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,
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
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
Some frequently asked questions, already answered for your
convenience, 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
Note that having co-authored a paper appearing at NeurIPS/ICML/etc.
is not necessary nor sufficient.
I get a lot of emails about admissions,
and unfortunately, I cannot write a personal reply to each
Q: Do you have any internship positions available?
I do not have internship positions
available (virtual or in-person).
Q: Do you have any open postdoc positions?
I do not have any open postdoc
positions. 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 cannot commit
to hosting external students or visitors whom I’ve never met or worked
Q: What is your advising style? What is it like to be your
I don’t have a fixed advising style; I’ve found that no one mode of
advising works for all students. My website has a list of my current
(and past) Ph.D. students. 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
First, 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
Comfort in 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
Q: What are good books to read about machine learning and/or
Q: I am currently a Columbia undergraduate/MS student; will
you supervise my independent research project or thesis?
Due to time constraints, I can only commit to 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) and
the instructor 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.
Q: Do you have any open research assistant positions
available in your lab?
No, I don’t even have a “lab”.
(These are not frequent answers to questions, but rather just links
to useful “advice” that others have written.)