Huiyuan Chen

Staff Research Scientist

Research Areas: Machine Learning, Anomaly Detection, and Recommendation Systems

Huiyuan Chen, Visa Research scientist.

Biography

Dr. Huiyuan Chen joined Visa Research as a Staff Research Scientist in November 2020. Huiyuan received his Ph.D. in Computer Science at Case Western Reserve University in 2020, and B.S. in Mechanical Engineering from Beijing Jiaotong University in 2013. Prior to joining Visa Research, Huiyuan was a Research and Teaching Assistant at Case Western Reserve University, teaching algorithm, data structure, and machine learning. His Ph.D. project focused on scalable tensor machine and its application in recommender systems and bioinformatics.

As a member of the Artificial Intelligence team, his research interests are machine learning and deep learning, with a particular focus on time series analysis, graph-based mining, and anomaly detection. He has published more than 10 papers in several conferences and journals, including The Web Conference (WWW), the International Joint Conference on Artificial Intelligence (IJCAI), the ACM Recommender Systems conference (RecSys), the Conference on Information and Knowledge Management (CIKM), the Institute of Electrical and Electronics Engineers (IEEE) International Conference on Data Mining (ICDM), and others.

Thesis

  1. Chen, H. (2020). Dimension Reduction for Network Analysis with an Application to Drug Discovery. Case Western Reserve University.

Conferences

  1. Chen, Huiyuan, and Jing Li. "Neural Tensor Model for Learning Multi-Aspect Factors in Recommender Systems." In IJCAI, 2020.
  2. Chen, Huiyuan, and Jing Li. "Adversarial tensor factorization for context-aware recommendation." In RecSys, 2019.
  3. Chen, Huiyuan, and Jing Li. "Data Poisoning Attacks on Cross-domain Recommendation." In CIKM, 2019.
  4. Chen, Huiyuan, and Jing Li. "Modeling relational drug-target-disease interactions via tensor factorization with multiple web sources." In WWW. 2019.
  5. Chen, Huiyuan, and Jing Li. "Exploiting structural and temporal evolution in dynamic link prediction." In CIKM. 2018.
  6. Chen, Huiyuan, and Jing Li. "Drugcom: Synergistic discovery of drug combinations using tensor decomposition." In ICDM, 2018.
  7. Chen, Huiyuan, and Jing Li. "Learning multiple similarities of users and items in recommender systems." In ICDM, 2017.