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Zheng Wang
Principal Researcher & Huawei TopMinds
Huawei Singapore Research Center
Office: The Metropolis Tower 1, North Buona Vista Drive, Singapore 138589
Email: wangzheng155@huawei.com, zheng011@e.ntu.edu.sg
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Biography
I am currently a Principal Researcher and Huawei TopMinds at Huawei Singapore Research Center. Prior to that,
I received my PhD degree from the School of Computer Science and Engineering, Nanyang Technological University in 2023, advised by Prof. Cheng Long and Prof. Gao Cong.
I was a recipient of Honourable Mention for Outstanding PhD Thesis Award, WAIC Yunfan Award, Google PhD Fellowship, and AISG PhD Fellowship.
I received my Master's degree from the Department of Computer Science, the University of Hong Kong in 2018, and Bachelor's degree from the School of Computer Science and Technology (Elite Class), Shandong University in 2016.
Research Interest
My research interests are broadly in data management, data mining and deep learning.
My current topics are summarized as follows:
- Large language models, e.g., retrieval-augmented generation (ACL'24, EMNLP'24a), multimodality (WWW'24, EMNLP'24b);
- Deep learning for data management, e.g., trajectory similarity and search (TKDE'22, PVLDB'20, KDD'19),
trajectory simplification
(ICDE'24, ICDE'21, KDD'21), learned index (SIGMOD'23, PVLDB'23);
- Spatio-temporal data mining, e.g., intelligent transportation (ICDE'23), sports data analytics (TKDD'24, SDM'22),
human mobility (BigData'22), urban computing (KDD'23, WWW'23, ICML'23);
- Graph algorithms, e.g., community search (TKDE'18), bipartite graph matching (AAAI'17);
- I have also studied autonomous driving (IEEE IV'20), natural language processing (WWW'21, ACL'21).
If you are interested in working with me as a research intern on large language/multimodal models, please contact me.
Experience
- Huawei Singapore Research Center
Principal Researcher and Huawei TopMinds, September 2022 - Present
- Joint NTU-WeBank Research Center on Fintech, Nanyang Technological University
Research Associate, August 2020 - July 2021
Advisors: Prof. Cheng Long and Prof. Gao Cong
- Data Management and Analytics Lab, Nanyang Technological University
Research Associate, May 2018 - July 2020
Advisors: Prof. Cheng Long and Prof. Gao Cong
- Intelligent Driving Group, Baidu
Algorithm Engineer, Nov 2017 - May 2018
- System Group, The Chinese University of Hong Kong
Research Intern, Jun 2017 - Nov 2017
Advisors: Prof. Michael R. Lyu
- Database Group, The University of Hong Kong
Thesis: Continuous Spatial-Aware Community Search, Jan 2017 - Nov 2017
Advisors: Prof. Reynold C.K. Cheng
- Institute of Computing Technology, University of Chinese Academy of Science
Visiting Student, Sep 2015 - Apr 2016
Advisors: Dr. Xiaoming Sun
- Graphics Group, The University of Hong Kong
Research Intern, Jul 2015 - Aug 2015
Advisors: Prof. Wenping Wang
- Interdisciplinary Research Center, Shandong University
Research Assistant, Sep 2014 - Jun 2015
Advisors: Prof. Baoquan Chen
- ACM-ICPC Lab, Shandong University
Team Member, May 2013 - Jun 2014
Selected Publications Full list of publications: [Google Scholar][DBLP] (* indicates that Zheng is the co-first author, # indicates that Zheng is the corresponding author)
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Crafting Personalized Agents through Retrieval-Augmented Generation on Editable Memory Graphs [Paper][Slides]
Zheng Wang, Zhongyang Li, Zeren Jiang, Dandan Tu, Wei Shi
EMNLP 2024 (Main Conference, Long Paper)
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Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting [Paper]
Chen Cai*, Zheng Wang*, Jianjun Gao, Wenyang Liu, Ye Lu, Runzhong Zhang, Kim-Hui Yap
EMNLP 2024 (Main Conference, Long Paper)
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M-RAG: Reinforcing Large Language Model Performance through Retrieval-Augmented Generation with Multiple Partitions [Paper][Slides]
Zheng Wang, Shu Xian Teo, Jieer Ouyang, Yongjun Xu, Wei Shi
ACL 2024 (Main Conference, Long Paper)
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Multimodal Query Suggestion with Multi-Agent Reinforcement Learning from Human Feedback [Paper][Slides][Media]
Zheng Wang, Bingzheng Gan, Wei Shi
WWW 2024 (Oral)
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Collectively Simplifying Trajectories in a Database: A Query Accuracy Driven Approach [Paper][Technical Report][Code]
Zheng Wang, Cheng Long, Gao Cong, Christian S. Jensen
ICDE 2024 (Oral, Directly accepted without revision)
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Billiards Sports Analytics: Datasets and Tasks [Paper]
Qianru Zhang*, Zheng Wang*, Cheng Long, Siu-Ming Yiu
TKDD 2024
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The RLR-Tree: A Reinforcement Learning Based R-Tree for Spatial Data [Paper][Code]
Tu Gu, Kaiyu Feng, Gao Cong, Cheng Long, Zheng Wang, Sheng Wang
SIGMOD 2023 (Oral)
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Towards Designing and Learning Piecewise Space-Filling Curves [Paper][Code]
Jiangneng Li, Zheng Wang, Gao Cong, Cheng Long, Han Mao Kiah, Bin Cui
PVLDB 2023 (Oral)
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Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning [Paper][Technical Report][Code]
Qianru Zhang*, Zheng Wang*, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi
ICDE 2023 (Oral)
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Urban Region Representation Learning with OpenStreetMap Building Footprints [Paper][Code]
Yi Li, Weiming Huang, Gao Cong, Hao Wang, Zheng Wang
KDD 2023 (Oral, Acceptance Rate: 313/1416 = 22.1%)
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Automated Spatio-Temporal Graph Contrastive Learning [Paper][Code]
Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Zhonghang Li, Siu-Ming Yiu
WWW 2023 (Oral)
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Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation [Paper][Code]
Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Siu-Ming Yiu, Ruihua Han
ICML 2023
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On Predicting and Generating a Good Break Shot in Billiards Sports [Paper][Appendix][Code&Dataset]
Qianru Zhang*, Zheng Wang*, Cheng Long, Siu-Ming Yiu
SDM 2022 (Oral)
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On Inferring User Socioeconomic Status with Mobility Records [Paper][Slides][Code][Video]
Zheng Wang, Mingrui Liu, Cheng Long, Qianru Zhang, Jiangneng Li, Chunyan Miao
BigData 2022 (Oral)
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Similar Sports Play Retrieval with Deep Reinforcement Learning [Paper][Slides][Code]
Zheng Wang, Cheng Long, Gao Cong
TKDE 2022
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Trajectory Simplification with Reinforcement Learning [Paper][Technical Report][Slides][Code][Video]
Zheng Wang, Cheng Long, Gao Cong
ICDE 2021 (Oral)
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Error-Bounded Online Trajectory Simplification with Multi-Agent Reinforcement Learning [Paper][Slides][Code][Video]
Zheng Wang, Cheng Long, Gao Cong, Qianru Zhang
KDD 2021 (Oral, Acceptance Rate: 238/1541 = 15.4%)
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Effective Named Entity Recognition with Boundary-aware Bidirectional Neural Networks [Paper]
Fei Li, Zheng Wang#, Siu Cheung Hui, Lejian Liao, Dandan Song, Jing Xu
WWW 2021 (Oral)
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Modularized Interaction Network for Named Entity Recognition [Paper]
Fei Li, Zheng Wang#, Siu Cheung Hui, Lejian Liao, Dandan Song, Jing Xu, Guoxiu He, Meihuizi Jia
ACL 2021 (Main Conference, Long Paper, Oral)
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Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning [Paper][Technical Report][Slides][Code][Video]
Zheng Wang, Cheng Long, Gao Cong, Yiding Liu
PVLDB 2020 (Oral)
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Interaction-aware Kalman Neural Networks for Trajectory Prediction [Paper]
Ce Ju*, Zheng Wang*, Cheng Long, Xiaoyu Zhang, Dong Eui Chang
IEEE IV 2020 (Oral)
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Effective and Efficient Sports Play Retrieval with Deep Representation Learning [Paper][Slides][Code][Video]
Zheng Wang, Cheng Long, Gao Cong, Ce Ju
KDD 2019 (Oral, Acceptance Rate: 110/1200 = 9.2%)
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On Spatial-Aware Community Search [Paper]
Yixiang Fang, Zheng Wang, Reynold Cheng, Xiaodong Li, Siqiang Luo, Jiafeng Hu, Xiaojun Chen
TKDE 2018
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Efficient Delivery Policy to Minimize User Traffic Consumption in Guaranteed Advertising [Paper]
Jia Zhang, Zheng Wang, Qian Li, Jialin Zhang, Yanyan Lan, Qiang Li, Xiaoming Sun
AAAI 2017
Academia Services
- Lead Organizer, Workshop on Information Seeking with Big Models
- Lead Organizer, Workshop on Large Generative Models Meet Multimodal Applications
- Session Chair: VLDB 2023, ICDE 2023-2024, CIKM 2022, SDM 2022
- Conference PC Member
- 2024: SIGMOD (Reproducibility), NeurIPS, WWW, EMNLP, ECCV, CIKM, SDM, MDM, BigData, DASFAA
- 2023: SIGMOD (Reproducibility), KDD, NeurIPS, CIKM, DASFAA
- 2022: KDD, OSDI (Artifact Evaluation), ATC (Artifact Evaluation), NeurIPS, CIKM
- 2021: NeurIPS, AAAI
- Journal Reviewer
- Selected External Reviewer
- SIGMOD, VLDB, ICDE, KDD, NeurIPS, AAAI, IJCAI, CIKM, ICDM, EMNLP
Teaching
- Introduction to Databases (CZ2007), Teaching Assistant, 2022 Spring, NTU
Mentoring
- Research Interns
- Chen Cai (Nanyang Technological University, Aug 2023 - Jan 2024)
- Yufan Zhao (National University of Singapore, May 2023 - Oct 2023)
- Ramazan Rakhmatullin (University of Waterloo, May 2023 - Aug 2023)
Awards & Honors
- Huawei TopMinds (2022), Future Star Award (2022), Innovation Competition (Silver Medal for 2023), Excellent Individual Award (2024)
- Honourable Mention for Outstanding PhD Thesis Award, 2023
- World Artificial Intelligence Conference (WAIC) Yunfan Award (15 selected world-wide), 2023
- Nominated Schmidt Science Fellows, 2023
- Google PhD Fellowship (sole winner from Asia in Structured Data and Database Management), 2021
- AISG PhD Fellowship (one of top three NTU awardees), 2021-2023
- Conference Travel Awards (WWW'23, KDD’21, VLDB’20, KDD’19)
- Best Team Award in Baidu, 2017
- Postgraduate Scholarship for Computer Science, The University of Hong Kong, 2016-2017
- Outstanding Bachelor Thesis in SDU, 2016
- Honorable Mention for Mathematical Contest in Modeling, 2015
- Second Prize in Contemporary Undergraduate Mathematical Contest In Modeling, 2014
- Honorable Mention in the ACM-ICPC Invitational Programming Contest Xian Site, 2014
Invited Talks
- Large Generative Models Meet Multimodal Applications, Huawei Young Scholar Innovation Summit (2023)
- Trajectory Data Simplification, Similarity Search and Inference with Deep Learning, HKBU (2022), WAIC (2023)
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