Han Xu's Website

Han Xu

Tenure-Track Assistant Professor (From Fall 2024)

Department of Electrical and Computer Engineering

The University of Arizona

Publications | Teaching | Talks and Tutorials | Google Scholar | CV

About Me

I obtained my PhD from the Department of Computer Science and Engineering, at Michigan State University. I am fortunately advised by Dr. Jiliang Tang. Before joining MSU, I received my master degree in Statistics from University of Michigan, Ann Arbor and my bachelor degree in Mathematics from Nankai University, China.

I have a broad research interests in Trustworthy ML/AI, including robustness, fairness, privacy and copyright issues, as well as the related problems in real-world applications, such as images, graph data, text data and financial data. Besides, I have a growing research interest in studying the trustworthy problems about generative models, including Large Language Models (LLMs) and Diffusion Models (DMs).

Group Members

- Yang Nan, PhD student, University of Arizona, from 2024
  Fall 2024, Yang is awarded Herbold 2 Scholarship from University of Arizona.
- Jiahao Wang, PhD student, University of Arizona, from Fall 2025
  Fall 2025, Jiahao is awarded EDFP Fellowship from the Engineering School of University of Arizona.
- Qihao Wen, PhD student, University of Arizona, from Fall 2025

News

08/2025 Our group has two papers accepted by EMNLP 2025.
06/2025 I am selected as an runner-up for INNS 2024 Doctoral Dissertation Award
04/2025 I give an invited talk at Eller College of Management of University of Arizona.
03/2025 My incoming student Jiahao Wang received EDFP fellowship. It is a very prestigious scholarship!
02/2025 Our paper is accepted by NACCL 2025.
01/2025 I will teach Principles of AI for this semester which is about search algorithms and symbolic reasoning.
11/2024 Our paper is accepted by TMLR 2025.
09/2024 Our paper is accepted by NeurIPS 2024.
09/2024 My student Yang Nan is awarded Herbold 2 Scholarship. It is a very prestigious scholarship!
09/2024 Two papers are accepted by EMNLP 2024.
08/2024 Our paper is accepted by ECCV 2024.
07/2024 Two papers are accepted by ACL 2024.
03/2024 Our paper is accepted by NACCL 2024
03/2024 I receive the Outstanding Graduate Student award from Department of Computer Science and Engineering at MSU.
01/2024 Our paper Sharpness-Aware Data Poisoning Attack is accepted by ICLR 2024 as spotlight (top 5%).
10/2023 Our paper is accepted by WACV 2024.
10/2023 I design a short-term PhD course about Trustworthy AI, and deliver this course at Aalborg University, Denmark.
09/2023 We build a dataset "HC_Var" (see in HuggingFace), for ChatGPT generated text detection.
05/2023 Our paper about the memorization of adversarial robust models is accepted by KDD 2023.
05/2023 Our paper about categorical attacks and defenses is accepted by ICML 2023.
01/2023 Our paper about unlearnable examples is accepted by ICLR 2023.
01/2023 Our paper about GNN's robustness and explainability is accepted by ICDE 2023.

Older News

12/2022 I collaborate with Dr. Wenqi Fan to write a survey paper about trustworthy AI in recommender systems.
09/2022 A paper about imbalanced adversarial training collaborated with Wentao Wang (the student I mentor) is accepted by ICDM 2022.
08/2022 I give a short talk about "Fairness in Adversarial Robust DNNs" as a Junior Researcher Spotlight in KDD 2022, Washington DC.
08/2022 We organize and present in KDD 2022 tutorial about adversarial attacks and defenses. Compared to previous two virtual tutorials, we finally hold our tutorial in-person in Washington DC.
06/2022 I start my internship in VISA Research, under supervision of Menghai Pan. I learn a lot about trustworthy AI, such as anomaly detection, in industry.
09/2021 Our collaborated paper about robust GNN models is published in NeurIPS 2022.
08/2021 We organize and present in KDD 2021 tutorial (virtually) about adversarial attacks and defenses.
04/2021 My paper about fairness in adversarial robust models is published in ICML 2021. I am so grateful for the help from my mentor and advisor Xiaorui Liu and Jiliang Tang.
12/2020 My paper about adversarial attacks against meta learning is published in SDM 2021. It is my first accepted paper.
10/2020 Our repository DeepRobust is accepted by AAAI 2021 as a demo.
08/2020 I organize and present the tutorial in KDD 2020 (virtually) about adversarial attacks and defenses.
07/2020 I attend KDD Cup Competition about adversarial attacks on graph data. We are top 10 winner!
03/2020 We release our first version of DeepRobust. We build this python platform to facilitate the researches about attacks and defenses.
03/2020 I start "working from home" due to pandemic.
12/2019 I pass my qualifying exam.
11/2019 My survey paper is published in International Journal of Automation and Computing.
06/2019 I write a survey paper about adversarial attacks and defenses to summarize the papers I read.
05/2019 I attend SDM Doctoral Forum in Calgary, Canada. I present my research about adversarial training against spatial attacks.
01/2019 Working on my first research project about adversarial training against spatially transformed adversarial attacks.
08/2018 I start my PhD Journey. Read papers of adversarial attacks and defenses. Learning a lot from reading papers.