Hua Tang

Hua Tang

Undergraduate @Industrial Engineering, Shanghai Jiao Tong University

About me

I’m a fourth-year undergraduate student from Shanghai Jiao Tong University (SJTU), majoring in Industrial Engineering(IE) and minoring in Mathematics and Applied Mathematics. I have a strong interest in Trustworthy AI(such as algorithmic fairness, robustness and privacy), as well as machine learning and data mining.

My CV and transcript can be downloaded through these links (CV and Transcript).

My Academic Statement can be downloaded through this line (Academic Statement)

Two current Research Lines:

Exploring the Impact of Data Distribution Properties on Epistemic Model Performance:

  • Ultimate Objective: Attaining a comprehensive understanding of the transitivity between classes’ power within the given data distribution.
  • Current Focus: Investigating the influence of data trends on the formalization of Neural Collapse.
  • Methods: Improved UFM + Adaptive ETF classifier

The difference between data distributions and how it works on the aleatoric model performance

  • Ultimate Goal: Gaining insight into the minimum “information” (what type and what content) of the test data distribution (compared to the training data distribution) which is required for the effective and desirable techniques.
  • Current Focus: Analysis of the differential privacy + fairness
  • Methods: Information-theoretic techniques

Selected Experience

  • June.2023 - Present: Remote Research Intern: Theoretical Analysis on the Trade-off between Accuracy and Fairness, advised by Mengnan Du, Assistant Professor, Department of Data Science, New Jersey Institute of Technology (NJIT). The manuscript titled ‘A Theoretical Approach to Characterize the Accuracy-Fairness Trade-off Pareto Frontier’ with me as the first author can be accessed through this link
  • Jul.2022 - May.2023: Empirical Strategies for High-frequency Quantitative Trading, advised by Tongxin Ren, Assistant Professor, Student Innovation Center, Shanghai Jiao Tong University(SJTU). Our source code now is available at link
  • Mar.2023 - Sept.2023: Skeleton-based Human Motion Quality Assessment via Improved ST-GCN, advised by Yongxiang Li, Associate Professor, Department of Industrial Engineering and Management, Shanghai Jiao Tong University(SJTU).
  • Jun.2022 - Sept.2022: Airline Fleet Allocation, advised by Prof. Yaoming Zhou, Associate Professor, Department of Industrial Engineering and Management, Shanghai Jiao Tong University(SJTU). We won the 1st Prize in the 17th “Dongfeng Nissan Cup” Tsinghua IE Sword National Industrial Engineering Case Study Competition!