Hao Fang (方 豪)

Master student at SIGS, Tsinghua University, Shenzhen, China

Hao Fang

1-year Master degree candidate

Address: SIGS, Tsinghua University, Shenzhen, Guangdong Province, China

Research Interest: Trustworthy AI, Computer Vision, Gradient Compression

Lab: ITML, SIGS, Tsinghua University

E-mail: fang-h23@mails.tsinghua.edu.cn

Biography

I am a first-year master's student in the ITML lab in the SIGS, Tsinghua University, supervised by Prof.Bin-Chen and Prof.Shu-Tao Xia. I received my B.S. degree in Computer Science and Technology from Harbin Institute of Technology, Shenzhen in 2023. My research interest includes Trustworthy AI, GAN, and Gradient compression.
And I enjoy playing basketball and doing some workouts in my spare time!

Received Honors

Fang has received many honors as follows (but not limited to):

  • Chinese National Scholarship for Undergraduate Students Top 1.5%
  • First class scholarship * 3 Top 5%
  • GongJin scholarship Top 1.85%
  • Fang Binxing Scholarship
  • Progress of star in SaiWei Scholarship
  • School-level Excellent students * 2
  • School-level Excellent League Member * 2
  • Excellent Student Model 0.3%
  • Outstanding Student Award for Scientific Research Commendation of Guangdong Provincial Key Laboratory
  • Provincial First Prize in the Blue Bridge Cup Program Competition
  • Honorable Mention of the American College Students' Mathematical Modeling Competition
  • The second prize of the 17th National University Student Smart Car Competition in China Southern District
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    Publication

  • Hao Fang, Bin Chen, Xuan Wang, Zhi Wang, Shu-Tao Xia, GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization, International Conference on Computer Vision 2023 (ICCV-23), accepted. (CCF A, TsinghuaCS: A). paper, code.

    • Project Experimence

  • 2019-2020 WeChat applet development project for campus market trading.

    • As the team leader, he is mainly responsible for the front-end development and interface building of the WeChat applet.

  • 2021.12-2022.8 The federated learning project cooperated by ICES Lab and China Unicom Payment Corporation.

    • In the early stage, he was responsible for the research and learning of homomorphic encryption algorithms and the research of federated learning algorithms such as logical regression under semi-homomorphic encryption. In the middle stage, he is responsible for the deployment of the stand-alone FATE framework and the operation and implementation of the FATE federated learning algorithm. In the later stage, he is responsible for the cross-version transplant of vertical federated model merge, and writing the report for final check. He has done experiments and written technical documents many times, which have been highly praised by teachers.

  • 2022.3-2022.7 Internship in the ITML lab of Tsinghua University.

    • He mainly studies federated/distributed gradient compression algorithms and gradient-based leakage attacks. During this period, he assists his fellow to finish an article and contribute it to INFOCOM.

    Skills

  • C language programming
  • Python/Pytorch programming
  • Federated learning
  • Application of GAN model
  • Distributed gradient compression
  • Machine learning algorithm
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