Bio: Ben Bycroft is Director of Vehicle Autonomy & System Trust at The Aerospace Corporation. His work spans research, development, and application of advanced and AI-enabled autonomy, dynamics and control, as well as electromechanical systems engineering for both launch vehicles and spacecraft. Benjamen has previously taught courses within the University of Southern California’s Viterbi School of Engineering. He holds a B.S. in Mechanical Engineering and an M.S. in Dynamics & Control from USC, as well as a B.A. in Physics from Willamette University.

Bio: Alberto Speranzon is a Lockheed Martin Technical Fellow and Chief Scientist for Autonomy at the Advanced Technology Labs (ATL), LM’s research arm. At ATL he leads projects at the intersection of autonomy, AI, and machine learning, emphasizing compositional design methods, neuro‑symbolic approaches, and their application to the design and verification of complex systems. He earned his Ph.D. in Electrical Engineering from the Royal Institute of Technology (KTH), Sweden, in 2006. Prior to joining Lockheed Martin, Alberto was a Technical Fellow at Honeywell Aerospace, where he worked on advanced aerial‑mobility solutions, and before that a research scientist at United Technologies Research Center (now RTX Research Center), tackling problems ranging from efficient building control to autonomous helicopters. Alberto has served as PI or Co‑PI on numerous government‑funded programs (DARPA, NASA) that develop novel navigation techniques for GPS‑degraded/denied environments and tools for the compositional modeling of multi‑agent autonomous systems. He is a Senior Member of IEEE, an associate editor for the IEEE Open Journal of Control Systems (OJ‑SYS), a former associate editor for IEEE Transactions on Control Systems Technology (TCST), and a former member of the Board of Governors of the IEEE Control Systems Society.

Bio: Naren Srivaths Raman is a Principal Software Engineer in the Controls and Identification team at MathWorks, where he focuses on reinforcement learning and model predictive control. He holds an M.S. and Ph.D. in Mechanical Engineering from the University of Florida, and a B.E. in Mechanical Engineering from Anna University, India.

Bio: Shrenik is a Staff Autonomy Engineer at Brain Corp, where he leads the motion planning team in building navigation systems for retail and industrial spaces. He holds a Master's in Robotics from the University of Pennsylvania, with a focus on robot learning, planning, and optimal control. He has worked on areas such as motion planning architecture, human-robot interaction, simulation, and trajectory optimization, as well as end-to-end models for mobile manipulation. Currently, he is focused on developing generative models for planning and decision making.