News

2024

Apr: A Paper co-authored with Central South University was recognized as a major technological innovation in railway science of China.
Mar: Dr. Wu gave a talk at The Hong Kong University of Science and Technology (Guangzhou). The topic is about the backbone model for multivariate time series forecasting.
Mar: Dr. Wu was selected for the inaugural cohort of the Ministry of Education's initiative to attract outstanding overseas postdoctoral talents. A 900, 000 RMB package.

2023

Dec: Wanlin’s paper “MSGNet: Learning Multi-Scale Inter-Series Correlations for Multivariate Time Series Forecasting” is accepted at AAAI 2024 (Code).
Dec: We've Open-Sourced SUMformer: A Transformer Framework for urban mobility forecasting (Paper, Code).
Dec: Dr. Wu has been promoted to a Senior Member of the IEEE.
Oct: Wang Kun from USTC gives a talk about graph neural network and casality learning in my group.
Aug: Dr. Wu gave a talk at Symposium on Transportation Science and Computation. The topic was about deep learning for spatiotemporal traffic data forecasting.
Aug: We've Open-Sourced FLoss: A Framework to Enhance Various Time Series Prediction Tasks (Paper, Code).
Aug: Prof. Paul Weng from Shanghai Jiao Tong University Introduces Latest RL Research in Wangjiang Rongzhi Lecture Series for us.
Jul: Dr. Wu gave a talk for OmniSky Company. The topic was about large deep learning models and intelligent transportation systems.
Jul: JingGuo's undergraduate thesis has been awarded the Outstanding Undergraduate Thesis Award of Sichuan University.
Jun: A paper entitled "Spatiotemporal Propagation Learning for Network-Wide Flight Delay Prediction." has been accepted for publication in IEEE Transactions on Knowledge and Data Engineering.
May: Qinghong’s paper “Adapting Energy Management Strategies for Hybrid Electric Vehicles in Dynamic Driving Cycles through Recurrent Policy” is accepted at IEEE SMC 2023. The project is supported by Sichuan Province College Students' innovation and entrepreneurship training program
May: Dr. Wu gave a talk at Emerging Engineering forum of SCU. The topic is about TOCC and AI ( slides).
May: Dr. Wu will serve as a Young Editorial Board Member of Data Science and Management (DSM).
Apr: I am delighted to be awarded by Tianfu Emei plan of Sichuan province.
Apr: Chen Xinyu from PolyMtl gives a talk about low-rank matrix and tensor decomposition for spaitotemporal learning in my group.
Jan: Our project “Graph Neural Networks based Aircraft Delay Propagation Modeling” is funded by Science and Technology Department of Sichuan Province.

2022

Dec: Liang Yuxuan from NUS gives a talk about spaitotemporal contrastive learning in my group.
Nov: Code release for our paper "Explainable and Safe Reinforcement Learning for Autonomous Air Mobility".
Nov: Wang Yong from BIT gives a talk about applications of deep reinforcement learning in my group.
Oct: Dingyi from MIT gives a talk about graph neural networks based demand uncertainty idenfication in my group.
Sep: Dr. Wu gives a talk about graph neural networks for traffic data kriging at the MAGIC LAB, Tongji University.
Aug: Dr. Wu gives two talks at the State Key Laboratory of Public Big Data of Guizhou University and the National Engineering Laboratory for Big Data Application.
Aug: One paper is accepted by CICAI 2022.
Aug: I was invited to serve as a Program Committee (PC) Member for the AI for Social Impact track at AAAI-23.
Aug: Our TII paper has been selected to receive the 2022 IEEE Outstanding Paper Award for TII.
Jul: Dr. Wu's research on deep learning for intelligent transportation systems has been awarded by Young Talents Plan of China Association for Science and Technology.
Jul: Dr. Wu gives a talk about machine learning based spatiotemporal analysis for traffic data at the big data mining and analysis in transportation session in 22nd COTA conference.
Jun: Dr. Wu gives a talk about machine learning for spatiotemporal modeling at the School of Mathematical Sciences, University of Electronic Science and Technology of China.
Jun: A paper entitled "Investigation on dynamic strength of 3D-printed continuous ramie fiber reinforced biocomposites at various strain rates using machine learning methods." has been accepted for publication in Polymer Composites.
Jun: I was invited to Early Career Editorial Advisory Board for Advanced Engineering Sciences (Chinese).
Mar: I am delighted to be a research professor (This is the same level as a full professor) at College of Computer Science at Sichuan University.

2021

Sep: A paper entitled "Deep learning-based super-resolution climate simulator-emulator framework for urban heat studies" has been accepted for publication in Geophysical Research Letters.
Sep: I was invited to serve as a Program Committee (PC) Member for the AI for Social Impact track at AAAI-22.
Sep: A paper entitled "A Deep Learning Framework of Autonomous Pilot Agent for Air Traffic Controller Training" has been published in IEEE Transactions on Human-Machine Systems.
Jul: A paper entitled "Rail transit OD-matrix completion via manifold regularized tensor factorization" has been published in IET Intelligent Transport Systems.
Jun: A special issue is launched on "electronic", please contribute your papers! .
Jun: Dr. Wu gives a remote talk for "Tsinghua AIR".
May: A special issue is launched on "Journal of Transportation Engineering and Information(Chinese)", please contribute your papers!
Apr: Dr. Wu gives a remote presentation on deep reinforcement learning for College of Computer Science, Sichuan University.
Feb: We present our work "Inductive Graph Neural Networks for Spatiotemporal Kriging" on AAAI 2021 conference.

2020

Dec: Our paper "Inductive Graph Neural Networks for Spatiotemporal Kriging" has been accepted for presentation at the AAAI-21.
Dec: Dr. Wu gives a remote talk on tensor and its application on traffic data analysis for Shenzeng University with "Dr. Linchao Li's group".
Oct: A paper titled "Non-recurrent Traffic Congestion Detection with a Coupled Scalable Bayesian Robust Tensor Factorization Model" has been accepted by Neurocomputing.
Oct: A paper titled "Understanding and Modeling Urban Mobility Dynamics via Disentangled Representation Learning" has been accepted by T-ITS.
Sep: The hybrid deep learning traffic flow prediction work has been ranked as one of TRC's top 3 most popular articles since 2017.
Aug: Our manuscript entitled "Hybrid electric vehicle energy management with computer vision and deep reinforcement learning" has been accepted for publication in the IEEE Transactions on Industrial Informatics.
Jul: We have shared the slides of Multi-agent Graph Reinforcement Learning on "slideslive".
Jul: Our paper Multi-agent Graph Reinforcement Learning for Connected Automated Driving was accepted for the ICML workshop on AI for Autonomous Driving.
Jul: Code release for our paper "Differential variable speed limits control for freeway recurrent bottlenecks via deep actor-critic algorithm".
Jun: Code release for our paper "Cross type transfer for deep reinforcement learning based hybrid electric vehicle energy management". This project provides several examples on using python to model HEV powertrains.
May: A paper titled "Cross type transfer for deep reinforcement learning based hybrid electric vehicle energy management" has been accepted for publication in the IEEE Transactions on Vehicular Technology.
May: Dr. Wu gives a lecture on deep learning based spatio-temporal modeling for Chengdu Normal University.
May: Two papers have been accepted by IEEE ITSC 2020.
Apr: A paper titled "Differential Variable Speed Limits Control for Freeway Recurrent Bottlenecks via Deep Actor-critic Algorithm" has been accepted for publication in Transportation Research Part C.
MAr: A paper titled "Traffic flow prediction with missing data imputed by tensor completion methods" has been accepted for publication in IEEE Access.
Mar: A paper titled "Rule-interposing deep reinforcement learning based energy management strategy for power-split hybrid electric vehicle" is accepted by journal Energy. The Code is also opensourced.
Jan: I received a Postdoc Funding from the Institute for Data Valorization (IVADO).