A 28nm FDSOI integrated reconfigurable switched-capacitor based step-up DC-DC converter with 88% peak efficiency. - Avishek Biswas; Yildiz Sinangil; Anantha P. Chandrakasan (ESSCIRC, 2014)

A 28 nm FDSOI Integrated Reconfigurable Switched-Capacitor Based Step-Up DC-DC Converter With 88% Peak Efficiency. - Avishek Biswas; Yildiz Sinangil; Anantha P. Chandrakasan (IEEE J. Solid State Circuits, 2015)

A 0.36V 128Kb 6T SRAM with energy-efficient dynamic body-biasing and output data prediction in 28nm FDSOI. - Avishek Biswas; Anantha P. Chandrakasan (ESSCIRC, 2016)

An offset-cancelling four-phase voltage sense amplifier for resistive memories in 14nm CMOS. - Avishek Biswas; Umut Arslan; Fatih Hamzaoglu; Anantha P. Chandrakasan (CICC, 2017)

Conv-RAM: An energy-efficient SRAM with embedded convolution computation for low-power CNN-based machine learning applications. - Avishek Biswas; Anantha P. Chandrakasan (ISSCC, 2018)

Energy-efficient smart embedded memory design for IoT and AI. - Avishek Biswas (2018)

CONV-SRAM: An Energy-Efficient SRAM With In-Memory Dot-Product Computation for Low-Power Convolutional Neural Networks. - Avishek Biswas; Anantha P. Chandrakasan (IEEE J. Solid State Circuits, 2019)

Neural Network Based Brain Tumor Segmentation. - Darshat Shah; Avishek Biswas; Pranali Sonpatki; Sunder Chakravarty; Nameeta Shah (BrainLes@MICCAI (2), 2021)

Motor Babble: Morphology-Driven Coordinated Control of Articulated Characters. - Avinash Ranganath; Avishek Biswas; Ioannis Karamouzas; Victor B. Zordan (MIG, 2021)

An area-efficient 6T-SRAM based Compute-In-Memory architecture with reconfigurable SAR ADCs for energy-efficient deep neural networks in edge ML applications. - Avishek Biswas; Hetul Sanghvi; Mahesh Mehendale; G. Preet (CICC, 2022)