Brown CS News

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.

Brown CS alum James Hendler has recently been honored with the 2025 Association for the Advancement of Artificial Intelligence (AAAI) Feigenbaum Prize for his groundbreaking work in artificial intelligence. The award recognizes Jim’s sustained and seminal contributions to experimental AI, especially related to AI planning systems, knowledge representation, and the Semantic Web, fields that have helped lay the foundation for modern AI applications. Jim completed his PhD at Brown under the late Eugene Charniak, whose mentorship, he says, played a formative role in his career.

The fellowship supports early-career computing researchers who bring interdisciplinary expertise from the social sciences to infuse ethical and societal perspectives into Trustworthy AI development, and Diana Freed is one of the inaugural recipients.

This year, research from Brown Visual Computing (BVC) student Yiqing Liang and her collaborators at NVIDIA was recognized as a best paper award candidate with oral presentation.