Stephen Bach And Srinath Sridhar Receive Named Chairs
- Posted by Jesse Polhemus
- on June 2, 2025
Brown CS is happy to announce that effective as of July 1, 2025, faculty members Stephen Bach and Srinath Sridhar have received named chairs. Steve is now the Eliot Horowitz Assistant Professor in Computer Science and Srinath is the John E. Savage Assistant Professor in Computer Science.
Stephen Bach
Steve came to Brown CS in 2018 after receiving his doctorate from University of Maryland and working as a postdoctoral scholar at Stanford. He leads the BATS (Bach’s Awesome Team of Students) machine learning research group, which seeks to improve the processes by which humans teach and instruct computers. That includes learning to generalize from fewer examples, with methods like zero-shot and few-shot learning, as well as engineering training data, with methods like synthetic data generation and programmatic weak supervision. Applications of their work include information extraction, image understanding, scientific discovery, and other areas of data science.
Steve’s latest papers include “Crosslingual Reasoning through Test-Time Scaling”, “Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance”, and “$100K or 100 Days: Trade-offs when Pre-Training with Academic Resources”. He teaches CSCI 1420 Machine Learning and CSCI 2952-C Learning with Limited Labeled Data.
Recently, Steve has given invited talks at the University of Rhode Island’s AI Big Data Forum, EpiVax’s Artificial Intelligence/Human Intelligence & Immunoinformatics Workshop, and Snorkel AI’s Enterprise LLM Summit. Last year, he co-authored work that earned a Best Paper Award at the Socially Responsible Language Modelling Research (SoLaR) workshop at the thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), and earlier this month, he and his collaborators received a Seed Award from Brown University's Office of the Vice President for Research (OVPR).
Srinath Sridhar
Srinath came to Brown CS in 2020 after receiving his doctorate from the Max Planck Institute for Informatics and working as a postdoctoral scholar at Stanford University. He leads the Interactive 3D Vision & Learning Lab (IVL), part of Brown Visual Computing, which works on 3D computer vision and machine learning problems to better understand how humans interact with the world. Their research spans 3D spatiotemporal visual understanding of objects, humans in motion, and human-object interactions.
Srinath’s latest papers include “GigaHands: A Massive Annotated Dataset of Bimanual Hand Activities”, “MotionGlot: A Multi-Embodied Motion Generation Model”, and “GeoDiffuser: Geometry-Based Image Editing with Diffusion Models”. He teaches CSCI 1430: Introduction to Computer Vision and CSCI 2952-K: Topics in 3D Computer Vision and Machine Learning.
Srinath is a recipient of an NSF CAREER Award, a Google Research Scholar award, a Best Student Paper award at WACV, and an Outstanding Reviewer award from the Conference on Computer Vision and Pattern Recognition (CVPR). His recent service to the field includes serving as Area Chair for CVPR, ICCV, SIGGRAPH, SIGGRAPH Asia, and as a panelist for the National Science Foundation.
For more information, click the link that follows to contact Brown CS Communications Manager Jesse C. Polhemus.
