Dear friends, nice to meet you!
I am Jiawei Xue and joined Alibaba Group as a Senior Algorithm Engineer in Sept. 2024. I earned a Ph.D. (2024) and Master’s degree (2020) from Purdue University, and a Bachelor’s degree (2018) from Tsinghua University. My research directions include recommendation, machine learning, urban science, and transportation engineering.
Please find my CV (January 2023), Google Scholar, ResearchGate, LinkedIn.
[Nov. 20, 2024] Our work from the Purdue-Yahoo Japan project, Predicting Individual Irregular Mobility via Web Search-Driven Bipartite Graph Neural Networks, has been published on IEEE Transactions on Knowledge and Data Engineering. Congratulations to all collaborators: Prof. Taka, Dr. Kota, Prof. Ma, and Prof. Ukkusuri.
[Sept. 28, 2024] Our paper, An Agent-based Model of Post-disaster Recovery in Multilayer Socio-physical Networks, has been accepted for publication on Sustainable Cities and Society. Congratulations to all collaborators: Dr. Park, Dr. Mondal, Dr. Reia, Dr. Yao, and Prof. Ukkusuri.
[June 1, 2024] Our study, Network Macroscopic Fundamental Diagram-Informed Graph Learning for Traffic State Imputation, has been accepted for poster presentation at ISTTT25 and publication on Transportation Research Part B: Methodological. Sincere thanks to all collaborators: Eunhan, Prof. Feng, and Prof. Ukkusuri.
[May 31, 2024] I am deeply honored to receive today the Best Student Speaker Award at Purdue’s Institute of Transportation Engineers (ITE) seminars for the 2023 Fall semester. Thanks to Professors and students from Purdue CE for their participation in the seminar!
[May 24, 2024] Our paper A Physics-Informed Machine Learning for Generalized Bathtub Model in Large-Scale Urban Networks was published on Transportation Research Part C: Emerging Technologies. Congratulations to all collaborators: Eunhan, Prof. Leclercq, and Prof. Ukkusuri!
[April 2, 2024] I successfully defended my doctoral dissertation entitled Physics-informed Graph Learning in Urban Traffic Networks! I am deeply honored to have been guided by Prof. Satish V. Ukkusuri (Purdue CE), Prof. Yiheng Feng (Purdue CE), Prof. Yexiang Xue (Purdue CS), and Prof. Vijay Gupta (Purdue ECE)!
[Jan. 17, 2024] I am pleased to present our research on graph learning in urban networks to colleagues at Senseable City Lab at Massachusetts Institute of Technology and DitecT Lab at Columbia University.
[Jan. 14, 2024] Our paper METS-R SIM: A Simulator for Multi-modal Energy-optimal Trip Scheduling in Real-time with Shared Autonomous Electric Vehicles was accepted by Simulation Modelling Practice and Theory. This is a city-wide, high-resolution (vehicle level and 0.3 seconds per tick) multi-modal (taxis and buses) traffic simulator. Congratulations to project leaders Zengxiang Lei, Dr. Xinwu Qian, Prof. Ukkusuri, and other colleagues. Please find our codes at https://github.com/umnilab/METS-R_SIM.
[Sept. 29, 2023] Three papers were accepted to present at the Transportation Research Board 103rd Annual Meeting in Washington, DC (TRB-24). Congratulations to colleagues and Prof. Ukkusuri!
[Aug. 6, 2023] Our study, Predicting Individual Irregular Mobility via Web Search-Driven Bipartite Graph Neural Networks, received the Best Poster Award (1 out of 18) at the First Research Summit of Urban Science in Beijing on August 5-6, 2023. Sincere thanks to all collaborators: Dr. Taka, Dr. Kota, Prof. Ma, and Prof. Ukkusuri.
[June 27, 2023] I am delighted to join as a research intern at the Institute for AI Industry Research, Tsinghua University since July 2023.
[April 27, 2023] I am pleased to pass the preliminary examination for my doctoral dissertation titled Physic-driven Graph Learning in Urban Networks. I express my gratitude to the esteemed committee members: Prof. Satish V. Ukkusuri, Prof. Yiheng Feng, Prof. Yexiang Xue, and Prof. Vijay Gupta!
[March 22, 2023] We present our study under Research Case of Location Information Obtained from Smartphones hosted by Yahoo! JAPAN R&D!
[Oct. 22, 2022] I accomplished 21.1 km with 1:43:56 (PB) in the 2022 Purdue Boilermaker Half-marathon in West Lafayette. Thanks for my passion for running and consistent effort! Hope colleagues can enjoy sports and maintain a healthy life!
[Oct. 1, 2022] Our paper Supporting Post-disaster Recovery with Agent-based Modeling on Multilayer Social-physical Networks was accepted to present at the Transportation Research Board 102nd Annual Meeting in Washington, DC (TRB-23). See you in D.C. next January!
[Sept. 24, 2022] Our paper Online Eco-routing for Electric Vehicles using Combinatorial Multi-armed Bandit with Estimated Covariance was online at Transportation Research Part D: Transport and Environment.
[August 17, 2022] I gave two talks titled Artificial Intelligence in Urban Science Discovery: Graph Neural Networks and Optimization in Emerging Transportation Technologies: Adaptive Buses, Crowd-shipping Logistics at Chang’ An University, China.
[July 2022] Our paper Demand-adaptive Route Planning and Scheduling for Urban Hub-based High-capacity Mobility-on-demand Services was presented as a poster at the 24th International Symposium on Transportation and Traffic Theory (ISTTT-24), Beijing, July 24 to 26, 2022.
[June 20, 2022] I gave a talk titled Harness Graph Neural Networks to Empower Urban Science Research (click to download the slide) at China Transportation Institute, Tongji University, China. We had a fruitful discussion and I thanked Dr. Yuntao Guo to organize the talk.
[May 19, 2022] Our paper Multiwave COVID-19 Prediction from Social Awareness using Web Search and Mobility Data was accepted by the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD-22). Acceptance Rate: 25.9% (195/753). Oral Presentation.
[Mar. 23, 2022] Our paper Quantifying the Spatial Homogeneity of Urban Road Networks via Graph Neural Networks was published on Nature Machine Intelligence (2023 IF: 18.8) and was selected as the cover paper of Volume 4 Issue 3, March 2022. Besides, this paper was reported by Nature Computational Science, Tech Xplore, and Peking University News.
[Jan. 10, 2022] We presented A Spatial Partitioning Algorithm of Urban Road Networks Based on Percolation Curves at the Transportation Research Board 101st Annual Meeting in Washington, DC (TRB-22).
[Oct. 25, 2021] Our two papers ADDS-EVS: An Agent-based Deployment Decision-support System for Electric Vehicle Services and How Information Heterogeneity Influences Traffic Congestion during Hurricane Evacuation were presented at the 2021 IEEE Intelligent Transportation Systems Conference (ITSC-21).
[June 30, 2021] We presented Braess’s Paradox in Scale-free Networks at the 8th International Symposium on Dynamic Traffic Assignment (DTA-21).
[May 1, 2021] Our paper Designing Pricing and Compensation Schemes by Integrating Matching and Routing Models for Crowd-shipping Systems was published on Transportation Research Part E: Logistics and Transportation Review.
[Oct. 27, 2020] Our paper Online Energy-optimal Routing for Electric Vehicles with Combinatorial Multi-arm Semi-Bandit was presented at the 2020 IEEE Intelligent Transportation Systems Conference (ITSC-20).
[Apr. 14, 2020] I completed my master thesis defense titled Structural and Dynamic Models for Complex Road Networks in Purdue University. I thank committee members: Dr. Satish V. Ukkusuri, Dr. Shreyas Sundaram, and Dr. P. Suresh C. Rao, for their guidance.
[Jan. 28, 2020] Our paper Impact of Transportation Network Companies on Urban Congestion: Evidence from Large-scale Trajectory Data was published on Sustainable Cities and Society.
[Oct. 27, 2019] Our paper Stationary Spatial Charging Demand Distribution for Commercial Electric Vehicles in Urban Area was presented at the 2019 IEEE Intelligent Transportation Systems Conference (ITSC-19).