Undergraduate Research Opportunities

Undergraduate Research Opportunities

Did you know that there are many opportunities in the CS department for undergraduates to participate in cutting-edge research?

  • You can take 0-6 credits of CSE 487 (Research in Computer Science) over several semesters, 3 credits of which can serve as a technical elective used to satisfy CS major requirements.
  • Alternatively, you can participate in a research project via the VIP program (Vertically Integrated Projects). If you complete 3 upper-division credits of VIP research that contains a substantial computing component, those 3 credits may substitute as a CS technical elective. Note that CSE 487 and VIP credit may not both be used to satisfy CS major requirements.
  • Finally, students in the CS Honors Program are required to complete a senior honors research project under CSE 495/496.

Whatever your situation may be, browse the research opportunities below and consider contacting the professor sponsoring the project if you are interested and meet the minimum qualifications.

Systems Research & Development

Projects supervisor: Michael Ferdman

Computer Architecture

You will help to publish a paper on a custom memory allocator that leverages CPU caches to improve performance of software. On the R&D spectrum, this is all the way on the R side; a research paper will be submitted for publication in this project.

Minimum qualifications: Applicants should have aced CSE 220 and CSE 320 and have a solid understanding of assembly programming.

Linux Administration Guru

You will figure out how to bring up a private cloud based on OpenStack with several hundred servers. On the R&D spectrum, this falls on the D side, not publishable research, but rather advanced development work.

Minimum qualifications: Applicants should have experience with Linux administration and networking. 

Artificial Intelligence, Machine Learning and Related Areas

Computer Vision and Machine Learning for Object Detection and Counting

Project supervisor: Minh Hoai Nguyen

The project's goals are to develop computer vision and machine learning models to detect and count objects in images, and subsequently optimize the models to fit into low-resource devices such as smart watches and phones. Through this project, students will have opportunities to learn cutting edge computer vision and machine learning algorithms, develop their research skills, and strengthen their coding competency.

Minimum qualifications: Must have completed either Fundamentals of Computer Vision (CSE 327) or Machine Learning (CSE 353) with a grade A- or better. Must have a GPA of at least 3.7. Experience with Android programming is desired, but not required.

Natural Language Processing (NLP)

Project supervisor: Niranjan Balasubramanian

The LUNR lab works on many problems in NLP including question answering, common-sense reasoning, building energy and compute-efficient NLP models, mobile NLP, NLP to assist formal verification of software, language generation, and much more. If you are interested in doing research in Natural Language Processing, Machine Learning or broadly in AI, please fill out this form. Prof. Balasubramanian will contact you if you are a suitable fit for one of his projects.

Algorithms and Theory

Projects supervisor: Pramod Ganapathi

Mathematical Puzzles

The goal of this project is to deeply understand various counterintuitive mathematical and algorithmic puzzles and all ways of solving them. The work includes reading web articles, reading books, reading papers, analyzing the pros and cons of existing solutions, developing new solutions if possible, coding and experimenting with the solutions to analyze new patterns, generalizing the puzzles, understanding different variants of the puzzles, and documenting. This work will be part of a new book on mathematical puzzles.

Minimum qualifications: Applicants should be strong in mathematics.

Organized Algorithmic Problem-Solving

The goal of this project is to understand the underlying organization/structure/template/pattern among several algorithms or solutions that use the same algorithm design technique or problem-solving strategy. The work includes reading web articles, reading books, analyzing and writing hundreds of algorithms for different classes of problems using common structures or templates, adding these algorithms to a website (using technologies such as github, jupyter, html, latex, etc), and creating beautiful visualizations for the recurrences used by the algorithms. The final product is a website that teaches organized algorithmic problem-solving and might be helpful to thousands of students, professionals, and teachers, to learn/teach algorithms in an organized way. 

Minimum qualifications: Applicants should be strong in algorithms and programming.

Interdisciplinary Research

Bioengineering Education, Application and Research (BEAR)

Project supervisor: Richard McKenna

The project's goals are to develop innovative solutions for Bioengineering education, application and research based on iterative engineering design processes and cutting-edge tools; produce tangible outcomes that can be applied and measured; and promote entrepreneurship activities with the collaboration of science and non-science majors.

See the project's page on the Vertically-integrated Project website for more information and to apply.

PoliTech: Automated Redistricting System

Project supervisor: Robert Kelly

The Stony Brook PoliTech project is a multidisciplinary research project that examines various aspects of Congressional redistricting. The project combines work of interest to Computer Science, Political Science, Applied Math, Psychology, Sociology, and others. At the heart of the research is the Stony Brook University Automated Redistricting System (ARS), which provides for the rapid generation of statewide congressional districts in accordance with constitutional and court-ordered guidelines, as well as user-defined preferences. For Computer Science majors, PoliTech explores efficient large scale graph partitioning algorithms, visualization of political and demographic data in a geographic context, and probabilistic assessment of districting plans.

Minimum qualifications: U2 status, 3.0 cumulative GPA

See the project's page on the Vertically-integrated Project website and this flyer for more information and to apply. Students may instead participate through CSE 487 if they wish.

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