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Ivan Papusha is a member of the senior professional staff in the Space Exploration Sector at the Johns Hopkins University Applied Physics Lab, where he works on a variety of scientific and engineering projects in the domain of space exploration. He was formerly a postdoctoral fellow in the Oden Institute for Computational Engineering and Sciences at UT Austin. There he invented new methods for autonomy and verification of machine learning systems.

He completed his PhD in Control and Dynamical Systems at Caltech, where he was awarded the National Defense Science and Engineering Graduate Fellowship (NDSEG). His research in the Networked Control Systems Lab spanned robustness, adaptation, and learning in optimal control—including the application of convex optimization and formal verification to robotic systems. He received his BS and MS degrees in Electrical Engineering from Stanford University, and is a member of the IEEE.