CV

Education

• Ph.D in Electrical Engineering, University of Minnesota, Nov. 2023.
• M.S. in Electrical Engineering, University of Minnesota, May 2022.
• B.S. in Automation, University of Science and Technology of China, July 2018.

Research Topics

• Theoretical understanding and practical implementation of differential privacy for large-scale optimization.
• Theoretical aspects of distributed optimization, algorithm design in decentralized optimization, and federated learning.
• Photovoltaic power generation, Inverter modeling, Smart power grid control

Work experience

• Dec. 2023 - Present: Postdoc in ISE
  • Viterbi School of Engineering, University of Southern California
  • Advisor: Prof. Meisam Razaviyayn
• May 2023 - Nov. 2023: Applied Scientist Intern
  • Amazon Web Services, Inc.
  • Duties included:
    • Research on differentially private training LLMs.
    • Develop differentially private large-scale training algorithms for foundation models.
  • Mentor: Dr. Woody Bu, Prof. Mingyi Hong; Manager: Dr. Kaixiang Lin
• May 2022 - Sept. 2022: Research Intern
  • IBM-MIT Watson AI Lab.
  • Duties included:
    • Research on federated learning on graph data and graph neural networks.
    • Develop federated learning algorithm for feature distributed graph data.
    • Research on Bayesian Optimization with unknown constraints.
  • Supervisor: Dr. Jie Chen
• Fall 2018 - Fall 2023: Graduate Research Assistant
  • Department of Electrical and Computer Engineering, University of Minnesota
  • Duties included:
    • Research on distributed algorithms, including federated learning and decentralized optimization.
    • Develop distributed machine learning systems for training neural networks using Python with TensorFlow/Pytorch and MPI.
    • Parallel programming using CUDA to solve large-scale distributed sparse precision estimation problems.
    • Research on distributed inverters and power grid control and implementation of gradient descent type algorithm on embedded microcontrollers.
  • Supervisor: Prof. Mingyi Hong, Prof. Sairaj Dhople
• May 2020 - Sept. 2020: Research Intern
  • Alibaba Group (U.S.) Inc.
  • Duties included:
    • Research on large-scale federated learning systems.
    • Develop a federated learning system for training large-scale neural networks using Python with Pytorch.
    • Parallel programming using multi-process multi-thread method to solve large-scale distributed communication problems.
  • Supervisor: Prof. Kun Yuan, Prof. Wotao Yin
• Spring 2017- Summer 2018: Undergraduate Research Assistant
  • Department of Automation, University of Science and Technology of China
  • Duties included:
    • Research in embedded machine learning and visual tracking algorithms for multi-UAV systems.
    • Develop embedded controllers for UAVs with real-time visual feedback.
  • Supervisor: Prof. Qing Ling

Service

• Journal Review
  • IEEE Transactions on Signal Processing
  • IEEE Transactions on Communications
  • IEEE Transactions on Control of Network Systems
  • IEEE Transactions on Energy Conversion
  • IEEE Transactions on Intelligent Transportation Systems
  • IEEE Transactions on Power Systems
  • IEEE Open Access Journal of Power and Energy
  • INFORMS Journal on Computing
  • Journal of Intelligent Manufacturing
  • Journal of Systems Architecture
  • Journal of Machine Learning Research
  • Transactions on Machine Learning Research
• Conference Review
  • Conference on Neural Information Processing Systems (NeurIPS)
  • International Conference on Machine Learning (ICML)
  • International Conference on Machine Learning (ICLR)
  • AAAI Conference on Artificial Intelligence (AAAI)
  • International Conference on Artificial Intelligence and Statistics (AISTATS)
  • Conference on Uncertainty in Artificial Intelligence (UAI)
  • Annual Conference of the IEEE Industrial Electronics Society (IECON)

Skills

• Programming: C/C++, Python, MATLAB, JAVA, Oracle
• Experienced Packages: OpenCV, CUDA, TensorFlow, PyTorch, MPI
• Language: Chinese, English, Japanese