His current work is focused on energy-efficient nanoelectronics and functional materials. More specifically, he works on non-von Neumann computing paradigms harnessing the physics of memristive devices to perform both memory and computing. He is interested in circuits and algorithms for on-chip implementation of ML/AI and nonconventional information processing algorithms (e.g. spike-based computing).