Please feel free to reach out. We love to meet new people interested in the kind of research done here! Some suggestions that will make it more efficient for you:

Potential collaborators

Please send me an email. I am excited at the possibility of fruitful collaborations. Beyond natural language processing and machine learning, I am also (and especially) interested in joining researchers from sociology, psychology, and political science.

Potential postdoctoral researchers and PhD students

If you are interesting in postdoctoral research at SCIRE Lab, please send an email with an academic curriculum vitae, a research statement, a link to your homepage, a link to your code repositories, etc.

If you are applying for the Computer Science or Data Science PhD program at Stony Brook and want to work at SCIRE Lab, please feel free to reach out by sending an email with your curriculum vitae, a link to any code repositories you may have, and specifically mention if you have any previous peer-reviewed research publications. We are quite selective, and accept only a very small pool of students with a strong background in machine learning and/or natural language processing, mathematics and/or statistics, and programming (mainly in Python, and particularly in the use of modern machine learning libraries like PyTorch). To ensure that I read your application, please

• apply to the Computer Science (or Data Science) PhD program at Stony Brook,
• specify in your application that you want to work with me, and
• specify which ongoing project at our lab you want to work on.

I will be eager to meet you once you are admitted after a successful application.

Please understand that it may not be possible to respond to individual queries sent via email regarding research positions.

Currently, temporary or short-term positions cannot be accommodated.

Current Stony Brook Students

If you are a current Ph.D. student in the Department of Computer Science at Stony Brook University, and 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 or Keras), feel free to contact us via email about potential opportunities within the lab. 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.

If you are a MS (or 5-yr BS/MS) student in Computer Science at Stony Brook, and want to work in our lab for your advanced graduate project (CSE 523 and CSE 524) or your thesis (CSE 599), send me an email with the following:

• undergraduate transcript with grades,
• current Stony Brook graduate transcript with grades,
• link to your code repositories from prior project (e.g., GitHub or BitBucket), 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. If contacted, 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 Ph.D. student leading the project. Everyone in this lab is dedicated to their research, and expectations from team members include:

• 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 Ph.D. student, and the specifics will be dictated by the project requirements.

At the end of the project/thesis, the 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).

Research opportunities in the form of CSE 487 or CSE 495/496 exist for exceptional undergraduate students. Outstanding performance in coursework relevant to machine learning is a prerequisite (ideally, in CSE 353 and/or CSE 354). If you are a current undergraduate student of computer science or a closely-related area, feel free to contact us via email about these options. At the end of the project/thesis, the goal is that your 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 (subject to acceptance at a reputable venue). Undergraduate students are expected to be as dedicated to research as everyone else at SCIRE Lab, and commit significant time (10-12 diligent hours/week) to work toward a publishable result.