This page is intended to provide some context to potential PhD students on what I am interested in. If you believe we may be a good fit, I encourage you to apply to OSU (and include my name as a potential advisor in the application).
My primary field of research lies broadly in the intersection of natural language + AI. Within this space, I am primarily interested in developing and studying human-centered language technologies, that is NLP models/language models and systems centered around human needs and preferences rather than solely focused on capabilities. Please check out my recent publications to learn more.
If you are interested in joining my lab:
If you are at/accepted to OSU CSE Ph.D. program: Please feel free to reach out via email!
If you are applying to the Ph.D. program: I will hire Ph.D. students through the OSE CSE PhD program -- please refer to the department's admission page for details. Select me as a potential advisor on your application form and mention my name in the final paragraph of your Statement of Purpose. I will read all applications that mention my name.
If you are an already accepted MS or undergraduate student at OSU, please feel free to reach out via email. I expect you to have completed courses like linear algebra (Math 2568), AI (CSE 3521), and/or some more advanced courses (CSE 5523/5524/5525/5526) or be familiar with the concepts from these courses.
Culture, Values, and Expectations
I do not expect incoming students to have extensive experience in ML/NLP, but students should be comfortable writing python code and familiar with libraries such as PyTorch and Huggingface Transformers.
I will strive to maintain a lab that values inclusiveness and is a safe environment for all members. As a new professor, I expect to work closely with students, including regular meetings (e.g. weekly or twice a week) and active involvement in projects, such as helping with paper writing. Students who are looking for close collaboration are a good fit. While I do expect frequent communication, I have no intention of tracking students' work hours or vacation time, and students will be encouraged to set schedules that best support their mental health and productivity.