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 three years, he has filed over 50 China/U.S. patents and published over 40 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.
[New] Postdoc position available! Very competitive salary and research fund package. Please drop your resume and representative publications to liuh[AT]ust[DOT]hk.
[2023 Fall] Multiple Ph.D. 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! (2022-9-16) One paper was accepted to NeurIPS 2022 about adversarial attack against graph based traffic forecasting models, congrats to my student Fan Liu.
- (2022-9-1) One paper was accepted to ICDM 2022 about knowledge enhanced imitative trajectory generation, congrats to my student Qingyan Zhu who graduated in August, a perfect end of research study.
- (2022-5-19) Three papers were accepted to SIGKDD 2022 about GPU-accelerated deep learning system, multi-agent charging pricing, and talent demand-supply prediction, congrats to my students Weijia Zhang and Zhuoning Guo.
- (2022-5-18) One paper on Reinforced charging station recommendation was accepted to TKDE.
- (2022-5-1) One paper on multi-modal transportation routing was accepted to VLDBJ.
- (2022-2-21) One paper on national-wide public transportation routing was accepted to TKDE.
- (2022-1-29) Two papers on semi-supervised air quality forecasting and graph-grounded conversational recommendation were accepted to TKDE.
- (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!
- Hao Liu, Qian Gao, Jiang Li, Xiaochao Liao, Hao Xiong, Guangxing Chen, Wenlin Wang, Guobao Yang, Zhiwei Zha, Daxiang Dong, Dejing Dou, Haoyi Xiong. JiZhi: A Fast and Cost-Effective Model-As-A-Service System for Web-Scale Online Inference at Baidu. In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2021), Virtual Conference, 2021.
- Hao Liu, Jindong Han, Yanjie Fu, Jingbo Zhou, Xinjiang Lu, Hui Xiong. Multi-Modal Transportation Recommendation with Unified Route Representation Learning. In Proceedings of the VLDB Endowment (VLDB 2021), Copenhagen, Denmark, 2021.
- Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma and Hui Xiong. Polestar: An Intelligent, Efficient and National-Wide Public Transportation Routing Engine. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2020), San Diego, California, 2020.
- Hao Liu, Yongxin Tong, Panpan Zhang, Xinjiang Lu, Jianguo Duan, and Hui Xiong. Hydra: A Personalized and Context-Aware Multi-Modal Transportation Recommendation System. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2019) , Anchorage, Alaska, 2019.
- Hao Liu, Ting Li, Renjun Hu, Yanjie Fu, Jingjing Gu, and Hui Xiong. Joint Representation Learning for Multi-Modal Transportation Recommendation. In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019) , Honolulu, Hawaii, USA, 2019.