Yatis K. Dodia serves as the branch head for Quantitative Methods within ASID in GTRI’s CIPHER lab. His work focuses on the intersections of classical and quantum information theory, machine learning, and computational complexity for applications to cybersecurity. Another core thrust is trusted communications, such as aiming to leverage zero trust principles within 5G networks, and the potential for using robust AI/ML methods for threat detection and optimal mitigation. Previously, he has worked with ion-trap quantum computing and for a large telecom where he was the lead engineer in transitioning to IP-based technologies and standardizing Consumer Edge (CE) network topologies.

Adonis Bovell leads the algorithm assurance branch in the Assured Software and Information Division of GTRI’s CIPHER Lab. His group’s work focuses on the security benefits and risks associated with the application of advanced algorithms to cybersecurity problems. This entails research on model robustness, trustworthiness and privacy, including data valuation and synthetic data generation, formal verification and adversarial machine learning, and privacy and fairness. Previously, Bovell has worked on automated malware analysis and malicious network traffic detection.

Robert Wright is a GTRI Senior Research Scientist in the Assured Software and Information Division within the CIPHER laboratory. He has been with GTRI since 2021 and leads research efforts in trustworthy autonomous systems. Wright started his career as a civilian research scientist for the Air Force Research Laboratory where he developed technologies and programs for autonomous command and control systems (2003-2016). In 2014, Wright received his Ph.D. in computer science from Binghamton University for his work in developing RL algorithms that learn efficiently from experience Prior to GTRI (2016-2021), Wright was a principal scientist for Assured Information Security where he was a PI for a number of DARPA and Air Force Research Laboratory efforts researching RL and AI techniques. His work has been published in many top venues and was awarded “Best Paper” at the 2013 European Conference on ML.