Hello people! This page contains some answers to questions that I find myself frequently providing. I record these answers here in case they are pertinent to a question you have. If you have other questions, feel free to email me.
Coming to Columbia as a student, postdoc, visitor, researcher, etc.
Q: I am interested in applying to a computer science degree program at Columbia. Should I do so and what are my chances of getting in?
Please see the CS department’s admissions webpage. There, you’ll find information about all aspects of the application process (e.g., deadlines, your chances of being admitted), as well as information about the academic programs themselves.
Some frequently asked questions (along with some answers), can be found by clicking the following links:
Ph.D. applicants: Please mention my name in your application if you are interested in my research. This is a good way to draw my (and others’) attention to your application. (There should be a box you can check or something like that …)
In general, my Ph.D. students tend to (1) be interested in working theoretical aspects of algorithmic statistics and machine learning, (2) have taken some advanced undergraduate courses in math, statistics, and/or theoretical computer science, and (3) have some research experience that is discussed by a mentor/advisor in a recommendation letter.
Note that having co-authored a paper appearing at NeurIPS/ICML/etc. is not necessary nor sufficient.
Although it is technically possible to apply to start the Ph.D. in a spring semester (with a different application deadline than for starting in the fall semester), I do not look at or accept any such applications.
I get a lot of emails about admissions, and unfortunately, I cannot write a personal reply to each one.
Q: Do you have any internship positions available?
I do not have internship positions available (virtual or in-person). I’ll update this page if this changes.
Q: Do you have any open postdoc positions?
I do not have any postdoc positions available. I’ll update this page if this changes.
Q: Can I do a research visit with you for n months? My company/government/self will cover all of my expenses; I will not require a stipend.
Due to time constraints, I do not host external students or visitors whom I’ve never met or worked with.
Q: What is your advising style? What is it like to be your Ph.D. student?
I’ve found that no one mode of advising works for all students, and therefore I do not have a fixed advising style. My website has a list of my current (and past) Ph.D. students, and you are welcome to contact them and find out about the range of advising styles that I have employed.
Getting started in machine learning
Q: I am interested in taking a course in and/or doing research in machine learning. What courses should I take in preparation?
It’s great that you are interested in these subjects! Machine learning is a confluence of ideas from many disciplines, including computer science, optimization, physics, and statistics. Because of this, it is a very broad subject that builds on a number of foundations. When getting started in machine learning, it may feel overwhelming—it did for me. At the same time, I hope it also means that there’ll be something particular that’ll “click” with you and that you’ll want to study in depth.
A good way to get started is to build up solid mathematical foundations in
linear algebra,
probability, and
multivariable calculus.
Being comfortable writing code to process and analyze data (e.g., in Python) is also very helpful.
These courses are “proof-based”, in the sense that the course is largely driven by formal definitions of and mathematical theorems about learning problems and algorithms. The proofs and the intuitions behind these theorems help solidify our understanding of the phenomenon that we call learning.
Q: What are good books to read about machine learning and/or learning theory?
Q: I am currently a Columbia undergraduate/MS student; will you supervise my independent research project or thesis?
Due to time constraints, I only consider supervising project/thesis students who have done well in a class I’ve taught, or who have done well in a relevant class (e.g., in learning theory) taught by an instructor who can send a strong letter of reference (an informal email is enough). Depending on your interests, I may recommend some courses that I think are useful to take before diving in, or other faculty members who may be a better fit.
Q: Do you have any open research assistant positions available in your lab?
I do not have any open research assistant positions available. I’ll update this page if this changes.
Advice
(These are not frequent answers to questions, but rather just links to useful “advice” that others have written.)