EnCharge AI

Holds a Ph.D. in electrical engineering and computer science from MIT. Serves as the Ralph H. and Freda I. Augustine Professor of Electrical and Computer Engineering at Princeton University and directs Princeton's Keller Center for Innovation. Spent six years developing and de-risking analog in-memory computing technology with DARPA and DOD funding before spinning out EnCharge AI in 2022. His foundational 'Configurable In-Memory Computing Engine' patent, which earned the 2024 Edison Patent Award in Computing Technology from the R&D Council of New Jersey, underpins EnCharge's core product combining memory and compute in analog circuits to run AI inference far more efficiently than conventional digital chips.

Holds a Ph.D. in electrical engineering from Stanford University. Spent over two decades at IBM Research, ultimately attaining the rank of IBM Fellow — one of the company's highest technical honors — and founding the IBM Research AI Hardware Center. Led world-wide efforts on advanced AI hardware, software, and algorithmic co-design at IBM, with contributions in low-precision arithmetic and compiler advances adopted in IBM's flagship AI products. Co-founded EnCharge AI in 2022 to commercialize analog in-memory computing technology for edge-to-cloud AI inference deployment.

An operations and business leader who co-founded EnCharge AI in 2022 alongside Princeton professor Naveen Verma and former IBM Fellow Kailash Gopalakrishnan. Serves as COO, overseeing the operational scaling of the company as it commercializes its analog in-memory compute chip technology. EnCharge has raised $44.3 million in private investment and secured an $18.6 million DARPA OPTIMA program grant to advance next-generation in-memory AI processors designed to dramatically reduce the energy cost of large-scale AI inference.