Publications in 2022

Journal Articles

  1. 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).
  2. 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.
  3. 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.
  4. 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).
  5. 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).
  6. 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”
  7. 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.
  8. 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.

Conference Articles

  1. 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.
  2. 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.
  3. 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.