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Resume (English only)
Academic Achievements
NICS-EFC lab has 8 papers accepted by NeurIPS 2025; Won the 10-Year Retrospective Most Influential Paper Award at ASP-DAC 2024; Research on large model multi-user inference scheduling accepted by MLSys 2025; Published the book 'Efficient Deep Learning: Model Compression and Design'.
Research Experience
Leading research directions include: single-agent, multi-agent reinforcement learning algorithms and applications, architecture and system design for domain-specific acceleration, and multi-agent systems.
Background
Research Interests: Multi-agent reinforcement learning algorithms, efficient and robust deep learning systems, domain-specific acceleration, multi-agent systems. Brief Introduction: Leader of the Energy Efficient Computing Group at the Nanoscale Integrated Circuits and Systems Lab, Department of Electronic Engineering, Tsinghua University.
Miscellany
For more information and video clips, please visit https://space.bilibili.com/642618077