Shane Strasser

Dr. Strasser received his BS in computer science and mathematics from the University of Sioux Falls in 2009. He then received an MS in computer science at Montana State University in 2011. He continued his studies and received his Ph.D. in computer science from Montana State University, completing a dissertation on Factored Evolutionary Algorithms. 

After graduating from MSU, he begun working at Oracle as a Senior Software Engineer where he focused on developing search and knowledge foundation software for the Oracle Service Cloud. He then transitioned in a software architect on designing and building multi-tenant Machine Learning applications for Oracle Service Cloud. Recently, he begun working at Globality as a backend Senior Software Engineer where he is designing and building matching algorithms for professional service procurement.

Education History

• BS, Computer Science, University of Sioux Falls
• M.S., Computer Science, Montana State University
• PHD, Computer Science, Montana State University

Work Experience

Adjunct Faculty, JHU Whiting School of Engineering, Engineering for Professionals

Publications

– Shane Strasser, John Sheppard, Michael Schuh, Rafal Angryk, and Clemente Izurieta. Graph-based ontology-guided data mining for d-matrix model maturation. In Aerospace Conference, 2011 IEEE , pages 1–12. IEEE, 2011.

– Shane Strasser and John Sheppard. Diagnostic alarm sequence maturation in timed failure propagation graphs. In 2011 IEEE AUTOTESTCON , pages 158–165. IEEE, 2011.

– Shane Strasser, Colt Frederickson, Kevin Fenger, and Clemente Izurieta. An automated software tool for validating design patterns. In INTERNATIONAL CONFERENCE ON COMPUTER APPLICATIONS IN INDUSTRY AND ENGINEERING , pages 322–327. Intl. Society for Computers and Their Application, 2011.

– Michael Schuh, John Sheppard, Shane Strasser, Rafal Angryk, and Clemente Izurieta. Ontology-guided knowledge discovery of event sequences in maintenance data. In 2011 IEEE AUTOTESTCON , pages 279–285. IEEE, 2011.

– Shane Strasser, Eben Howard, and John Sheppard. An integrated toolset for ontology-guided diagnostic knowledge discovery. In 2012 IEEE AUTOTESTCON Proceedings , pages 280–290. IEEE, 2012.

– Shane Strasser and John Sheppard. An empirical evaluation of bayesian networks derived from fault trees. In 2013 IEEE Aerospace Conference , pages 1–13. IEEE, 2013.

– Shane Strasser and John Sheppard. Diagnostic model maturation. IEEE Aerospace and Electronic Systems Magazine , 28(1):34–43, 2013.

– Michael Schuh, John Sheppard, Shane Strasser, Rafal Angryk, and Clemente Izurieta. An ieee standards-based visualization tool for knowledge discovery in maintenance event sequences. IEEE Aerospace and Electronic Systems Magazine , 28(7):30–39, 2013.

– Nathan Fortier, John Sheppard, and Shane Strasser. Learning bayesian classifiers using overlapping swarm intelligence. In 2014 IEEE Symposium on Swarm Intelligence , pages 1–8. IEEE, 2014.

– Nathan Fortier, John Sheppard, and Shane Strasser. Abductive inference in bayesian networks using distributed overlapping swarm intelligence. Soft Computing , 19(4):981–1001, 2015.

– Nathan Fortier, John Sheppard, and Shane Strasser. Parameter estimation in bayesian networks using overlapping swarm intelligence. In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation , pages 9–16. ACM, 2015. 1

– Logan Perreault, Monica Thornton, Shane Strasser, and John W Sheppard. Deriving prognostic continuous time bayesian networks from d-matrices. In 2015 IEEE AUTOTESTCON , pages 152–161. IEEE, 2015.

– Rollie Goodman, Monica Thornton, Shane Strasser, and John W Sheppard. Micpso: A method for incorporating dependencies into discrete particle swarm optimization. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI) , pages 1–8. IEEE, 2016.

– Logan Perreault, Shane Strasser, Monica Thornton, and John Sheppard. A noisy-or model for continuous time bayesian networks. In The Twenty Ninth International Flairs Conference , 2016.

– Stephyn Butcher, Shane Strasser, Jenna Hoole, Benjamin Demeo, and John Sheppard. Relaxing consensus in distributed factored evolutionary algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference 2016 , pages 5–12. ACM, 2016.

– Shane Strasser, Rollie Goodman, John Sheppard, and Stephyn Butcher. A new discrete particle swarm optimization algorithm. In Proceedings of the Genetic and Evolutionary Computation Conference 2016 , pages 53–60. ACM, 2016. 2

– Shane Strasser, John Sheppard, Nathan Fortier, and Rollie Goodman. Factored evolutionary algorithms. IEEE Transactions on Evolutionary Computation , 21(2):281–293, 2016.

– John W Sheppard and Shane Strasser. A factored evolutionary optimization approach to bayesian abductive inference for multiple-fault diagnosis. In 2017 IEEE AUTOTESTCON , pages 1–10. IEEE, 2017.

– Shane Strasser, John Sheppard, and Stephyn Butcher. A formal approach to deriving factored evolutionary algorithm architectures. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) , pages 1–8. IEEE, 2017.

– Shane Strasser and John W Sheppard. Convergence of factored evolutionary algorithms. In Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic Algorithms , pages 81–94. ACM, 2017.

– Shane Strasser and John W Sheppard. Evaluating factored evolutionary algorithm performance on binary deceptive functions. In 2017 IEEE Symposium Series on Computational Intelligence (SSCI) , pages 1–8. IEEE, 2017.

– Shane Tyler Strasser. Factored evolutionary algorithms: cooperative coevolutionary optimization with overlap . PhD thesis, Montana State University Bozeman, College of Engineering, 2017.

– John W Sheppard and Shane Strasser. Multiple fault diagnosis using factored evolutionary algorithms. IEEE Instrumentation & Measurement Magazine , 21(4):27–38, 2018.

– Stephyn GW Butcher, John W Sheppard, and Shane Strasser. Pareto improving selection of the global best in particle swarm optimization. In 2018 IEEE Congress on Evolutionary Computation (CEC) , pages 1–8. IEEE, 2018.

– Stephyn GW Butcher, John W Sheppard, and Shane Strasser. Information sharing and conflict resolution in distributed factored evolutionary algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference , pages 5–12. ACM, 2018.