About Me

Hua Wei (him/his) is an assistant professor at the School of Computing and Augmented Intelligence (SCAI) in Arizona State University (ASU). He also affiliates with the Lawrence Berkeley National Laboratory.

Before joining ASU, he worked as an Assistant Professor at New Jersey Institute of Technology and a Staff Researcher at Tencent AI Lab. He got his PhD from Pennsylvania State University in 2020 under the supervision of Dr. Zhenhui (Jessie) Li. Before that, he received his master and bachelor degree from Beihang University (BUAA) majoring in Computer Science, working with Prof. Jinpeng Huai and Dr. Tianyu Wo.


I have several positions available for research interns (flexible time) and several fully-funded PhD positions (Spring and Fall 2025) available. If you are interested in working with me, please read this.

Research Interests

Reinforcement Learning, Data Mining, Urban Computing, Human-in-the-loop Computations

News

[12/20/2024] Two papers are accepted by SDM'25. Check them out: CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Traffic, and Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness.

[10/22/2024] Glad to receive Amazon Research Award!

[10/21/2024] Glad to receive support from Arizona DOT!

[10/15/2024] Glad to receive support from TSMC!

[10/05/2024] I’m going to deliver two keynote talks in CIKM’24 at the Workshop of AI Agent for Information Retrieval and the Workshop on Data-Centric AI. See you in Boise, ID!

[09/25/2024] Our paper “RegExplainer: Generating Explanations for Graph Neural Networks in Regression Tasks” has been accepted by NeurIPS’24.

[09/21/2024] I’m going to deliver a keynote talk on “Simulation: Machine learning from it, for it and beyond it” at ITSC 2024.

[07/31/2024] I'll be the session chair for "DM: Mining spatial and/or temporal data" at IJCAI'24 at Jeju, South Korea.

[07/16/2024] Three papers are accepted by CIKM 2024.

[07/10/2024] Our paper "SynTraC: A Synthetic Dataset for Traffic Signal Control from Traffic Monitoring Cameras" is accepted by ITSC 2024.

[05/28/2024] Our paper "CityFlowER: An Efficient and Realistic Traffic Simulator with Embedded Machine Learning Models" is accepted by ECML-PKDD'24 Demo Track. Checkout the demo here.

[05/27/2024] Our paper "Spatial-Temporal PDE Networks for Traffic Flow Forecasting" is accepted by ECML-PKDD'24.

[05/17/2024] Our paper "CoSLight: Co-optimizing Collaborator Selection and Decision-making to Enhance Traffic Signal Control" is accepted by KDD'24.

[05/13/2024] Our paper "Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks" is awarded the Best Paper Runner-up in TrustLOG Workshop@WWW 2024).

[05/01/2024] Our paper "Generating In-Distribution Proxy Graphs for Explainable Graph Neural Networks" is accepted by ICML'24.

[04/16/2024] Our paper "X-Light: Cross-City Traffic Signal Control Using Transformer on Transformer as Meta Multi-Agent Reinforcement Learner" is accepted by IJCAI'24.

[04/07/2024] I'll be giving a keynote on Data Science for Smart Manufacturing and Healthcare Workshop in SDM'24 on "Trustworthy Decision Making in the Real World with Uncertainty Quantification". See you in Houston!

[04/07/2024] Our paper "HumanLight: Incentivizing Ridesharing via Human-centric Deep Reinforcement Learning in Traffic Signal Control" is accepted by Transportation Research Part C: Emerging Technologies.

[02/27/2024] Our paper "eTraM: Event-based Traffic Monitoring Dataset" is accepted by CVPR'24.

[02/27/2024] Our workshop “DCgAA 2024: International Workshop on DL-Hardware Co-Design for Generative AI Acceleration” has been accepted by DAC'24.

[02/07/2024] Congrats to Longchao and Hao for being awarded the ASU SCAI Doctoral Fellowship Award!

[01/17/2024] Our papers Prompt to transfer: Sim-to-real Transfer for Traffic Signal Control with Prompt Learning and Uncertainty Regularized Evidential Regression are selected for Oral Presentations for AAAI 2024. Check them out!

[01/16/2024] We thank OpenAI for providing us with API credits under the Researcher Access program.

[01/16/2024] Our paper "Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks" is accepted to ICLR 2024

[12/09/2023] Four papers are accepted by AAAI'24. See you in Vancouver!

[11/23/2023] RegExplainer is accepted by LoG'23.

[11/10/2023] I'm giving a talk in ASU SCAI AI Day.

[11/03/2023] I'm co-organizing an ARO-sponsored workshop on "Metacognitive AI".

Contacts

Office: BYENG 586, 699 S Mill Ave, Tempe, AZ 85281

Office Phone: +1 602-543-5652

Email: hua.wei [at] asu.edu

You can find more about me at: Google Scholar, Twitter, LinkedIn