About Me

I received my B.S. in Mathematical and Physical Sciences in July 2015 from the University of Electronic Science and Technology of China (UESTC), and earned my Ph.D. in Automation in July 2021 from Tsinghua University. In December 2021, I joined the Department of Precision Instrument at Tsinghua University as a postdoctoral researcher under the Shuimu Tsinghua Scholar Program (水木学者). I have been recognized with several honors including the Outstanding Ph.D. Graduate of Tsinghua University, the Outstanding Ph.D. Dissertation Award of Tsinghua University, and the 2022 China National Postdoctoral Program for Innovative Talents (博新计划). I have published over 20 papers, with three as the first or corresponding author in IEEE TPAMI, as well as papers in NeurIPS (spotlight), ICML, AAAI, IEEE TCYB, IEEE TNNLS, and other top-tier conferences and journals in artificial intelligence.

Research Interests:

🔹 Brain-Inspired Foundation Models
– Developing brain-inspired theoretical frameworks for next-generation AI beyond transformer-based LLMs.
– Endowing LLMs energy-efficiency learning ability and human-level compositional reasoning ability.

🔹 Spiking Neural Networks (SNNs)
– Designing neuromorphic neural networks with biologically plausible learning rules (e.g., spike-timing-dependent plasticity).
– Bridging gaps between computational neuroscience and machine learning.

🔹 Brain-Inspired World Models for Real-Time Adaptive Robotics
– Brain-inspired real-time model-based reinforcement learning for robotics.
– Building embodied intelligence systems inspired by the brain mechanisms of memory, decision, reasoning.

I am dedicated to advancing brain-inspired AGI, exploring novel computing principles, and developing efficient, scalable models for real-world applications.