Information for Prospective Students
If you are a PhD student in the Department of Computer Science at Stony Brook University, and have a strong background in (i) mathematics and/or statistics, and (ii) programming (mainly in Python, and particularly in the use of modern machine learning libraries like PyTorch), feel free to contact Dr. Banerjee via email about potential opportunities within the research group.
Unfortunately, this research group cannot accommodate temporary or short-term research positions.
If you are a student in the MS or 5-yr BS/MS program in the computer science department, and want to work with Dr. Banerjee for your advanced graduate project (CSE 523 and CSE 524) or your thesis (CSE 599), contact with the following:
undergraduate transcript with grades,
current SBU graduate transcript with grades,
code repositories, if any (e.g., a project on GitHub), and
research publications, if any.
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 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. Please be prepared for an initial technical interview on NLP/ML concepts. If your interview is satisfactory, you will be put into a specific project team, with a PhD student leading the project. Dr. Banerjee and his team are dedicated to their research, and expectations from the team members include the following:
Approximately 10-12 hours of diligent work on a weekly basis.
Attending one weekly research group meeting. Individual and project progress will be discussed and assessed in these weekly meetings. They will also often include discussions and presentations of research papers.
Attending at least one weekly internal meeting with your project team. These meetings will be chaired by the lead PhD student, and the specifics will be dictated by the project requirements.
At the end of the project/thesis, the work should be deemed 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.
Research opportunities in the form of CSE 487 or CSE 495/496 exist for exceptional BS students as well. Outstanding performance in coursework relevant to machine learning is a prerequisite (ideally, in CSE 353 and/or CSE 354).