Avatar


    Email
    LinkedIn
    Google Scholar

I am a Research Staff Member in the Department of Data Science and System Security at the NEC Labs America. I got my Ph.D. in Information Technology from Rutgers, the State University of New Jersey, under the supervision of Professor Hui Xiong.
I have a broad interest in data mining, natural language processing, machine learning, and their applications to solve real problems. My current research develops efficient and effective solutions to address challenges in various domains, including e-commerce, social networks, complex system management, finance, cybersecurity, and aerospace.
I have published papers in top journals and conferences in data mining and applied machine learning including TKDE, KDD, SIGIR, WWW, CIKM, AAAI, WSDM, ICDM, ICDE with more than 4,800 citations (H-index: 29), served as (senior) program committee members in KDD, WWW, SIGIR, WSDM, AAAI, IJCAI, CIKM as well as several workshops.


Research Interest

  • Data Science: Data Mining, Recommender Systems, Time Series Analysis
  • Natural Language Processing: Language Modeling, Information Extraction, Cross-lingual Transfer
  • Machine Learning: Deep Learning, Clustering, Anomaly Detection, Semi-supervised Learning


    • Selected Publications

    • Google Scholar | • DBLP

  • Shengming Zhang, Yanchi Liu, Xuchao Zhang, Wei Cheng, Haifeng Chen, Hui Xiong. CAT: Beyond Efficient Transformer for Content-Aware Anomaly Detection in Event Sequences. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2022.
  • Denghui Zhang, Yanchi Liu, Zixuan Yuan, Yanjie Fu, Haifeng Chen, Hui Xiong. Multi-Faceted Knowledge-Driven Pre-training for Product Representation Learning. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
  • Denghui Zhang, Zixuan Yuan, Yanchi Liu, Hao Liu, Fuzhen Zhuang, Hui Xiong, Haifeng Chen. Domain-oriented Language Modeling with Adaptive Hybrid Masking and Optimal Transport Alignment. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
  • Xuchao Zhang, Bo Zong, Wei Cheng, Jingchao Ni, Yanchi Liu and Haifeng Chen. Unsupervised Concept Representation Learning for Length-Varying Text Similarity. In Proceedings of The 2021 Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL), 2021.
  • Denghui Zhang, Yanchi Liu, Wei Cheng, Bo Zong, Jingchao Ni, Zhengzhang Chen, Haifeng Chen, Hui Xiong. T$^2$-Net: A Semi-supervised Deep Model for Turbulence Forecasting. 2020 IEEE International Conference on Data Mining (ICDM), 2020.
  • Renjun Hu, Yanchi Liu, Yanyan Li, Jingbo Zhou, Shuai Ma, Hui Xiong. Exploiting User Preference and Mobile Peer Influence for Human Mobility Annotation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2020.
  • Pengpeng Zhao, Anjing Luo, Yanchi Liu, Fuzhen Zhuang, Jiajie Xu, Zhixu Li, Victor S Sheng, Xiaofang Zhou. Where to go next: A spatio-temporal gated network for next poi recommendation. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.
  • Weijia Zhang, Hao Liu, Yanchi Liu, Jingbo Zhou, Tong Xu, Hui Xiong. Semi-Supervised City-Wide Parking Availability Prediction via Hierarchical Recurrent Graph Neural Network. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2020.
  • Nengjun Zhu, Jian Cao, Yanchi Liu, Yang Yang, Haochao Ying, Hui Xiong. Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation. Proceedings of the 13th International Conference on Web Search and Data Mining (WSDM), 2020.
  • Jian Liu, Pengpeng Zhao, Fuzhen Zhuang, Yanchi Liu, Victor S Sheng, Jiajie Xu, Xiaofang Zhou, Hui Xiong. Exploiting Aesthetic Preference in Deep Cross Networks for Cross-domain Recommendation. Proceedings of The Web Conference (WWW), 2020.
  • Zixuan Yuan, Hao Liu, Yanchi Liu, Denghui Zhang, Fei Yi, Nengjun Zhu, Hui Xiong. Spatio-Temporal Dual Graph Attention Network for Query-POI Matching. %Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020.
  • Dongbo Xi, Fuzhen Zhuang, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He. Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), 2019.
  • Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Jiajie Xu, Victor Sheng, Zhiming Cui, Xiaofang Zhou, Hui Xiong. Recurrent Convolutional Neural Network for Sequential Recommendation. World Wide Web conference (WWW), 2019.
  • Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Victor S Sheng, Jiajie Xu, Fuzhen Zhuang, Junhua Fang, Xiaofang Zhou. Graph Contextualized Self-Attention Network for Session-based Recommendation. International Joint Conference on Artificial Intelligence (IJCAI), 2019.
  • Yanchi Liu, Tan Yan, Haifeng Chen. Exploiting Graph Regularized Multi-dimensional Hawkes Processes for Modeling Events with Spatio-temporal Characteristics. the 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018.
  • Pengpeng Zhao, Haifeng Zhu, Yanchi Liu, Zhixu Li, Jiajie Xu, Victor S Sheng. Where to go next: A spatio-temporal lstm model for next poi recommendation. AAAI, 2018.
  • Yanchi Liu, Chuanren Liu, Xinjiang Lu, Mingfei Teng, Hengshu Zhu, Hui Xiong. Point of Interest Demand Modeling with Human Mobility Patterns. The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017.
  • Pengpeng Zhao, Xiefeng Xu, Yanchi Liu, Victor S. Sheng, Kai Zheng, Hui Xiong. Photo2Trip: Exploiting Visual Contents in Geo-tagged Photos for Personalized Tour Recommendation. Proceedings of the 2017 ACM on Multimedia Conference (MM), 2017.
  • Pengpeng Zhao, Xiefeng Xu, Yanchi Liu, Ziting Zhou, Kai Zheng, Victor S. Sheng, Hui Xiong. Exploiting Hierarchical Structures for POI Recommendation. 2017 IEEE International Conference on Data Mining (ICDM), 2017.
  • Yanchi Liu, Chuanren Liu, Bin Liu, Meng Qu, Hui Xiong. Unified Point-of-Interest Recommendation with Temporal Interval Assessment. The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016.
  • Lian Duan, Nick Street, Yanchi Liu, Haibing Lu. Community detection in graphs through correlation. Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining (KDD), 2014.
  • Yanchi Liu, Chuanren Liu, Nicholas Jing Yuan, Lian Duan, Yanjie Fu, Hui Xiong, Songhua Xu, Junjie Wu. Exploiting heterogeneous human mobility patterns for intelligent bus routing. 2014 IEEE International Conference on Data Mining (ICDM), 2014. (Best paper candidate>)
  • Yanchi Liu, Zhongmou Li, Hui Xiong, Xuedong Gao, Junjie Wu, Sen Wu. Understanding and enhancement of internal clustering validation measures. IEEE Transactions on Cybernetics, 2013.
  • Yu Zheng, Yanchi Liu, Jing Yuan, Xing Xie. Urban computing with taxicabs. Proceedings of the 13th international conference on Ubiquitous computing (UbiComp), 2011. (Best paper candidate>)
  • Yanchi Liu, Zhongmou Li, Hui Xiong, Xuedong Gao, Junjie Wu. Understanding of internal clustering validation measures. 2010 IEEE International Conference on Data Mining (ICDM), 2010.
  • Zhongmou Li, Hui Xiong, Yanchi Liu, Aoying Zhou. Detecting Blackhole and Volcano Patterns in Directed Networks. 2010 IEEE International Conference on Data Mining (ICDM), 2010.


    • Honors and Awards

  • NEC Global Innovation Unit Outstanding Award, NEC, 2022
  • Baidu Research Fellowship (10 PhD candidates worldwide), Baidu, 2018
  • TA/RA Developing Fund Award, Rutgers University, 2018
  • Nominee of Best Paper, IEEE International Conference on Data Mining (ICDM), 2014
  • Nominee of Best Paper, ACM International Conference on Ubiquitous Computing (UbiComp), 2011