Gund Fellow, Professor, Department of Computer Science

Byung S. Lee is a Professor of Computer Science at the College of Engineering and Mathematical Sciences in the University of Vermont. His expertise lies in developing and comparing computational methods for modeling, understanding, and processing large data efficiently, intelligently, and adaptively. He has published widely and supervised students’ research in these areas. His recent research activities focus on applying advanced data stream processing algorithms to critical applications in environment, energy, healthcare, and social networks. He actively collaborates with scientists at UVM, national laboratory, industry and other universities.


  • Jungeun Kim, Sungsu Lim, Jae-Gil Lee, and Byung Suk Lee, LinkBlackHole*: Robust Overlapping Community Detection Using Link Embedding, IEEE Transactions on Knowledge and Data Engineering, IEEE Publishing, October 2019, 13 pages (early access). 
  • Yuhang Lin, Byung Suk Lee, and Daniel Lustgarten, Continuous Detection of Abnormal Heartbeats from ECG Using Online Outlier Detection, in: Information Management and Big Data, Communications in Computer and Information Science, vol. 898, Springer, September 2018, pp. 349-366. 
  • Ali Javed and Byung Suk Lee, Hybrid Semantic Clustering of Hashtags,Online Social Networks and Media, Volume 5, Elsevier, March 2018, pp. 23-36.
  • Saurav Acharya, Byun Suk Lee, and Paul Hines, Causal Prediction of Top-K Event Types over Real-Time Event Streams, The Computer Journal, Volume 60, Issue 11, November 2017, pp. 1561-1581.
  • Sang-Pil Kim and Byung Suk Lee, Are You a Compatible User? -- Compatibility of a Microblog User with a News Article, Proceedings of the 5th World Conference on Information Systems and Technologies, Vol.3, pp. 193-204, Porto Santo Island, Madeira, Portugal, April 11-13, 2017 in Volume 571 of the Advances in Intelligent Systems and Computing Series, Springer.  

Areas of Expertise and/or Research

Database, data stream, data mining, machine learning


  • PhD, Electrical Engineering (Computer Science), Stanford University
  • MS, Electrical Engineering, KAIST, South Korea
  • BS, Electronics Engineering, Seoul National University


  • 802-656-1919
Office Location:

Innovation E409

  1. Google Scholar