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Tom Devine

Tom Devine


AER 337

Teaching Assistant Professor - Lane Department of Computer Science and Electrical Engineering


  • Ph.D., Computer Science, West Virginia University, 2020
  • M.S., Computer Science, West Virginia University, 2013
  • B.S., Computer Science, Fairmont State University, 2010
  • B.S., Mathematics, Fairmont State University, 2009
  • B.A., Philosophy/History of Science & Mathematics, St. John’s College, 2003

Tom Devine is a Teaching Assistant Professor at West Virginia University who prepares students to meet the demands of the modern technological workforce. He is a Fairmont native who has earned 2 Bachelor of Arts degrees from St. John’s College, 2 Bachelor of Science degrees from Fairmont State University, and a Master’s and PhD in Computer Science from WVU. For his PhD research, he developed scalable artificial intelligence algorithms to help astrophysicists discover rare stars. When he isn’t teaching or doing research, Tom can be caught spending time with his family, playing with his dogs, riding his motorcycle, or slaying dragons online.

Selected Publications

  1. T. Devine, "Searching for Needles in the Cosmic Haystack," West Virginia University Graduate Theses, Dissertations, and Problem Reports, July, 2020.
  2. Tom Cuchta, Brian Blackwood, Thomas R. Devine, Robert J. Niichel, Kristina M. Daniels, Caleb H. Lutjens, Sydney Maibach, and Ryan J. Stephenson. 2019. Human Risk Factors in Cybersecurity. In Proceedings of the 20th Annual SIG Conference on Information Technology Education (SIGITE '19). ACM, New York, NY, USA, 87-92. DOI:
  3. Thomas R. Devine, Katerina Goseva-Popstojanova, and Di Pang. 2018. Scalable Solutions for Automated Single Pulse Identification and Classification in Radio Astronomy. In Proceedings of the 47th International Conference on Parallel Processing (ICPP 2018). ACM, New York, NY, USA, Article 11, 11 pages.
  4. Thomas Devine, Katerina Goseva-Popstajanova, Maura McLaughlin, “Detection of Dispersed Radio Pulses: A machine learning approach to candidate identification and classification,” Monthly Notices of the Royal Astronomical Society 459 (2), pp 1519-1532, 2016.
  5. Thomas Devine, Katerina Goseva-Popstajanova, Sandeep Krishnan, Robyn Lutz, “Assessment and cross-product prediction of software product line quality: accounting for reuse across products, over multiple releases,” Automated Software Engineering, pp 1-50, 2014.

Teaching Interests

  • Computer Science Fundamentals
  • Software Engineering
  • Operating Systems
  • Cybersecurity Fundamentals
  • Network Security
  • Vulnerability Assessment
  • Ethics

Research Interests

  • Data Science
  • Machine Learning
  • High Performance Computing
  • Astrophysics

Professional Societies

  • Member of the Association for Computing Machinery (ACM)
  • Member of the Institute of Electrical and Electronics Engineers (IEEE)