Assistant Professor, Gr-I
Dr. Das received his Ph.D. in Electrical Engineering from IIT Bombay in 2020. His doctoral research involved developing a simulation framework using the non-equilibrium Green’s function (NEGF) spin transport formalism to study the scaling effects of magnetic tunnel junction (MTJ) devices. Later, he worked on a micromagnetic simulation framework to design a skyrmion-based self-sustaining oscillator.
As a postdoctoral research fellow at the National University of Singapore (NUS), Dr. Das developed a simulation framework based on the Fokker-Planck (FP) equation to model the impact of stochastic programming processes in emerging non-volatile memory (eNVM) devices. He subsequently shifted his research focus to the applications of spintronic devices in neuromorphic computing, performing micromagnetic simulations to replicate the functionality of biological neurons and synapses for spiking neural networks (SNNs) using spintronic devices, such as magnetic skyrmions and domain walls. Dr. Das has also collaborated with experimentalists on spintronic devices, integrating the characteristics of fabricated devices into neuromorphic computing models.
His current research interests involve investigating emerging devices and leveraging their characteristics to optimize the performance of neuromorphic systems and other computing architectures. He is focused on developing novel devices, algorithms, and neuromorphic architectures that are both powerful and energy-efficient.
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