Scott Buffett

Roles and responsibilities

I am a Senior Research Officer in the Digital Technologies Research Center, specializing in pattern-based behavioural analysis through the use of data mining and machine learning. I am also the lead for the Cybersecurity research team.

Current research and/or projects

My research focusses on the development of novel methods for analyzing patterns found in large streams of data captured via sensors and event logs monitoring the usage of machines and systems, with the objective of modeling underlying behaviours.

Research and/or project statements

This work has applicability in numerous project areas, including:

  • Analysis of training simulator usage for the purpose of improving simulator workflows or course material
  • Identification of activities exhibited by human subjects via movement patterns, which can be used to help athletes improve performance or to monitor the activity of older adults living alone to detect abnormalities
  • Detection of the presence of malicious behaviour on systems or networks in order to identify potential threats or attacks

Education

PhD (Computer Science), University of New Brunswick

Professional activities/interests

Adjunct Professor, Faculty of Computer Science, University of New Brunswick

Associate Editor, Electronic Commerce Research and Applications (ECRA)

Key publications

Buffett S. Discretized sequential pattern mining for behaviour classification. Granular Computing. 2021 Oct;6(4):853-66.

Buffett S. Dramatically Reducing Search for High Utility Sequential Patterns by Maintaining Candidate Lists. Information. 2020 Jan 15;11(1):44.

Buffett S. Candidate list maintenance in high utility sequential pattern mining. In 2018 IEEE International Conference on Big Data (Big Data) December 2018 (pp. 644-652). IEEE.

Buffett, S., Pagiatakis, C., & Jiang, D. Pattern-Based Behavioural Analysis on Neurosurgical Simulation Data. Proceedings of the Machine Learning for Healthcare Conference (MLHC 2018), Stanford, CA, August 2018.

Emond, B., Buffett, S., Goutte, C., & Guo, R. J. Analysing and Refining Pilot Training. Proceedings of the 9th International Conference on Educational Data Mining (EDM 2016), Buffalo, NY, July 2016, pp. 682-687.

Emond, B., and Buffett, S. Analyzing student inquiry data using process discovery and sequence classification. Proceedings of the 8th International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, June 2015, pp. 412-415.

Buffett, S. A Revelation Mechanism for Shared Conditional Preferences in Multi-Attribute Negotiation. The Third International Workshop on Agent-based Complex Automated Negotiations, held in conjunction with the Eighth International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2010), Toronto, Canada, May 2010, pages 9-15.

Buffett, S. Abductive Workflow Mining using Binary Resolution on Task Successor Rules. The International RuleML Symposium on Rule Interchange and Applications (RuleML 2008). October 30, 2008. NRC 50392.

Buffett, S., and Fleming, M.W. Persistently Effective Query Selection in Preference Elicitation. The 2007 IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT'07). Fremont, CA. November 2-5, 2007. NRC 49846.

Scott Buffett

Scott Buffett

Senior Research Officer
Digital Technologies
46 Dineen Drive
Fredericton, New Brunswick E3B 9W4
Preferred language: English
Telephone: 506-444-0386

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Expertise

Information Technology, Computer security, Data analytics, Data Science