover that they don’t enjoy their PhD work, or are struggling to make progress, are sometimes better off deciding to leave the program. As I note below (see “challenges” section), the PhD process often brings periods of uncertainty and anxiety, as well as relentless feedback, some of it negative like paper rejections. While many people are able to overcome these challenges, others may not – again, this is perfectly understandable. Based on your program requirements, you can often leave with a Masters degree, making your time investment worthwhile, at least to some degree (no pun intended).

Writing papers

There are many forms of scholarly impact. Writing papers is one of them—and among the most important for graduate students. Though other forms of impact are very important, such as making important systems or helping to inform policy, the importance of such forms often relies on a base of academic writing.

Eric Gilbert’s PhD syllabus has some additional recommendations about paper writing. In particular, Eric recommends finding exemplary papers from the target venue to use as referral and inspiration. Indeed, while you can and will work with me directly on papers (as I expand on below), my time will always be limited; and there is no substitute for interactively thinking about your writing in comparison with other similar scholarship.

Process: writing alone, better together

Part of your development as a scholar is being able to plan, outline, and write an academic paper. I will be your co-author and collaborator for most of the papers you’d write. As an advisor, I will help train you to write academic papers during this co-authorship.

Commonly, we will plan the paper together, thinking about its contributions, how to present then, the intended structure of the paper, how to present the results and arguments. The writing usually comes after lots of direct consultation with me about these issues over the preceding days, weeks and months. I typically ask my PhD students to write the first draft of each section in the paper independently. It may seem like the reason I do this is because it’s less work for me; it’s not. In fact, early in the PhD program, I think it’s more. For example, often with first-year or second-year papers, I’ll be frank: I could write a better paper in less time than I spend advising and working with the student on the paper. If I was solely aiming to optimize for publications, it would make sense to cut the student out of it at the point of drafting the first document. However, going back to my perspective on the PhD, teaching students how to be excellent writers is essential to their success as scholars. These experiences struggling (and ultimately succeeding!) with writing are important educational experiences.

For a 1st or 2nd year student, that writing process might be the student delivering an individual section for in-depth feedback from me, followed by rewrites by the students, ultimately followed by extensive editing and rewriting by me. For a 5th or 6th year student, students (after discussing their thoughts on its direction and narrative) are likely to go off and write a near-perfect paper on their own, followed by collaborative editing and rewriting.

There are resources with specific tips and tricks for paper writing, for example from Jeremy and others. In fact, if you are reading this and are my student, make sure to ask me for my private “how to write” document, which is a multi-year iteration on Jennifer Widom’s CS-systems-oriented notes which I picked up during my own PhD (one day, sigh, I will share my document here as well).

It is OK to use ChatGPT or similar AI technologies to assist in various ways in the writing process, but you should tell me that you are doing it so I can give you the right level of feedback. In general, remember this: (1) the output of whatever writing process is your responsibility, regardless of whether AI helped or not. You should be able to justify every single word, sentence or argument, 100%, no excuses, at any time; (2) especially in your first years, I highly recommend writing and structuring text yourself to have a better appreciation of what makes good writing; (3) when you do use AI, you should think about what you want to write and give the AI a template or draft text to improve upon. Of course, you should always follow the submission venue’s policies regarding use of AI and disclosure.

Paper Deadlines

Since papers are your main product, deadlines involving paper submissions might be the most stressful times of your PhD experience. We often submit to highly peer-reviewed venues like CSCW, CHI, and ICWSM. For these venues, deadlines are every 3-4 months, although there’s often a “major” annual deadline for each of them, the last chance to submit a paper that would go into that year’s conference. I will do whatever I can to help you set appropriate deadlines and meet these deadlines – in terms of planning and in terms of writing. I highly recommend planning submissions in a way that does not offset or suspend other life goals or practices like sleep.

With advance planning, I am willing to work extra hours before a deadline, recognizing that they are important to advance your career. You don’t have to do that (see notes above on taking time off). However, students can only expect me to work extra hours on a paper deadline if they are also committed to doing so; and should not expect me to work over time to give them feedback unless they verified in advance that I am available and willing to do so (no “hey I just finished the first draft of the paper that’s due tomorrow can you read it tonight”). I generally believe that work at night is more counter-productive than it is useful.

I have an informal “-7 days” internal deadline for submissions. This guideline states that a paper intended for submission needs to be in submittable (but not perfect) state 7 days before the deadline. The paper doesn’t have to be perfect: the bar I use is that all the sections, results should be there: the studies have to be completed, the data analyzed, the findings solidified, the message of the paper needs to exist, etc. This allows me to really understand what we have, where we’re at, and where we need to go in the next 7 days. The paper would often undergo significant changes in that last week, and we may end up working on it extensively as the final deadline approaches, but the -7 days practices should make the deadline more manageable, and the final product (the paper) stronger.


As is common in our field, I am very likely to be a co-author on the papers we work on, which generally means most if not all the papers you lead. Further, papers (and projects) often involve other collaborators, including faculty, PhD students, MS/undergraduate students and others. I tend to be inclusive in whom to list as co-authors, often being a bit more permissive than some existing guidelines.

Authorship order will become important, and the default expectation is that you will be listed as first author for your “PhD papers”. However, there are often other considerations for authorship order and first-author choice (e.g. an undergraduate who contributed significantly; a PhD student you collaborated with equally) where you may end up not being a first author even for work that contributes to your PhD. This is not a problem.

You are welcome to write papers without me, and likely to do so e.g. during internships. However, when work is done at the lab, as part of –or adjacent to– your PhD, I expect to be collaborating on the work and on the paper writing. If that doesn’t happen, we probably have other issues to work out!

Conference and Other Presentations

With many of our papers submitted to highly peer-reviewed conferences, you can expect to be able to present your research in conferences (and similar settings), often to dozens if not hundreds of people. Later in your PhD you are also likely to have other presentations of your research work, including seminars and eventually job talks. I will help you prepare for these talks, taking an iterative process that follows in many ways the paper-writing process outlined above: planning/outlining, drafts, iterations. Expect more of this feedback and iteration earlier in your PhD; it is not uncommon for students to give 3-5 practice versions of the talk before their public presentation, at least in their early years. Job talks often take 10 or more iterations to “nail”.

Relatedly, I am also likely to present you research in invited talks, lectures and seminars. I will of course give you prominent credit when I do so.

Travel to Conferences and other Events

I will cover expenses related to travel for the lead author of papers we submitted together to a conference. I will likely ask you to submit a request a travel grant from Cornell to cover some of the expenses. I will likely not be able to broadly fund travel to other events including stand-alone workshops, talks, conferences where you do not have a paper, etc. There are exceptions so if you are interested in traveling to such events, ask me about it before making plans (or submitting).

When you do travel, I will ask you to keep expenses to a reasonable level for flights, hotel, meals, etc. (rough guideline: whatever you would have spent yourself if you could afford it and were paying for it). Of course, you should be comfortable and safe during the trip so do not choose, for example, a dangerous neighborhood or unofficial taxi just to save money. You should share hotel rooms whenever possible and reasonable to do so. Instead of meal receipts, you should keep track of your food expenses and ask for an equivalent per-diem to cover them. 

Non-Research Work

Expect to have quite a lot going on in your work besides research.

Taking Classes

I share Eric’s view on classes: they are very much secondary to your research. Many students, having excelled in classes their entire academic lives, have trouble letting go of excelling in classes; it’s perfectly ok to do so. Your class performance is not critical for your PhD success or outcome. Well, of course the required classes are important for that, but you know what I mean. It’s important not to lose sight of this during the program, especially as the (relatively) easily-satisfiable interim deliverables of classes stack up next to the (relatively) harder-to-satisfy expectations of research.

Classes are useful to expose you to broad areas of scholarship or methods that you might not have been aware of before, and that could be informative for your own work and research. They are useful ways to meet (and impress) other faculty, and consequently to build bridges to the (myriad) committees you will need to form in your time as a PhD student. However, they should come second to your research, your data, your questions.

To summarize, the PhD program is all about learning new things, but as your research problems lead you there. You will spend lots of time learning new skills, techniques, and theories—most likely on your own. You might seek out a class to help you master something you know you need in research. But let the research drive that exploration and those decisions.

I usually take on 4-5 students at a time, and they are often scattered through various stages of their PhD (i.e. 0-2 students a year). The core members of the lab are these students, and other members are MS students, undergraduates, and interns working with us as well as others. We have a weekly lab meeting, as noted above.

There’s often work associated with sustaining a research lab and its culture, and I believe all members of the lab (i.e. my PhD students) should be contributing to this work. For example, such work may include designing, building or updating a lab website; organizing the schedule for the lab’s weekly meeting; or organizing social activities for the lab.

As noted above, in your first year you may be working with a more senior lab PhD student on a project. Accordingly, when you are in your advanced years, you will be expected to be able to mentor and help an incoming student with their first project steps.

Non-research Work

Beyond research activities, you should expect to spend time on various other tasks in a sustained or intermittent manner. These activities should be considered part of your academic work, and fit into your work week. Such tasks may include: reviewing papers (often referred by me); participating in review committees (later years); applying for internships and fellowships; reading papers and books; participating in conferences, workshop, retreats, and other academic events; volunteering in or help organize (later years) conference, workshops, seminars and other events; work to support the academic community goals such as broadening participation; attending seminars; doing classwork; doing TA work (when relevant); doing non-PhD-related GRA work (rare, as noted above); doing student committee work (e.g. “PhD social committee”) and department committee work (usually voluntary, e.g. member of the faculty search committee); outreach work (e.g. report or op-ed based on your research); advising others (e.g. Masters/Undergraduates/interns working on your projects); writing professional email.

Challenges and Mental Health Resources

The PhD experience can be very challenging—and in unexpected ways. It is common to experience mental health challenges during grad school. While I’m not personally trained to help directly, I hope to be supportive in whatever ways my advisees feel will be helpful, including of course helping them avoid such issues wherever I can. I have met very few individuals that have not struggled with anxiety and other mental issues during their PhD. There are many reasons for that, in my opinion, mostly due to the combination of uncertainty, self-responsibility, and relentless feedback one receives as a PhD student. It is possible that you will experience some anxiety during your PhD, most likely during your 2-3rd year where your self-expectations are high, and feedback in the form of recognized success or established dissertation direction are still often somewhat elusive. This feeling is common, and many PhD students will experience it at some point or another. Don’t be alarmed; come to talk to me (or others) if you feel that way.

The environment in academia, including at Cornell and Cornell Tech, will not stop you from overworking at the cost of your well-being. Quite the opposite, you will often feel like academic work culture encourages working evenings and weekends, and many do (I sometimes do). In our group, we actually care about your health and well-being and when we say take care of yourself, we mean it. Overworking is neither healthy nor productive in the long run as a PhD is a marathon, not a sprint. When you feel uneasy, don’t run faster, but keep good company. After all, the point of a PhD program is that you don’t need to run it all alone.

If you or someone you know is feeling overwhelmed, depressed, and/or in need of support, services are available at Cornell and Cornell Tech to support you. These services range from a student services team member available to discuss your challenges, to professional outside services offered through your student health insurance. You can find more details on the Cornell Tech and Cornell websites.


I strongly encourage my students to take internships, though not necessarily every year. There are three main reasons to do internships . First, they pay well; grad school does not. Second, they can advance your research by giving you skills, access, or points of view that you would otherwise not have in your research. Third, it would be useful for you to know what industry looks like. At some point you will find yourself choosing between academia and industry; without having had a few internships, it’s hard to really know what industry is like.

You could do an internship any given summer, and I am flexible with students about when and where they take them. You and I will discuss whether it’s a good idea for you to seek an internship as each summer approaches, and what kind of internships you may want to seek (or accept). For example, you are more likely to get research internship offers after your 3rd or 4th year, those are usually recommended though the alignment to your own research and your progress will also play a role. You are more likely to get “practical” (engineering, user research) internships after your 1st or 2nd year. Those are less useful for your PhD (though they will still get you that good money!) and I would sometimes recommend that you spend the summer advancing your research instead.

I usually have research assistantship support for students who are interested in sticking around for the summer. In fact, I don’t remember a single case when a student wanted to stay for summer and could not be supported.

Students in our area often look for internships at: MSR, Microsoft, Google, Facebook, Twitter, Airbnb, Reddit, Twitch, Instagram, etc. Emerging startups can also be exciting opportunities; they generally require more work to seek out, and you will probably have a more varied role when you get there. Within these companies, there are a wide spectrum of intern roles—from pure research to pure development. You will likely prefer the former over the latter (the former can lead to papers; though that is often not incentivized within companies). While it varies by place, students tend to line up internships as early as October before the summer they intern, though that process can and does go into March. Again, it varies by company and stage in the program. If there is a certain place you’d like to intern, ask me: I may know someone there and can make an introduction.

Since the work in the lab is highly multidisciplinary, your intern positions may also vary based on your expertise, from technical work with algorithms to user research with actual individuals. It’s all good.

During your internship, I will mostly leave you alone. I want you to experience industry, and it’s hard to do with me hanging around. Also, don’t feel like you need to bring me on to a project with you. I will sometimes join an intern project in an advisory capacity if all interests align (you, me, and the company’s). However, it is not uncommon for you to have some work lingering from your PhD that needs to be done during your internship: for example, a paper with a revise-and-resubmit deadline, or data collection that cannot be stopped.


Where could you expect to end up after your PhD? Well, the sample so far is not very large so it is hard to generalize and predict. Students I have advised have ended up in both academia and industry positions. Some typical targets are academic positions (often after a post-doc appointment), industry research, data scientist roles, software/ML engineering, and user experience research roles.

At some point in your PhD, typically after 3-4 years though sometimes earlier (and sometimes later), we will have a better idea of which careers you may desire and which may be attainable. When that happens, we will work together to align your work, output, and activities to maximize the likelihood of the desired outcome.