Thank you for your interest in joining our lab!
Here is general information on current opportunities.
How to apply
[fall2026]”.Note: Due to the overwhelming number of emails, while I’ll read them, I probably won’t be able to respond.
Prospective master’s students
Yale CS offers a highly competitive two-year funded Master’s program that is designed for students considering a PhD in future and looking to gain substantial research experience.
If you are interested in this program and want to work in NLP/LLM-related areas, I encourage you to reach out.
Please include [2yr-ms] in the subject line of your email.
The two-year Master’s program is funded, research-focused and can be a strong pathway into a PhD.
Program details: Yale Masters Graduate Program.
If you are already admitted to a Yale graduate program and would like to explore research opportunities with my group, feel free to email me.
Master’s students enrolled at Yale
Generally, we welcome motivated master’s students who plan to apply to PhD programs, including students enrolled in the two-year master’s program.
Please feel free to contact me.
We welcome motivated Yale undergraduates who are interested in a longer-term research commitment to join our lab.
Students with strong programming skills and prior experience in AI/ML/NLP are especially encouraged to reach out.
We have limited capacity for hosting visiting students, interns, or short-term research visitors.
We generally only consider visits when there is a strong match to ongoing work or a well-defined collaboration plan.
I’m always interested in hearing from outstanding postdoctoral candidates.
While I do not currently have dedicated funding for postdoctoral positions, I encourage applicants to reach out if they are interested in applying for external fellowships or funding opportunities. If there is a strong match, I am happy to discuss potential projects and support fellowship applications. Please include [postdoc] in the subject line of your email.
Yale is an excellent place to do frontier research in NLP and large language models.
We develop and study LLM-based systems that are scientifically grounded and reliable, while pushing on fundamental questions in learning, reasoning, evaluation, interpretability, and safety.
Students in our lab have substantial ownership over their research direction, with strong mentorship, a collaborative research community, and opportunities to work with industry and interdisciplinary partners.