Highlights
Simulation Frameworks
Processing-in-Memory Design: Performance and Data Movement in Compact PIM Design [Code], KV Cache Quantization and Pruning [Code].
Compression: Norm-Q Quantization for Hidden Markov Model in Neuro-Symbolic Application [Code], Hessian-Enhanced Robust Optimization [Code].
Noise-aware Training: Photonic Generative Model [Code].
Biography
Xiaoxuan Yang is an Assistant Professor in the Electrical and Computer Engineering Department at the University of Virginia. She was a Postdoctoral Scholar in the Robust Systems Group at Stanford University. She received her Ph.D. degree in Electrical and Computer Engineering at Duke University. She received the B.S. degree in Electrical Engineering from Tsinghua University and the M.S. degree in Electrical Engineering from the University of California, Los Angeles (UCLA). Her research interests include in-memory computing, neuromorphic computing, energy efficient design, and hardware-software co-design.
Xiaoxuan has received the Best Paper Award at GLSVLSI 2025. Her research work won Third Place of ACM Student Research Competition SRC at ICCAD and Best Research Award at ACM SIGDA Ph.D. Forum at DAC. She was recognized as a Rising Star in EECS, an NSF iREDEFINE Fellow, a Machine Learning and Systems Rising Star, and a Rising Scholars Postdoc Fellow.
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