Rachel Sterneck receives NCWIT Collegiate Award Honorable Mention for her work on “Energy Efficient and Adversarially Robust Neural Networks” published in IEEE TCAD 2021....
Our paper on “MIME: Adapting a Single Neural Network for Multi-task Inference with Memory-efficient Dynamic Pruning” accepted into DAC 2022.
Our paper on “Privatesnn: Fully privacy-preserving spiking neural networks” accepted into AAAI 2022.
Our paper on “Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?” accepted into ICASSP 2022.
Two papers from our group - “1) Gradient-based Bit Encoding Optimization for Noise-Robust Binary Memristive Crossbar, 2) Examining and Mitigating the Impact of Crossbar Non-...
Prof. Panda gives a talk on “Towards Energy Efficient, Interpretable and Robust Neuromorphic Computing: Algorithm and Hardware Perspective” at the WTI Integration Conference.
Prof. Panda gives a talk on “Exploring Robustness in Neural Systems with Hardware aware and Spike-based Machine Intelligence” at the NIST Seminar Series on Artificial...
