Vector Database Systems
This project focuses on designing efficient indexing techniques for data-intensive applications.
My research focuses on distributed systems, large-scale databases, cloud computing, federated learning, and the intersection of systems and artificial intelligence.
This project focuses on designing efficient indexing techniques for data-intensive applications.
This project investigates client selection strategies for federated learning. We study the design space of existing approaches, analyze their trade-offs, and develop new adaptive client selection techniques to improve training efficiency, model accuracy, and system scalability.
This project focuses on designing scalable Byzantine fault-tolerant (BFT) consensus protocols for replicated systems and permissioned blockchains. The research introduces novel protocol designs that improve throughput, communication efficiency, and scalability while preserving the safety and liveness guarantees of Byzantine consensus.
I am looking for motivated students interested in distributed systems, databases, cloud computing, federated learning, vector search, and AI infrastructure. Students should be comfortable learning systems concepts, reading papers, and building prototypes.