Brown CS News

The program, first of its kind worldwide, aims to enable these young scientists to conduct high-quality, policy-informed AI research, to empower them to advocate for new AI policies or changes to existing policy, and to build a pipeline of qualified technologists to fill emerging needs in government.

“We don’t have a robust theory of humans,” Will Crichton says. But he’s working on it. Formerly a Brown CS postdoctoral researcher advised by Shriram Krishnamurthi, he returns to the Department this fall as assistant professor. He’s one of two recent hires in the multi-year CS With Impact campaign, our largest expansion to date.

This fall, she joins Brown CS as associate professor within a year of receiving a Sloan Research Fellowship, an NSF CAREER Award, and the ACM SIGGRAPH Significant New Researcher Award, as well as being named to MIT’s 35 Under 35.

New research (“Towards Improving Reward Design in RL: A Reward Alignment Metric for RL Practitioners”) co-authored by Brown CS faculty member Serena Booth has received the conference’s Outstanding Paper Award for Emerging Topics in Reinforcement Learning. 

CNTR PhD student Rui-Jie Yew and faculty collaborators Suresh Venkatasubramanian and Jeff Huang received a Best Paper Award at the 2025 ACM Designing Interactive Systems (DSI) Conference for their paper "Copyrighting Generative AI Co-Creations."

Only weeks after earning the ECOOP Distinguished Paper and Distinguished Artifact Awards for work in formal methods visualization, Brown PLT has won an International Conference on Computer-Aided Verification (CAV) Distinguished Paper Award for a new misconception-based automated Linear Temporal Logic tutoring system.

Deepti Raghavan, Malte Schwarzkopf, and Nikos Vasilakis were chosen by a distinguished group of Google engineers and researchers for work that leads the analysis, design, and implementation of efficient, scalable, secure, and trustworthy computing systems. 

The new institute, based at Brown and supported by a $20 million National Science Foundation grant, will convene researchers to guide development of a new generation of AI assistants for use in mental and behavioral health.

New work (Cope and Drag, also known as CnD) from Brown PLT is a novel lightweight diagramming language. It’s just earned recognition at ECOOP 2025, receiving both a Distinguished Paper and a Distinguished Artifact Award.

Ritambhara aims to develop new computational methods that can combine multiple types of health information to better predict diseases and design effective treatments tailored to each individual, and she’s just received a National Science Foundation (NSF) CAREER Award to help pursue them.