Hua Wei (him/his) is an assistant professor at the School of Computing and Augmented Intelligence (SCAI) in Arizona State University (ASU). His research is mainly focused on machine learning and data mining.

Before joining ASU, he worked as an Assistant Professor at the New Jersey Institute of Technology and as 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. He received his master and bachelor degree from Beihang University (BUAA) majoring in Computer Science, working with Prof. Jinpeng Huai and Dr. Tianyu Wo.

Research Interests

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

Prospective Students

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.

News

[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 give 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, April 18-20!

[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.

[11/03/2023] Dr. Wei co-organizing an ARO-sponsored workshop on “Metacognitive AI”.

[10/03/2023] Our paper “LibSignal: An Open Library for Traffic Signal Control” is accepted by Machine Learning journal by Springer.

[09/03/2023] Our paper “Uncertainty-aware Traffic Prediction under Missing Data” is accepted to ICDM 2023.

[08/15/2023] Our survey paper on Transportation Safety is accepted by MDPI Designs journal.

[07/11/2023] Our paper “Rethinking Sentiment Analysis under Uncertainty” is accepted to CIKM 2023.

[07/11/2023] Two papers are accepted to CDC 2023.

[06/05/2023] Our paper “FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph” is accepted to ECML-PKDD 2023!

[05/26/2023] Our paper “Sim2Real Transfer for Traffic Signal Control” is accepted to IEEE CASE 2023! Congrats to Longchao and Hao!

[05/16/2023] Our paper “MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation” is accepted to KDD 2023! Congrats to Jiaxing!

[04/19/2023] Our paper “Reinforcement Learning Approaches for Traffic Signal Control under Missing Data” is accepted to IJCAI 2023! Congrats to Hao!

[04/01/2023] Our paper “Learning to Calibrate Hybrid Hyperparameters: a Study on Traffic Simulation” is accepted to SIGSIM-PADS’23. See you in Florida!

[03/22/2023] Our tutorial of “Cross-simulator Datasets and Evaluations for Traffic Control Policies” is accepted to IEEE-ITSC 2023. See you in Spain!