Paul Gibby

Paul Gibby is an assistant staff member in the Artificial Intelligence Technology and Systems Group at MIT Lincoln Laboratory. He started his Laboratory career in the Cyber Operations and Analysis Technology Group in January 2018 and transferred to his current group in the spring of 2019. He has interests in natural language processing, machine learning, adversarial robustness, and graph neural networks.

Gibby received his BS degree in applied mathematics from Brigham Young University, where he performed undergraduate research into the dynamics of systems under time-varying time delays.

He coauthored a paper on the use of genetic algorithms to model sparse, seasonal data, such as the arrival times of cyberattacks. The paper was accepted and published by the International Conference on Pattern Recognition (ICPR) 2020 conference.