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Chen, Feng

Dr. Feng Chen

Associate Professor


  • Ph.D., Computer Science, Virginia Tech, Blacksburg, VA, 2012
  • M.S., Computer Science, Beihang University, Beijing, China, 2004
  • B.S., Computer Science, Hunan University, Hunan, China, 2001

Research Interests:

  • Anomaly, Event, and Fraud Detection
  • Spatial-Temporal Data Analysis
  • Big Data Analytics
  • Graph Mining and Network Science
  • Machine Learning
  • Artificial Intelligence

Major Honors and Awards:

  • NSF Faculty Early Career Development (CAREER) Award – 2018
  • Faculty Research Awards, University at Albany, State University of New York, 2014, 2018
  • Service Excellence Award as Publication Chair, IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Nov. 13-15, Arlington, VA, 2006

Representative Publications:

  • Chen Zhao and Feng Chen, “Rank-Based Multi-task Learning For Fair Regression”, in Proceedings of the 19th IEEE International Conference on Data Mining (ICDM 2019), 2019.
  • Baojian Zhou, Feng Chen, and Yiming Ying, “Dual Averaging Method for Online Graph-structured Sparsity”, in Proceedings of the 25th ACM SIGKDD conference on knowledge discovery and data mining (KDD 2019), 2019.
  • Baojian Zhou, Feng Chen, and Yiming Ying, “Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization”, in Proceedings of the 36th International Conference on Machine Learning (ICML 2019), 2019.
  • Jose Cadena, Feng Chen, and Anil Vullikanti, “Near-Optimal and Practical Algorithms for Graph Scan Statistics with Connectivity Constraints”, ACM Transactions on Knowledge Discovery from Data (TKDD), volume 13, issue 2, pages 1-33 2019.
  • Audun Jøsang, Jin-Hee Cho, and Feng Chen, “Uncertainty Characteristics of Subjective Opinions”, in Proceedings of the IEEE International Conference on Information Fusion (FUSION’18), 2018.

Notable Service

  • Tutorial Co-Chair, IEEE International Conference on Big Data, 2017
  • BPOD workshop co-chair, IEEE International Workshop on Benchmarking, Performance Tuning and Optimization for Big Data Applications (BPOD), 2018, 2019
  • Guest Editor, A special issue of Geoinformatica on Geosocial Media Analytics, 2016-2018

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