General Information

Full Name Yihua Zhang
Date of Birth 9th July 1997
Languages Chinese, English, German


  • 2022 - now
    Ph.D. Student in Computer Science
    Michigan State University, USA
    • Trustworthy Machine Learning
      • Model Robustness (Adversarial Robustness, Backdoor Attacks, Out-of-Distribution, etc.)
      • Model Fairness
      • Machine Unlearning (Copyright infringement, Harmful Content Removal)
    • Scalable Machine Learning
      • Efficient Model (Model Pruning, Mixture-of-Expert, On-Device Training)
      • Efficient Data (Data Distillation, Coreset Selection)
    • Foundation Algorithm Development
      • Bi-Level Optimization
      • Zeroth-Order Optimization
      • Invariant Risk Minimization
      • Distribution Machine Learning
  • 2015-2019
    B.Eng. in Mechanical Engineering
    Huazhong University of Science and Technology, China

Internship Experience

  • 11/2023-08/2024
    Research Scientist Intern
    Cisco Research
    • Investigate efficient and effective machine unlearning algorithms for foundation models, including Large Language Models (LLMs), Diffusion Models (DMs), and Mixture-of-Experts (MoEs).
  • 05/2023-08/2023
    Applied Scientist Intern
    Amazon AWS
    • Investigate the in-context learning for vision generative models, including its design, training, and generalization ability.
  • 01/2021-08/2021
    Research Internship
    JD AI Research
    • Develop algorithms to enhance the robustness and the fairness of the AI algorithms, such as facial recognition, ORC, object detection. Implement and release the new designed algorithms to the JD corperation for intern use or as part of the commercial APIs.

Honors and Awards

  • 2024
    • 2024 MLCommons ML and Systems Rising Stars sponsored by Nvidia
  • 2023
    • AAAI 2023 Travel Award
    • NeurIPS Scholar Award
    • NeurIPS Top Reviewer
    • CVPR 2023 Outstanding Reviewer
  • 2022
    • Best Paper Runner-up Awards, UAI 2022
    • NeurIPS Scholar Award
    • NeurIPS Top Reviewer
    • ICML 2022 Travel Grant Award
  • 2017
    • National Scholarship
  • 2016
    • National Scholarship

Professional Services


  • AAAI 2024 Tutorial, Zeroth-Order Machine Learning: Fundamental Principles and Emerging Applications in Foundation Models
  • AAAI 2023 Tutorial, Bi-level Optimization in Machine Learning: Foundations and Applications
  • Talk at INFORMS Annual Meeting 2022, Advancing Algorithmic Foundation of Robust Deep Learning through the Lens of Bi-level Optimization