Sebastian Bruch

Sebastian Bruch is a senior research scientist at the Institute for Experiential AI at Northeastern University. He earned his Ph.D. in computer science from the University of Maryland, College Park in 2013. Bruch is interested in exploring the utility of noise and uncertainty in producing order, efficiency, fairness, and other desirable properties in decision-making processes. His research focuses on probabilistic data structures and approximate algorithms for retrieval; efficient and effective algorithms for learned ranking functions; and stochastic ranking policies and decision-making.

Bruch is the author of "Foundations of Vector Retrieval" and co-author of "Efficient and Effective Tree-based and Neural Learning to Rank." His published works have appeared in leading information systems journals, including ACM Transactions on Information Systems, IEEE Transactions on Knowledge and Data Engineering, and Foundations and Trends in Information Retrieval. He has contributed to the proceedings of and served on the program committees of premier conferences including SIGIR, WSDM, SIGKDD, NeurIPS, ICLR, and the Web Conference.

After nearly a decade in the industry, Bruch returned to academia in 2024 and is currently a senior research scientist at Northeastern University in Boston. He also serves as an associate editor for the ACM Transactions on Information Systems journal.