- E. Lee, V. Chekuri and S. Mukhopadhyay, “A PFM boost harvester with System-level Self-tuned Maximum Power Point Tracking” accepted for publication at IEEE Transactions on Power Electronics (TPE).
- P. Saha and S. Mukhopadhyay, “Unraveled Multilevel Transformation Networks for Predicting Sparsely-Observed Spatiotemporal Dynamics,” accepted for publication in Philosophical Transactions of the Royal Society A – Mathematical, Physical, and Engineering Sciences.
- D. Kim, X. She, E. Lee, B. Kang, and S. Mukhopadhyay, “MONETA: A Processing-In-Memory-based Hardware Platform for the Hybrid Convolutional Spiking Neural Network with On-line Learning,” accepted for publication in Frontiers in Neuroscience.
- S. Dash, Y. Luo, A. Lu, S. Yu, and S. Mukhopadhyay, “Robust Processing-In-Memory with Multi-bit ReRAM using Hessian-driven Mixed-Precision Computation”, accepted for publication at IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD).
- K. Samal, P. Saha, M. Wolf, and S. Mukhopadhyay, “Task-driven RGB-Lidar Fusion for Object Tracking in Resource-Efficient Autonomous System”, accepted for publication at IEEE Transactions on Intelligent Vehicles (TIV).
- M. Mukherjee, B. A. Mudassar, M. Lee, E. Lee, and S. Mukhopadhyay, “Energy Efficient Pixel-Parallel Read-Out Circuits for Digital Image Sensors using Cross-Layer Pixel Depth Control,” accepted for publication at IEEE Sensors Journal in the special issue on “Selected Papers from IEEE Sensors 2020”
- E. Lee, N. Rahman, V. Chekuri, A. Singh and S. Mukhopadhyay, “A low power authentication IC for visible light based interrogation”, IEEE Transactions on Industrial Electronics (TIE), vol. 69, no. 3, March 2022, pp. 3120-3130.
- E. Lee, D. Kim, J. Kim, S. Lim and S. Mukhopadhyay, “A ReRAM Memory Compiler for Monolithic-3D Integrated Circuits in a Carbon Nanotube Process”, ACM Journal on Emerging Technologies in Computing Systems (JETC), vol. 18, no. 1, January 2022, pp 1–20.
- X. She, S. Dash, and S. Mukhopadhyay, “Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods,” International Conference on Learning Representation(ICLR), 2022.
- J. Seo, M. Mukherjee, N. M. Rahman, C. Delude, T. Krishna, J. Romberg, and S. Mukhopadhyay, “A Configurable Architecture for Efficient Sparse FIR Computation in Real-time Radio Frequency Systems,” IEEE International Microwave Symposium (IMS), 2022.
- K. Jung, J. Woo, and S. Mukhopadhyay, “An On-chip Accelerator with Hybrid Machine Learning for Modulation Classification of Radio Frequency Signals,” IEEE International Microwave Symposium (IMS), 2022.