LIU Yiding (刘亦丁)

Short Bio:

  • I received my Ph.D. degree from from Nanyang Technological University in 2020.
  • My research focuses on data science, including large-scale data mining & analytics, data management, etc.
  • My recent research topics include:
    • Efficient and effective text retrivial & recommendation;
    • Modeling geo-spatial and mobility data;
    • Others: graph neural networks, generative models, and few-shot learning.
  • Contact: liuyiding.tanh at gmail.com

Education

  • 2016 – 2020:     Nanyang Technological University.     Singapore
    • Ph.D. in Computer Science; Supervisor: Prof. Gao Cong.
    • Research interests: Spatiotemporal data mining, (deep) representation learning, recommender system.
    • Thesis: Latent Representation Models for Mining Geo-spatial Data.
      • Honourable Mention for Outstanding PhD Thesis Award [News].
  • 2011 – 2015:     Univ. of Elec. Sci. and Tech. of China.     Chengdu, Sichuan, China
    • BEng. in Computer Science (Outstanding Graduates); Supervisor: Prof. Tao Zhou & Prof. Zhihai Rong.
    • Research interests Spatiotemporal data mining, social network analysis.
    • Thesis: Human Mobility Prediction using Machine Learning.

Experiences

  • May 2020 – Now: Baidu Inc. Beijing, China
  • Sep 2019 – Apr 2020: JD.COM. Beijing, China
    • Research Scientist (Intern) at Data Science Lab.
  • Sep 2015 – Aug 2019: Nanyang Technological University. Singapore
    • Project Officer at Data Management & Analytics Lab (DMAL).
  • July 2014 – Sep 2014: Tencent. Chengdu, Sichuan, China
    • Research Intern at Social Network Group.
  • Sep 2013 – Jul 2015: Univ. of Elec. Sci. and Tech. of China. Chengdu, Sichuan, China
    • Research Assistant at Web Science Center.

Publications

Full list of publications: Google Scholar, DBLP

Conference Papers:

  • Wenwen Ye, Yiding Liu, Lixin Zou, Hengyi Cai, Suqi Cheng, Shuaiqiang Wang, Dawei Yin. Fast Semantic Matching via Flexible Contextualized Interaction. (Accepted by WSDM’22)
  • Yile Chen, Xiucheng Li, Gao Cong, Zhifeng Bao, Cheng Long, Yiding Liu, Arun Chandran and Richard Ellison. Robust Road Network Representation Learning: When Traffic Patterns Meet Traveling Semantics. (Accepted by CIKM’21)
  • Yiding Liu, Weixue Lu, Suqi Cheng, Daiting Shi, Shuaiqiang Wang, Zhicong Cheng, Dawei Yin. Pre-trained Language Model for Web-scale Retrieval in Baidu Search (ADS Track). In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’21). [Arxiv]
  • Siyuan Guo, Lixin Zou, Yiding Liu, Wenwen Ye, Suqi Cheng, Shuaiqiang Wang, Hechang Chen, Dawei Yin and Yi Chang. Enhanced Doubly Robust Learning for Debiasing Post-Click Conversion Rate Estimation. In Proceedings of the 44th International ACM SIGIR Conference (SIGIR’21). [Arxiv]
  • Yiding Liu, Yulong Gu, Zhuoye Ding, Junchao Gao, Ziyi Guo, Yongjun Bao and Weipeng Yan. Decoupled Graph Convolution Network for Inferring Substitutable and Complementary Items (Applied Research Track). In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM’20), Online, October 2020. [Link]
  • Yulong Gu, Zhuoye Ding, Shuaiqiang Wang, Lixin Zou, Yiding Liu, Dawei Yin. Deep Multifaceted Transformers for Multi-objective Ranking in Large-Scale E-commerce Recommender Systems (Applied Research Track). In Proceedings of the 29th ACM International Conference on Information and Knowledge Management (CIKM’20), Online, October 2020. [Link]
  • Zheng Wang, Cheng Long, Gao Cong, Yiding Liu. Efficient and Effective Similar Subtrajectory Search with Deep Reinforcement Learning. In Proceedings of the 46rd International Conference on Very Large Data Bases (VLDB’20) [Arxiv]
  • Yiding Liu, Kaiqi Zhao, Gao Cong, Zhifeng Bao. Online Anomalous Trajectory Detection with Deep Generative Sequence Modeling. In Proceedings of the 36rd IEEE International Conference on Data Engineering (ICDE’20), Dallas, Texas, USA, April 2020. [Link]
  • Lucas Vinh Tran, Tuan-Anh Nguyen Pham, Yi Tay, Yiding Liu, Gao Cong and Xiaoli Li. Interact and Decide: Medley of Sub-Attention Networks for Effective Group Recommendation. In Proceedings of the 42nd International ACM SIGIR Conference (SIGIR’19), Paris, France, July 2019. [Link]
  • Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li. MetaST: Deep Spatial-Temporal Prediction via Knowledge Transfer from Multiple Cities. In Proceedings of The Web Conference 2019 (WWW’19), San Francisco, California, USA, May 2019. [Link]
  • Yiding Liu, Kaiqi Zhao, Gao Cong. Efficient Similar Region Search with Deep Metric Learning. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’18) (Research Track – Oral), London, United Kingdom, August 2018. [Link]
  • Yiding Liu, Tuan-Anh Nguyen Pham, Gao Cong, Quan Yuan. An Experimental Evaluation of Point-of-interest Recommendation in Location-based Social Networks. In Proceedings of the 43rd International Conference on Very Large Data Bases (VLDB’17), Munich, Germany, August 2017. [Link]
  • Kaiqi Zhao, Yiding Liu, Quan Yuan, Lisi Chen, Zhida Chen, Gao Cong. Towards Personalized Maps: Mining User Preferences from Geo-textual Data (Demo). In Proceedings of the 42nd International Conference on Very Large Data Bases (VLDB’16), New Delhi, India, September 2016. [Demo site]
  • Kaiyu Feng, Kaiqi Zhao, Yiding Liu, Gao Cong. A System for Region Search and Exploration (Demo). In Proceedings of the 42nd International Conference on Very Large Data Bases (VLDB’16), New Delhi, India, September 2016. [Demo site]

Journal Paper:

  • Chao Fan, Yiding Liu, Junming Huang, Zhihai Rong, Tao Zhou. Correlation between social proximity and mobility similarity. Scientific Reports 7 (1), 11975. [Link]

Selected Awards

  • Honourable Mention for Outstanding PhD Thesis Award, Nanyang Tech. Univ., 2020
  • KDD Student Travel Awards, ACM, 2018
  • VLDB Travel Awards (10 out of all student participators), VLDB Endowment, 2017
  • Outstanding Graduates, Univ. of Elec. Sci. and Tech. of China (UESTC), 2015
  • Meritorious Winner (top 10%), 2013 Interdisciplinary Contest in Modeling (ICM), COMAP, 2013
  • Outstanding Student Leader Scholarship, Univ. of Elec. Sci. and Tech. of China (UESTC), 2013
  • First Class Scholarship, Univ. of Elec. Sci. and Tech. of China (UESTC), 2012 & 2014

Professional Services

  • Web Chair, 38th IEEE International Conference on Data Engineering, 2022

  • Conference Reviewer
    • 2022: AAAI, IJCAI, WSDM.
    • 2021: AAAI, IJCAI, WSDM, PAKDD, TheWebConf, KDD, CIKM.
    • 2020: KDD, ICDE, AAAI, ICLR, IJCAI, PAKDD.
    • 2019: TKDE, KDD, EMNLP, CIKM, SIGSPATIAL.
    • 2018: SIGMOD, WWW, KDD, AAAI, DASFAA, SIGSPATIAL, BigData.
    • 2017: WSDM, CIKM, ICDM, DASFAA, DSAA, ADMA.
  • Journal Reviewer
    • TKDE, TOIS, GeoInformatica