Approximate computing
Error-aware design of approximate multipliers, squarers, square-root and logarithmic circuits that trade a bounded error for large savings in area and energy.
Approximate Computing · Digital VLSI · Edge AI · Biomedical ASICs
Assistant Professor, Department of Electronics and Communication Engineering
Manipur Technical University, Imphal, Manipur, India
My research is on energy-efficient digital VLSI design: approximate arithmetic circuits with guaranteed error bounds, hardware architectures for machine-learning algorithms, and low-power electronics for biomedical applications such as EEG-based depth-of-anaesthesia monitoring, mood detection, and EEG artifact removal.
I received my Ph.D. in VLSI Design from NIT Silchar (2020), M.E. in Microelectronics from BITS Pilani (2014) and B.E. in Electronics and Communication Engineering from Manipal Institute of Technology (2011). Before joining Manipur Technical University in 2018, I worked in the semiconductor industry as an ASIC Engineer at NVIDIA and a Design Engineer at Sankalp Semiconductor in Bangalore.
Error-aware design of approximate multipliers, squarers, square-root and logarithmic circuits that trade a bounded error for large savings in area and energy.
Energy-efficient VLSI architectures for learning algorithms, including a cascade support vector machine with on-chip training and k-means clustering.
EEG-based depth-of-anaesthesia monitoring, EEG artifact removal and low-power biomedical ASIC design.
Published in Integration, the VLSI Journal (Elsevier).
PaperEGPARnet, a transformer–GRU model for removing ocular and muscular artifacts from EEG published in Medical & Biological Engineering & Computing (Springer).
Paper Work on spectral-edge frequency and spectral energies for depth-of-anaesthesia estimation presented at IEEE ICNGCS 2025.
Paper Machine-learning-based depth-of-anaesthesia estimation from EEG features presented at ICCEDT 2023 (Springer).
IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 67, no. 5, pp. 851–855, 2020
Circuits, Systems, and Signal Processing, vol. 39, no. 10, pp. 5272–5297, 2020
Medical & Biological Engineering & Computing, vol. 64, no. 3, pp. 975–999, 2026