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Adam Szymanski

Unmanned Aerial Vehicles UAV/UAS


He is a computer scientist in the Global Security Sciences Division at Argonne National Laboratory working on a variety of Modeling and Simulation (M&S) projects. He is an integral part of the Analysis of Mobility Platforms (AMP) logistics modeling project for U.S. Transportation Command. He has also been the lead investigator on a program for the Naval Research Laboratory doing Electronic Warfare (EW) M&S, which includes both EW system modeling as well as detailed Radio Frequency (RF) propagation modeling in complex environments. Among his research interests is the development of remotely distributed deep-learning image recognition systems for Unmanned Aerial Systems (UAS) detection. He participated in numerous government and military test and evaluation events for UAS mitigation systems and did analysis on UAS threats to critical infrastructure and methods for protection. He graduated from Carnegie Mellon University with a degree in computer science and robotics and is currently pursuing a master's in analytics at the University of Chicago with an emphasis on advanced computational models, including computer vision and machine learning algorithms.