Research Opportunities

Research positions can be challenging to get, and the Meta-URAs wanted to provide information of how to get your foot in the door for  the labs of specific professors.  We have worked with several professors to create a list of any prerequisites needed to be able to start researching. As we get more information from professors, we will add to this list. 

Opportunities within the department:

Stephen Bach: Our group primarily works on improving the ways that we teach computers. Check out our work to learn more. Interested students should usually have a background in some area related to machine learning (such as CSCI 1420, CSCI 1470, etc.), natural language processing (such as CSCI 1460), or computer vision (such as CSCI 1430). We always welcome visitors at our group meetings. Email me to connect!

Ugur Çetintemel: My current work is at the intersection of database systems and generative AI. Interested students should have a background in systems and/or AI, ideally both. Please reach out with your CV and specific interests if you would like to explore whether we can work on a project together. 

Yu Cheng: Mathematical and algorithmic maturity. If you are interested in getting to know the theory/algorithms community at Brown CS, you are welcome to attend our weekly seminars (where we invite external speakers, https://theoryseminar.cs.brown.edu/) as well as the weekly algorithm lunch (where students give talks). To learn more about my research, consider taking CSCI 2952-Q and/or CSCI 1520.

Diana Freed: The Sociotechnical Systems and Wellbeing Research Lab (SWRL) designs, develops, deploys, and evaluates sociotechnical systems that make technology-mediated environments safer and more equitable for vulnerable and at-risk communities. We are seeking motivated undergraduate and graduate students to join our group. Email me directly to learn about current and future research opportunities.

Amy Greenwald: The GLAMOUR research group works at the intersection of economics and computer science. Interested students should usually have a background in some area related to optimization (such as APMA 1160), machine learning (such as CSCI 1420, CSCI 1470, etc.), or economics (such as CSCI 1440). We always welcome visitors at our group meetings. Email arjun_prakash@brown.edu to connect!

Maurice Herlihy: Having taken CSCI176 (Multiprocessor Synchronization) is a plus, but not required.

D. Ellis Hershkowitz: See this for more information.

Jeff Huang: My research is focused on generative AI lawand human-computer interaction. I work with students directly and prefer that they take one of my courses.

Sorin Istrail: Take CSCI1820 (Algorithmic Foundations of Computational Biology) and have done very well

Vasileios Kemerlis: Brown's Secure Systems Lab (SSL) designs and develops innovative protection mechanisms for hardening (software) systems against exploitation. We also investigate offensive methods for demonstrating weaknesses in real-world, deployed systems and/or defenses. To work with us, having taken CSCI 1650 (Software Security and Exploitation), and ideally CSCI 1670/1690 too, and have done well, is a prerequisite.

Philip Klein: Working on algorithms for hard problems in road networks, such as traveling salesman and facility location.  Summer research opportunities available to those who take Optimization Algorithms for Planar Graphs (CSCI2500-B) in the spring. The prerequisite for that seminar is an algorithms class such as Design and Analysis of Algorithms (CSCI1570), taught in the fall. 

Shriram Krishnamurthi: Take and do very well in CSCI1730 (Programming Languages). Also interested in talking with students who have taken CSCI 1377, 1710, 1715.

David Laidlaw: Please refer to the Visual Computing "onboarding" document. A good project to consider for working with me is to get some virtual reality software working on a new scientific dataset. Or reach out if something else feels more relevant.

Michael Littman: He is focused on how to combine ideas from machine learning and more traditional programming to make it easier for end-users to tell computers what to do. He's currently away from Brown, so his capacity to supervise students is limited, but he'll make time for projects that are closely aligned with this research agenda.

Peihan Miao: My research is in both theoretical and applied cryptography, with a focus on secure multi-party computation. Prerequisites include mathematical maturity and having taken CSCI 1510 (Introduction to Cryptography and Computer Security). Ideally, also consider taking CSCI 2952L, 2590, or 1515. If you are interested in learning more about cryptography research, you are welcome to attend our weekly crypto reading group (subscribe to the crypto mailing list here)

Akshay Narayan: Ideally, take CSCI 1675 or 2680, though not strictly required. Email me to ask about current projects.

Tim Nelson: Take CSCI 1710/1950Y (Logic for Systems). Ideally, take CSCI 0320 (Introduction to Software Engineering) or 1730 (Programming Languages).

Deepti Raghavan: My lab has several projects related to (1) systems for machine learning applications and (2) datacenter operating systems and networking. Most projects require system programming skills, so CSCI0300 or equivalent experience is required. For ML-related projects, CSCI1390, or experience from some ML class is helpful, but not required. Please email me for details.

Sherief Reda: My SCALE group has several research opportunities related to (1) SW/HW co-design of ML/AI applications, (2) the use of ML techniques in optimization, and (3) emerging computing paradigms.

Steve Reiss: While retired, I am still actively doing research. Students wishing to work with me must have extensive programming experience, notable with Java (at least CS0320) and be comfortable with multithreaded programs and development environments. Students must also be willing to interact with me remotely. Please email me if you are interested.

Daniel Ritchie: Check this web page for more information.

Malte Schwarzkopf: for research with the ETOS group, completing CSCI 1670/1690 or 2390 is helpful and preferred. Email me directly to ask about current and future opportunities.

Srinath Sridhar: Prof. Srinath Sridhar is looking for students who are interested in 3D/4D computer vision and artifitial intelligence. This kind of research drives practical applications building spatially-intelligent AI, robotics, augmented/virtual reality, autonomous vehicles, etc. Examples of potential projects include 3D human/object reconstruction, spatio-temporal reconstruction, vision for robotics, and vision for virtual/augmented reality. Please see here to get a sense of past projects.

Roberto Tamassia: Take CSCI1660 (Computer Systems Security).

Stefanie Tellex: Check this website for more information. 

James Tompkin: visual.cs.brown.edu/onboarding ! www.jamestompkin.com ! A fascination with visual computing, especially cameras. Most projects involve computer vision (e.g., CSCI1430, CSCI2951I) and/or computer graphics (e.g., CSCI123, CSCI2240), and often include components of interaction and machine/deep learning (e.g., CSCI1420, CSCI1470). Strong programming skills with a focus on performance (e.g., GPUs).

Eli Upfal: Take CSCI1550 (Probability and Computing: Randomized Algorithms and Probabilistic Analysis) and have done well. Most likely also be a joint Math/CS or Applied Math/CS concentrator. 

Nikos Vasilakis: Most projects require the ability to program. Any courses on software systems (e.g., CSCI 300, 1310, 1380, 1952R), programming languages (e.g., CSC1730, 1710, 1715) or security (e.g., CSC1660, CSC1650) are a strong plus, but not required. Visit atlas.cs.brown.edu for project-specific onboarding, prereqs, and starter mini-projects.

Suresh Venkatasubramanian: I direct the Center for Tech Responsibility, Reimagination, and Redesign (cntr.brown.edu). We work on many projects at the juncture of technology and society. If you’re interested in participating in the work of the CNTR, visit our Get Involved page. We are always looking for motivated students to participate in a variety of roles, whether it be as a builder, advocate, connector, or storyteller.

Opportunities outside the department:

Thomas Serre (CLPS department): For students interested in deep learning and working at the intersection between artificial and biological intelligence. Solid PyTorch experience. Students should have ideally taken CLPS1950 or CLPS1291 or at least a computer vision, machine learning or a deep learning course.

There are three ways to do research: