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 Java and/or Python), feel free to contact me via email about potential opportunities in my research group.
If you are a student in the MS or 5-yr BS/MS program in our department, and want to work with me for your advanced graduate project (CSE 523 and CSE 524) or your thesis (CSE 599), you can contact me with the following:
- Undergraduate transcript with grades
- Current SBU graduate transcript with grades
- Code repositories, if any (e.g., project on GitHub)
- Research publications, if any
A successful applicant will typically have good grades, a strong programming background in Java and/or Python with knowledge of version control, and a good understanding of machine learning fundamentals. Experience with deep learning or other ML/NLP libraries is a strong plus.
I strongly urge you to take the graduate ML and/or NLP courses. This is an important indicator of your area of interest. Please be prepared for initial interviews focusing 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. We take work ethics very seriously, and expect the student to do the same. The expectations are:
- 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 on research papers.
- Attending at least one weekly internal meeting with your project team. These meetings will be chaired by the leading PhD student, and the specifics will be dictated by the specific requirements of the project.
- At the end of the project/thesis, the work should be deemed publishable at a research conference or journal. If you have made significant contribution, you will be a co-author in the published research.
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).