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.

NSF Research Experience for Undergraduates (REU) in Big Data

Project supervisor: Fusheng Wang

We have multiple openings for NSF funded Research Experience for Undergraduates (REU). The program is open to U.S. citizens and permanent residents who are undergraduates majoring in computer science or informatics, or a related field. The REU projects are extensions of the NSF CAREER project "High Performance Spatial Queries and Analytics for Spatial Big Data" and "CIF21 DIBBs: Middleware and High Performance Analytics Libraries for Scalable Data Science". Students will conduct interdisciplinary research crosscutting computer science and biomedical informatics. Example projects include (not limited to): 1) Understanding COVID-19’s Impact on Opioid Misuse Using Social Media; 2) Incorrect Face Mask Wearing Detection and its Deployment Using Amazon DeepLens; 3) Geospatial-temporal Patterns Analysis of 30-day Readmissions of Patients in New York State; 4) Cancer Burdens in Long Island at Census Tract Level; 5) 2020 US Presidential Election and its Correlation Factors (in NYS) at High Spatial Resolution.

You can either start to work immediately (hourly based), or work full-time from June 1 to August 6. You will work in the Lab of Data Management and Biomedical Data Analytics, directed by Dr. Fusheng Wang. We invite you to join a community of undergraduate researchers, graduate students and faculty to develop innovative solutions for processing, managing, and analyzing large scale data.

Application to the REU Program

The program is open to U.S. citizens and permanent residents who are undergraduates majoring in computer science or informatics, or a related field, with a GPA > 3.0/4.0. Applicants must have completed at least their freshman year. You must still be in a student status at the time of the research. Potential students submit an application form, unofficial transcript, one letter of recommendation, a personal statement on research interest, previous research experiences, and any coursework relevant to their research interests.

Selection will be rolling based.

Please fill the 1) application form, 2) uploading an essay, CV and unofficial transcript. (You need a GMail account to sign in.) 3) Please have a letter of reference sent to fusheng.wangatstonybook.edu

The REU Experience

The REU program at Stony Brook University “Big Spatial and Image Data Analytics” is an opportunity for qualified, academically talented and motivated undergraduate students interested in eventually pursuing their doctor degree in Computer Science or Biomedical Informatics. The program provides the student an intensive research experience with leading researchers in the field.

The program is expected to run from June 1 to August 6, 2021. For Stony Brook Students, working hourly in Spring is welcome. The REU student will participate in a research project mentored by Dr. Fusheng Wang and his Ph.D. students, and become fully integrated in the research group. The student will attend weekly research meetings, and present the research results. The student will also attend academic development workshops co-located with other Stony Brook University REU site, and have the opportunity to present a poster at the REU symposium.


The participant will receive a stipend of $500 per week, for a total of $5000 summer stipend for full-time research (or hourly if working from Spring, up to $5000).

Systems Research & Development

Computer Architecture

Project supervisor: Michael Ferdman

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

Project supervisor: Michael Ferdman

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.

Computer Systems and Storage

Project supervisor: Erez Zadok

We seek to recruit qualified undergraduate CS students each semester to join a project involving broadly computer operating systems and storage systems. Projects often touch on topics of operating systems, data storage, networking, security, machine learning, performance, and more. Students will get an opportunity to work on cutting-edge research topics alongside graduate students and faculty, and even publish papers and attend conferences.  Qualifications expected: C/C++ experience, passed CSE-306 (OS) or CSE-320, and CSE-373 (Algorithms), or equivalent. Students who join the project can receive project credit or be paid for their time ($15/hr minimum, available to domestic students under the NSF REU program); salary is commensurate with experience. To apply, use the following Google Form (where you'd be asked to upload your up-to-date resume): here

Artificial Intelligence, Machine Learning and Related Areas

EyeCanDo: Eye Gaze-based Communication for Patients with Motor Disabilities

Project supervisor: Fusheng Wang

EyeCanDo is an eye gaze-based app running on iPhone/iPad that can advance the communication of patients with motor disability and improve their quality of life. It combines augmented reality, human-computer interaction and AI to 1) achieve high accuracy and stability, 2) provide multiple levels of communication – from basic needs to reading, messaging, typing and entertainment, and 3) automatically adapt to each individual for a smooth user experience.

We are looking for students with strong motivation on mobile app development (iOS) to work on the project.

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.