About Me

I’m Yaxin Li, a PhD student from the Department of Computer Science and Engineering at Michigan State University. My advisor is Dr. Jiliang Tang, whose research interests focus on Machine Learning on Graph and Trustworty AI.

My research interests focus on trust-worthy deep learning, especially robustness and privacy. My goal is to discover potential harm of AI systems and prevent different types of data from being misused by AI.

Before I joined MSU, I completed my BS (2019) in the Department of Automation at Tsinghua University.

My CV

Recent News

• 09/24 Start an internship at Newsbreak.
• 07/24 One paper about metigate memorization for Diffusion model is accepted by ECCV!
• 05/24 One paper about exploring memorization in Language model is accepted by ACL!

Opensource Projects

DeepRobust: A Platform for Adversarial Attacks and Defenses In AAAI 2021 Repo

Previous Experiences

• 06/24 I’m actively looking for an applied scientist/ machine learning engineer role, I would be really glad if you notify me any job opening or give me a referral!^_^

• 01/24 Find my poster on WACV2024 poster session2 #71

• 10/23 Our paper accepted by WACV2024: Neural Style Protection: Counteracting Unauthorized Neural Style Transfer

• 06/23 Start my internship at BAIDU. Working on LLM privacy problem.

• 08/21 Find the website of our KDD tutorial here: https://sites.google.com/view/kdd21-tutorial-adv-robust/”

• 08/21 Our survey Trustworthy AI: A Computational Perspective is released.

• 05/21 Our paper Elastic Graph Neural Networks got accepted in ICML21.

• 05/21 Our paper To be Robust or to be Fair: Towards Fairness in Adversarial Training got accepted in ICML21.

• 12/20 Our paper Yet Meta Learning Can Adapt Fast, it Can Also Break Easily is accepted by SDM21.

• 10/20 Our demo A Platform for Adversarial Attacks and Defenses is accepted by AAAI21.

• 09/20 Serve as a PC member in AAAI20.

• 08/20 We are honored to give a tutorial about adversarial attack and defense. Find the website of our KDD tutorial here: Intro&Video

• 08/20 Received KDD Student Travel Award and served as a volunteer.

• 07/20 Serve as a volunteer in ICML20.

• 06/20 Serve as a PC member in ICONIP20.

• 05/20 Our tutorial “Adversarial Attacks and Defenses: Frontiers, Advances and Practice” is accepted by KDD20. Looking forward to your attendance!

• 05/20 Check out the technical report of our package: DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses

• 04/20 Find our Pytorch library for attack and defense in Github: https://github.com/DSE-MSU/DeepRobust

• 03/20 Check out our survey: Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study

• 08/19 Join DSE Lab.