Qiaochu Zhang

Qiaochu Zhang serves as Assistant Professor in the Charles L. Brown Department of Electrical and Computer Engineering at the University of Virginia, joining in Summer 2024 after industry experience at NXP Semiconductors. His research spans analog/mixed-signal IC design, electronic design automation, and hardware acceleration for complex computational problems.

Education:

• B.S. in Physics (Hons.), Fudan University (2017)
• Ph.D. in Electrical Engineering, University of Southern California (2024)

Research focuses on four interconnected domains:

• Mixed-Signal VLSI Design: Advanced data converters, frequency synthesizers, and transceivers enabling high-speed wireless systems
• Electronic Design Automation: Machine learning-driven frameworks for automating analog circuit customization and performance optimization
• Mixed-Signal Computing: Hardware accelerators for neural networks and NP-hard combinatorial optimization problems
• Low Power Design: Energy-efficient circuit techniques for portable and embedded applications

His publication trajectory (2021-2025) reveals a strategic evolution toward time-domain circuits and analog accelerators, with increasing emphasis on stochastic computing for SAT solvers and memristor-based quadratic programming. Key innovations include ultrafast metastability-resilient solvers and synthesizable TDC architectures that bridge digital precision with analog efficiency.

Scientific recognition includes:

• USC Provost’s Fellowship (2017-2020)
• USC Ming Hsieh Institute Ph.D. Scholar (2021-2022)
• IEEE ISSCC Student Travel Grant (2023)
• IEEE SSCS Predoctoral Achievement Award (2022-2023)

Dr. Zhang actively recruits Ph.D. students for his UVA research group, focusing on integrated circuit design and hardware acceleration. Prospective students must apply through UVA's Computer Engineering or Electrical Engineering graduate programs. His research is supported by faculty startup resources and builds on prior industry collaboration with NXP Semiconductors.

The research group operates from Rice Hall 309, establishing specialized facilities for mixed-signal/RF circuit prototyping and EDA tool development. Current efforts focus on translating theoretical circuit innovations into practical computing solutions for optimization-intensive applications.