معرفی
Xiaoxuan Yang is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Virginia. Her research focuses on processing-in-memory-based system design, biologically plausible systems, and hardware accelerators for emerging applications. She has held postdoctoral positions at Stanford University's Robust Systems Group and served as a research scientist at the University of Virginia.
- Ph.D.: Electrical and Computer Engineering, Duke University
- M.S.: Electrical Engineering, University of California, Los Angeles
- B.S.: Electrical Engineering, Tsinghua University
Her research integrates neuromorphic computing, LLM acceleration, and hardware-software co-design, with specific interests in ReRAM crossbars, photonic neural networks, and memristor synapses. Current projects address stochastic noise resilience, quantization optimization, and energy-efficient AI.
The 15 most recent publications explore PIM architectures (38%), neuromorphic systems (30%), ML hardware (25%), and optical computing (7%). Key trends include large language model acceleration, hardware robustness, and emerging memory technologies.
- Third Place ACM Student Research Competition (ICCAD)
- Best Research Award ACM SIGDA Ph.D. Forum (DAC)
- Best Paper Award GLSVLSI 2025
- Rising Star in EECS
- NSF iREDEFINE Fellow
- Machine Learning and Systems Rising Star
- Rising Scholars Postdoc Fellow
