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This article provides a brief overview of my personal background, allowing you to better understand my educational and research background.

I am currently with the Microarchitecture and Integrated Circuit Laboratory (MICL), in School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB).

I am leading the Swarm Intelligence and Collabrative Computing (SICC) Group, where our research centers on swarm learning, focusing on collaborative decision-making, robustness, and secure learning within distributed systems. Our work spans two primary domains: robotics and materials big-data.

In swarm robotics, we investigate how multi-agent systems can autonomously and cooperatively perform complex tasks in uncertain environments, leveraging wireless localization, reinforcement learning, and quantum machine learning. Meanwhile, in materials science, we explore collaborative computation and secure data handling for large-scale materials datasets.

The common thread between these domains is their foundation in multi-agent systems, which allows us to apply unified theoretical approaches across diverse applications. Part of our research aims to enhance robustness and security in swarm-based decision-making and distributed learning systems.

Keywords: Swarm Robotics, Multi-Agent System, Reinforcement Learning, Localization and Navigation, Quantum Machine Learning, Blockchain, Federated Learning, Distributed Security, Materials Big-data, and AI4Science.

Employments

  • Visiting Scholar @ CISS
    • 2024.03 - Present
    • Collaborator: Prof. Chau Yuen
    • Nanyang Technological University (NTU)
  • Visiting Scholar @ IRIDIA
  • Associate Professor @ USTB
    • 2021.07 - Present
    • University of Science and Technology Beijing
  • Associate Professor (Specially Appointed)
    • 2019.05 - 2021.06
    • University of Science and Technology Beijing

Education

  • Ph.D. in Computer Science
    • 2016.08 - 2019.01
    • University of Science and Technology Beijing
    • Thesis: Towards Human Motion Tracking: Study on Performance Evaluation and Algorithms for IMU/TOA Fusion
  • MEng in Computer Science
    • 2012.08 - 2015.01
    • University of Science and Technology Beijing
    • Thesis: Height Dependent TOA Ranging Error Model For Near Ground Localization Applications
  • BSc in Computer Science
    • 2008.09 - 2012.06
    • University of Science and Technology Beijing
    • Thesis: Design and Development of Android-based Conputing Engine for Indoor Geolocation system

Awards

  • China National Postdoctoral Program for Innovative Talents awarded by Ministry of Human Resources and Social Security : I obtained a talent funding program focusing on the research of Collaborative Localization and Navigation for Emergency Rescue in Bilnd Environments.

  • CWSN2021 Outstanding Paper Award awarded by China Computer Federation (CCF): My paper, Reward-Filtering-based Credit Assignment for Multi-agent Deep Reinforcement Learning, was honored by the China Computer Federation (CCF) for the Outstanding Paper Award in the 15th China Conference on In- ternet of Things (Wireless Sensor Network). My work introduces a credit assignment algorithm based on reward filtering, integrating Bayesian filter- ing with reinforment learning methods. We propose a multi-agent deep re- inforcement learning framework based on reward filtering (RFMADRL) and validate it successfully in the cooperative navigation environment provided by Open AI.

  • Excellent Doctoral Dissertation awarded by University of Science & Technology Beijing: I was honored by the University of Science & Technology Beijing for the Excellent Doctoral Dissertation.

  • Science and Technology Innovation Award awarded by China Fire Protection Association: I devote myself to the navigation and positioning for emergency rescue applications. Using TOA, our group developed a searching and rescue device and a supporting command system for first responders.

Social Positions