Prospective Students
If you are not a student at Stony Brook University, and want to join Banerjee's research group as a research assistant, please note that (a) direct application for any position in the research group is not currently possible for candidates outside Stony Brook University, and (b) temporary or short-term research positions cannot be accommodated.
It may not be possible for Banerjee to respond to individual emails or queries regarding available positions. If you are interested in joining his research group as part of your M.S. or Ph.D., please apply to one of the following graduate programs offered at Stony Brook University: M.S. in Computer Science, Ph.D. in Computer Science, or M.S. or Ph.D. in Data Science.
Students at Stony Brook University
Ph.D. (Computer Science or Data Science)
If you are a current Ph.D. student in the Department of Computer Science, have a strong background in mathematics (and/or statistics) and programming (mainly in Python, and particularly in the use of modern machine learning libraries like PyTorch, TensorFlow, or Keras), feel free to contact Banerjee via email about potential opportunities within his research group. Ph.D. students are expected to have the ability to formulate a research problem that they want to pursue. Please be prepared to start your journey by presenting a convincing proposal for your research.
M.S. (Computer Science or Data Science)
If you are a current M.S. student, you must have already demonstrated interest in an ongoing research project with tangible contributions (usually by taking independent study, CSE 593). This is the most important indicator of your genuine interest. Fall 2025 onward, Banerjee's research group will no longer consider applicants for an advanced graduate project (CSE 523/524) or graduate thesis (CSE 599) in any other way. If you are interested, please keep the following in mind:
A successful applicant will typically have good grades, a strong programming background in Python with knowledge of version control, and a good understanding of machine learning fundamentals. Experience with libraries like PyTorch, TensorFlow, or Keras is a strong plus.
As prerequisites, the graduate machine learning and/or natural language processing courses are strongly recommended. This is an important indicator of your area of interest. If contacted, please be prepared for an initial technical interview on NLP and/or ML concepts. If your interview is satisfactory, you will be put into a specific project team, usually with a Ph.D. student leading the project. Banerjee and his team are dedicated to their research, and applications are expected to
invest approximately 10-12 hours of diligent work on a weekly basis;
participate in one weekly research group meeting for progress assessment and discussion/presentation of research papers and ideas; and
participate in at least one weekly internal meeting with your project team, which are usually chaired by the lead Ph.D. student (specifics will be dictated by the project requirements).
At the end of the project/thesis, your work is expected to be of a caliber that is publishable at a peer-reviewed research conference or journal. If you have made significant contribution, you will be a co-author in the published work (subject to acceptance at a reputable venue).
If these expectations instill excitement in you, please apply here for a position at the Social & Computational Research (SCIRE) group.
B.S. (Computer Science, Mathematics, or Linguistics)
Research opportunities for undergraduate students exist in the form of CSE 487, or CSE/HON/WSE 495/496. Outstanding performance in coursework relevant to machine learning is a prerequisite (ideally, in CSE 353 and/or CSE 354). At the end of the project/thesis, the goal is that your work should be deemed publishable at a peer-reviewed research conference or workshop. If you have made significant contribution, you will be a co-author in the published work (subject to acceptance at a reputable venue).
If you are a current undergraduate student of computer science or an area closely related to natural language processing, and the thought of venturing into intellectually unknown territory excites you, reach out by filling this form.