• I recently joined NVIDIA as a Distinguished Engineer, where I’m developing VLSI AI Agents that leverage large language models (LLMs) to accelerate hardware design.
  • My research interests include deep learning and information theory, Google Scholar.
  • Past work experiences

Education

  • Ph.D. in Electrical and Computer Engineering, Syracuse University, 2009
  • M.S. in Computer Science, Chinese Academy of Science, Institute of Automation, 2005
  • B.S. in Electronic Engineering and Information Science, University of Science and Technology of China, 2002

Selected Research Projects

  • Developing General AI Agents with Gemini Multimodality
    • Leveraged Langfun and Gemini’s multimodal capabilities to build a general-purpose AI agent, achieving SOTA performance on the GAIA benchmark in December 2024. This project demonstrated the effectiveness of Langfun + Gemini for complex reasoning and task completion across diverse domains.
    • Adapted the general-purpose AI agent idea to create a specialized vision-only AI agent for automated proofreading of large-scale 3D neuron reconstructions in mouse brain microscopy datasets on neuroglancer.
  • Applying Deep Learning to Drug Discovery
    • Our publication in the Journal of Medicinal Chemistry, for the first time, discovered a novel small molecule ligand for WDR91 by using affinity-mediated DNA-encoded chemical library selection followed by deep learning. WDR’s unique β-propeller structure makes them attractive targets, but most human WDRs are unexplored compared to other major drug target families. The discovery of a drug-like small molecule and its covalent analog compounds will soon enable researchers to identify a WDR91 drug candidate.
    • Talk
  • Studying secure communication from information theoretic perspective

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