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Ivan Papusha, PhD. is a senior analyst in Washington, D.C. He was previously a senior engineer and computer scientist in the Space Exploration Sector at the Johns Hopkins University Applied Physics Lab, where he worked on a variety of scientific and engineering projects in the domain of space exploration. Before then, he was 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; he is a member of the IEEE, and the founder and CEO of subgradient.