My research over the past 19 years has focused on an array of problems in Information and Data Sciences viewed through the lens of Information Theory, with an emphasis on both deriving fundamental performance limits and also on designing algorithms approaching these fundamental limits. A particular focus is on information storage/communication/processing systems that may be under attack by eavesdropping and/or jamming malicious parties – the tools I have helped develop over the last two decades provide unconditional information-theoretic security guarantees (independent of cryptographic security guarantees often considered in security scenarios, which usually rely on computational hardness assumptions that are sometimes fragile).

My research group calls itself the CAN-DO-IT team: Codes, Algorithms, Networks – Design and Optimization for Information Theory. The work that I and collaborators focus on lies in the intersection of and impacts, among other fields, Information Theory, Coding theory, algorithm design, high-dimensional geometry, estimation theory, and optimization. Despite the tools of my trade being mathematically abstract and theoretical, they have tangible real-world implications and a broad range of data-driven applications, such as for large-scale data processing, secure distributed computing, and robust distributed data storage.

Specific projects I am involved in, and which may potentially lead to research projects (feel free to email me), include: