Hao Liu received his Ph.D. degree from the Hong Kong University of Science and Technology (HKUST) in 2017. He is currently an assistant professor at the Artificial Intelligence Thrust, HKUST (Guangzhou), and an Affiliated Assistant Professor at the Department of Computer Science and Engineering, HKUST (Clear Water Bay). Dr. Liu’s current research interests include spatiotemporal data mining, graph learning, reinforcement learning, and their applications on urban computing, intelligent transportation, and recommender systems. In the past two years, he has filed over 50 China/U.S. patents and published over 20 research papers at prestigious journals and conferences, such as TKDE, SIGKDD, SIGIR, WebConf, VLDB, AAAI, and IJCAI. For his research on intelligent transportation and urban computing, he was named in Forbes 30 Under 30 China list for science and healthcare 2021.

[2023 Fall] Multiple Ph.D. and M.Phil. positions available! Please feel free to send your resume to liuh[AT]ust[DOT]hk. Experiences of top-tier academic publications, data mining challenge awards, and ICPC awards are strong plus. Perspective students are also highly encouraged to apply to my visiting student positions first. You can have a close look at my research group, and we can also try to find common research interests before you start your Ph.D. career.


  • New! (2022-5-1) One paper on multi-modal transportation routing was accepted to VLDBJ.
  • New! (2022-2-21) One paper on national-wide public transportation routing was accepted to TKDE.
  • New! (2022-1-29) Two papers on semi-supervised air quality forecasting and graph-grounded conversational recommendation were accepted to TKDE.
  • New! (2022-1-29) One paper on data science competition analysis was accepted to TKDD.
  • (2021-12-02) One paper was accepted to AAAI 2022 about long path knowledge reasoning.
  • (2021-09-28) One paper was accepted to NeurIPS 2021 about bi-level optimization.
  • (2021-09-16) I was named in Forbes 30 Under 30 China 2021 list.
  • (2021-05-18) Four papers were accepted to SIGKDD 2021 about web-scale machine learning system, real estate appraisal, talent demand forecasting, and domain-oriented BERT.
  • (2021-01-16) Two papers were accepted to WebConf 2021 about intelligent charging station recommendation and online query-POI matching.
  • (2020-12-02) Four papers were accepted to AAAI 2021 about transportation demand prediction, atmospheric prediction, corporate porfiling, and POI recommendation.
  • (2020-10-21) Our paper Semi-Supervised City-Wide Parking Availability Prediction via Hierarchical Recurrent Graph Neural Network was accepted to TKDE.
  • (2020-10-16) Our paper Multi-Modal Transportation Recommendation with Unified Route Representation Learning was accepted to VLDB 2021 Scalable Data Science track.
Past news * (2020-03-16) Our Cross-City Multi-Modal Recommendation service get online! This service covers over 330 cities in mainland China.
* (2019-08-02) We organized "The KDD Cup 2019 Regular ML Track", Context-Aware Multi-Modal Transportation Recommendation. We attracted over 1700 teams participates.
* (2018-9-01) Our Multi-Modal Transportation Recommendation service get online! Download Baidu Maps and try Zhixing!

Selected Publications