About

I am a second-year PhD student in the Department of Electrical and Computer Engineering at George Mason University, advised by Prof. Weiwen Jiang. I received my B.E. in Computer Science and Technology from Zhejiang University in 2022.

Research Interests

My research interests include quantum sensing, quantum optimization, and application-driven hardware-software co-design for scientific computing systems. I focus on developing intelligent methods that are not only accurate but also practical under real-world constraints such as latency, energy, and communication efficiency.

Currently, I am working on projects that bridge quantum and classical sensing with deep learning, as well as hardware-physics co-guided frameworks for distributed scientific machine learning. I contributed to EPIC, a hardware- and physics-co-guided distributed SciML framework for full-waveform inversion accepted at DAC 2026, which explores how edge-side encoding and physics-aware decoding can reduce communication latency and energy while preserving physical fidelity.

I am drawn to interdisciplinary problems that connect machine learning, physical insight, and practical system constraints. My long-term goal is to develop efficient AI systems that co-optimize across algorithms, hardware, and physical models to address important challenges in sensing, computing, and emerging technologies.

News

• [Jul 2026] One paper accepted at CODES+ISSS 2026 (to appear in IEEE TCAD).
• [Jul 2026] Selected as a DAC 2026 Young Fellow.
• [Jun 2026] One paper accepted at DAC 2026 (Design Automation Conference).
• [Jan 2025] Started my PhD at George Mason University.

Education

• Ph.D. in Electrical and Computer Engineering, George Mason University, 2025 - Present
• B.E. in Computer Science and Technology, Zhejiang University, 2018 - 2022