Advising and Admissions

Current NYU Students

If you're working on a PhD and are interested in collaborating or seeking an advisor, contact me. If you're working on an undergraduate or master's degree, I will only agree to a research collaboration if you've already taken some coursework in computational linguistics or NLP and done very well. If that's you, send me an email with a CV, a transcript, and a very short note about your plans and research interests.

If your goal is to get started with independent research in NLP, I strongly encourage you to take DS-GA 1012 as soon as you can, and ideally before you reach out to me for one-on-one research supervision. I designed that class to walk you through your first major research project, and both the prerequisites and the non-project-related assignments are relatively light.

I'm generally only able to offer funded RA positions to PhD students. When funding for other students becomes available I'll generally offer it to students I've already worked with.

Prospective Graduate Students

I can advise graduate students in the Department of Linguistics (PhD), the Center for Data Science (MS, PhD), and the Department of Computer Science at Courant (MS, PhD). If you're interested, you're welcome to contact me, though get too many inquiries to be able to read and reply to them reliably. As above, if you're applying for an MS, I won't commit to supervising you as a research student until after you've taken coursework in NLP at NYU. I will likely be able to recruit a new PhD student to start in 2019.

In the interest of fairness (and my sanity), I don't hold interviews or admissions-related meetings with prospective students until after we have received and reviewed everyone's applications. I never hold interviews with MS or undergraduate applicants.

At the PhD level, the Linguistics program offers students a full five-year fellowship, while funding for CS and Data Science students, though guaranteed, often comes through grants for research on specific areas, which flow through advisors. This leads to somewhat different expectations for admission. Linguistics will admit students without a close fit to an advisor, so it's important that the applicant already be quite independent and have a good fit to the department overall. In CS and Data Science, fit to the department is less important, but it's crucial for applicants to name specific potential advisors and to demonstrate (i.e., through reference letters and published/publishable written work) that they're ready to work on problems that those advisors are likely to be interested in (and able to write grants for). Admission rates for all three programs are similar (and low), so you should apply to whichever best fits your record and your interests. For students broadly interested in cognitive science, this page offers some useful information about the available programs at NYU.

Prospective Postdocs and Visitors

I don't currently have funding for new postdocs, though this could change soon. If you're looking for a position at NYU and have a specific research direction in mind, let me know and I may be able to help you apply for outside funding or University funding.

I can't offer full funding for internships or other visiting positions, though I may be able to host and help support visitors who have already secured outside funding, at least when there is a clear fit. I can host undergraduate visitors, but only if they have research records and references comparable to those of early-year PhD students at strong US departments.


Variational Autoencoders

My paper on this topic with Luke Vilnis was done during a Google internship, and we were not able to take any code or data with us at the end of the internship. If you need help applying VAE language models in new areas, my coauthor Luke has some notes that we are allowed to share, but your best bet is to look at any of the many good papers on the topic that have come out since ours.