About CISA

Chad Kidder, PE, has spent most of his career working on radars in defense and civilian applications, particularly imaging radars. He chairs the IEEE-USA Conference Committee and serves on the Sensors Council Administrative Committee.

Miguel Heredia Conde received his Dr.Eng. in sensor signal processing in 2016 and his Habilitation in 2022 from the University of Siegen. He joined the University of Wuppertal in 2023, where he heads the Computational 3D Imaging research group. His interests include time-of-flight and terahertz imaging, compressive sensing, computational imaging, and unconventional sensing. He previously led research on compressive sensing for photonic mixer devices at Siegen’s Center for Sensor Systems and managed the MENELAOS research training network. He chairs the IEEE Synthetic Aperture Standards Committee’s P3382 working group on performance metrics for MRI reconstruction. His work has received awards at ICCP and CoSeRa.

Ritwik Gupta is an Assistant Professor of Computer Science and AI at the University of Maryland, College Park. He leads the Resilient AI for Grounded Sensing Lab. Ritwik’s researc is focused on representation learning for active sensors such as radar and sonar, and perception for large data formats such as satellite imagery. Ritwik received his Ph.D. from the University of California, Berkeley in Computer Science in 2025 and completed a post-doc at Berkeley in Chemistry. Previously, Ritwik served as the Technical Director for Autonomy at the U.S. Department of Defense’s Defense Innovation Unit.

Bhupendra A. Raut is a Computational Environmental Scientist at Argonne National Laboratory. He specializes in remote sensing, atmospheric data analysis, and scientific software development. His research develops algorithms and scalable software to detect, characterize, track, and forecast atmospheric convection from weather radar and other observations. His current work includes adaptive radar scanning, real-time storm tracking, and AI for autonomous analysis. He develops open-source tools and interoperable workflows connecting radar processing, computer vision, and quantitative analysis.

Bobby Jackson is an Atmospheric Scientist at Argonne National Laboratory whose expertise includes radar meteorology, AI for meteorological observations, and boundary layer processes. He earned his Ph.D. in Atmospheric Sciences at the University of Illinois Urbana-Champaign in 2015 and completed a postdoctoral appointment at the University of Wyoming. At Argonne, he leads development of scanning weather radar products for the Department of Energy’s Atmospheric Radiation Measurement Facility and Integrated Energy Systems Office. He also develops AI and machine learning workflows for ARM data quality control and self-driven boundary layer sensing systems.

Eric Mason is Director of Data Science at HawkEye360, where he leads development of capabilities and products for space-based sensing, detection, identification, and tracking of RF emitters. He earned his Ph.D. in electrical engineering at Rensselaer Polytechnic Institute in 2017. From 2017 to 2021, he researched signal processing, machine learning, and optimization for radar and electronic warfare at the US Naval Research Laboratory. His work centers on cognitive RF systems, including a multinational cognitive electronic warfare prototype and the cognitive system behind HawkEye360’s maritime domain products.

Corina Nafornita is a Professor at Politehnica University of Timisoara, Romania, and a Senior Member of IEEE. She earned her Ph.D. in electronics and telecommunications at the Technical University of Cluj-Napoca in 2008 and defended her Habilitation in 2015. Her research interests include signal and image processing, radar, machine learning, synthetic aperture radiometry, and wavelets. She serves as Vice-chair of the IEEE P3339 Synthetic Aperture Radiometry Working Group and Chair of the IEEE P3520 Machine Learning for Synthetic Apertures Working Group. She has published more than 80 papers.

Shubham Sharma is a Senior Member of IEEE with nearly a decade of experience in SAR image processing. He is Secretary of the IEEE Synthetic Aperture Standards Committee and Vice Chair of the working group on leveraging machine learning in synthetic aperture imaging and sensing. He holds a Master’s degree in Computer Science and Engineering from Nirma University. His experience includes fellowship projects with ISRO processing RISAT-1 and other spaceborne SAR data. His interests span SAR signal processing, image processing, computer vision, and remote sensing, and he has contributed to SciPy and PyCon conferences.

Peter Vouras chairs the IEEE Signal Processing Society Synthetic Aperture Standards Committee and was the founding Chair of its Synthetic Aperture Technical Working Group. The committee develops image-formation standards for radar, channel sounding, radiometry, MRI, and sonar. He holds an M.S.E. in Electrical and Computer Engineering from Johns Hopkins University, a B.S. from George Mason University, and B.A. degrees in Economics and Foreign Affairs from the University of Virginia. He is with the US Department of Defense and previously worked at NIST and the Naval Research Laboratory.