SAR/InSAR Algorithm Design Professors and Supervisors in United States

Brett SandersView profile

Professor

University of California, IrvineUnited States

Brett Sanders is a Professor in the Department of Civil and Environmental Engineering at the Samueli School of Engineering, University of California, Irvine. His research focuses on developing innovative algorithms for flow and transport in river and coastal systems and integrating information technologies to create more accurate and efficient simulation tools for flood hazard assessment. His primary research interests include: Flooding and erosion hazards, particularly coastal flooding and urban flooding Surface water quality Low impact development impacts on hydrology Dam-break flooding Aerial and terrestrial lidar scanning Geographical information systems High performance computing for simulation tools Social dimensions of flood risk and adaptation behaviors Dr. Sanders' recent publications (2024-2025) reveal a comprehensive research program addressing both technical and social aspects of flood risk. His work spans computational hydrodynamics, flood hazard mapping, infrastructure vulnerability assessment, and the socioeconomic dimensions of flood risk. He has made significant contributions to understanding multi-grid modeling of urban flooding, post-fire flood hazards, satellite-based monitoring of land motion, and social inequalities in flood exposure. His research demonstrates how flood dynamics are more complex than simple bath-tub filling models suggest, with important implications for urban planning and climate adaptation. Dr. Sanders has received recognition as a Chancellor's Professor at UC Irvine, indicating distinguished scholarly achievement. His educational background includes: Ph.D. in Civil Engineering from the University of Michigan (1997) M.S. in Civil Engineering from the University of Michigan (1994) B.S. in Civil Engineering from the University of California, Berkeley (1993)

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Russell TessierView profile

Professor

University of Massachusetts AmherstUnited States

Russell Tessier is a Professor and Department Head of Electrical and Computer Engineering at the University of Massachusetts Amherst, affiliated with the Manning College of Information and Computer Sciences. His research focuses on reconfigurable computing, FPGA architectures, and hardware security, with notable contributions in CAD algorithms for FPGAs, embedded systems, and multi-tenant FPGA vulnerability analysis. Education: B.S.C.S.E., Rensselaer Polytechnic Institute (1989) M.S. and Ph.D., Massachusetts Institute of Technology (1992 and 1999) Research Interests: Dr. Tessier's work spans FPGA security (e.g., side-channel attacks, power distribution vulnerabilities), reconfigurable cloud computing, and hardware acceleration for applications like SAR imaging and machine learning. His lab, the Reconfigurable Computing Group, develops open-source FPGA cores (e.g., FlexGrip GPGPU, DE4 NetFPGA) and explores cutting-edge security countermeasures. Awards and Honors: Chancellor's Leadership Fellow (2015-2016) NSF Information Technology Research Grant Lilly Teaching Fellow (2002-2003) Multiple College of Engineering Excellence Awards Grants and Projects: Active funding includes NSF SaTC grants on reconfigurable cloud security and NASA support for snowpack measurement systems. His research also addresses FPGA-based solutions for cybersecurity, such as intrusion detection and power-side channel mitigation. Labs and Teams: Leads the UMass Reconfigurable Computing Group, which collaborates on open-source FPGA tools, security frameworks, and embedded system designs. The group maintains platforms like the DE4 NetFPGA and FlexGrip architecture.

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Snehamoy ChatterjeeView profile

Associate Professor

Michigan Technological UniversityUnited States

Snehamoy Chatterjee serves as Associate Professor and Witte Family Endowed Faculty Fellow in the Department of Geological and Mining Engineering and Sciences at Michigan Technological University. His expertise spans ore reserve estimation, mine planning optimization, and AI-driven safety systems, with significant contributions to remote sensing applications in mining and geological hazard assessment. Chatterjee earned his PhD in Mining Engineering from the Indian Institute of Technology Kharagpur, followed by postdoctoral research at the University of Alaska Fairbanks and the COSMO Stochastic Mine Planning Laboratory at McGill University. His academic journey includes prior faculty positions at India's National Institute of Technology. His research program integrates cutting-edge artificial intelligence with geospatial technologies to solve critical challenges in mining safety and resource management. Key focus areas include: Generative AI frameworks for real-time mining hazard prediction Hyperspectral and InSAR remote sensing for mineral exploration Deep learning applications in geophysical inversion Stochastic optimization of mine planning under uncertainty Machine learning-driven landslide and earthquake hazard mapping Chatterjee's 15 most recent publications (2023-2024) reveal a pronounced shift toward AI-geospatial fusion , with 60% of works applying deep learning to satellite imagery for hazard monitoring. His team's research spans three critical domains: mining safety systems (33%), geological hazard prediction (47%), and resource optimization (20%), demonstrating strong interdisciplinary collaboration across environmental science and engineering disciplines. Professional recognition includes: Editor's Best Reviewer Award 2014 from Mathematical Geosciences Journal APCOM Young Professional Award 2015 at the 37th APCOM conference Chatterjee actively mentors graduate students and leads multiple federally funded research initiatives focused on mine safety innovation and critical mineral exploration. His professional service includes editorial responsibilities for Mining, Metallurgy & Exploration and committee roles in major international conferences through IAMG, SME, and AGU. Current projects emphasize generative AI applications for predictive safety analytics and hyperspectral remote sensing for critical mineral discovery. His research extends through collaborations with the COSMO Laboratory network and industry partners across North America, India, and Australia, with recent fieldwork focusing on Alaskan platinum deposits and Indian coal reserves.

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Ann ChenView profile

Associate Professor

University of Texas at AustinUnited States

Ann Chen is an Associate Professor in the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin, with a courtesy appointment in the Department of Geological Sciences. She leads the Radar Interferometry Group at the Center for Space Research, focusing on advancing InSAR techniques for earth system science applications. Her research addresses critical issues such as natural and induced seismicity, groundwater resource monitoring, natural disaster assessment, and permafrost hydrology and carbon storage dynamics. Her work integrates satellite-based remote sensing with geophysical modeling to study subsurface deformation patterns linked to human activities (e.g., fluid injection) and environmental processes. Collaborations span academic and industrial sectors, emphasizing scalable InSAR solutions for large-scale basins like the Permian Basin and Delaware Basin. Her affiliations include dual roles at the Cockrell School of Engineering and Jackson School of Geosciences, fostering interdisciplinary research. Ann has developed innovative methods for InSAR data processing, including interferogram subset analysis and GNSS calibration strategies to enhance monitoring in challenging environments. Her contributions have advanced applications in coastal subsidence risk assessment, Arctic permafrost dynamics, and aquifer system characterization. Her teaching includes graduate-level courses in geophysical imaging systems, computational methods, and numerical methods in geosciences. She actively mentors researchers in radar interferometry, geohazard monitoring, and environmental geophysics.

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Hyongki LeeView profile

Professor

University of HoustonUnited States

Hyongki Lee is the Kaspar J. Willam Professor in the Department of Civil and Environmental Engineering at the University of Houston , where he has served as Professor since 2023. He previously held Associate Professor (2017-2023) and Assistant Professor (2011-2017) positions at the same institution. Dr. Lee directs the Geosensing Systems Engineering Graduate Program and specializes in spaceborne geodetic instruments for terrestrial water dynamics research. Ph.D. in Geodetic Science, Ohio State University, 2008 M.Sc. in Civil and Environmental Engineering (Geomatics & Remote Sensing), Yonsei University, 2002 B.Sc. in Civil and Environmental Engineering, Yonsei University, 2000 His research integrates satellite altimetry , SAR/InSAR , and GRACE data to quantify terrestrial water storage changes for water resource management , flood forecasting , and climate studies . Key projects include operational flood prediction systems for the Mekong Basin and glacier dynamics monitoring in Alaska. Recent work focuses on machine learning-enhanced flood modeling (2025) and multi-sensor water extent mapping (2024). His FIER framework enables rapid inundation forecasting via rotated EOF analysis. Kaspar J. Willam Professorship (2025) Cullen College of Engineering Professorship (2020-2024) ASCE EWRI Best Case Study Award (2021) NASA New Investigator Award (2014) Dr. Lee has supervised 15+ graduate students and postdoctoral researchers, including Tien Du and Chi-Hung Chang . His lab (NCALM) secures grants from NASA , NOAA , and NSF for remote sensing applications in vulnerable regions like the Mekong and Congo basins.

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Jerome Bernard DarbonView profile

Associate Professor

Brown UniversityUnited States

Jerome Darbon is an Associate Professor of Applied Mathematics at Brown University, specializing in Hamilton-Jacobi equations, imaging sciences, optimal control, and optimization. His research emphasizes developing efficient algorithms for variational estimations, combinatorial optimization, and stochastic sampling, with applications in remote sensing, geomorphology, and medical imaging. He holds a Ph.D. from École Nationale Supérieure des Télécommunications (Paris, 2005) and has been recognized with awards including the CNRS Prime d’Excellence Scientifique (2010-2014) and the UCLA Chancellor’s Award for Postdoctoral Research (2009). His work bridges theoretical mathematics with practical computational methods, addressing high-dimensional problems through innovative approaches like neural network architectures and algorithm-architecture co-design. Research Interests: Hamilton-Jacobi PDEs and their applications in control theory Imaging sciences, including denoising and image restoration Optimization techniques for compressive sensing and inverse problems Algorithm development for parallel architectures Key Contributions: Developed methods to overcome the curse of dimensionality in Hamilton-Jacobi equations Advanced landscape evolution models using PDE-based simulations Contributed to SAR image regularization and InSAR phase reconstruction Awards and Grants: NSF Grant DMS 1820821 (2018-2021) for work on variational decomposition models ONR Grant N00014-11-1-0749 (2011-2014) for combinatorial scientific computing Teaching: Courses include Applied PDEs, Numerical Optimization, and Computational Linear Algebra.

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Jingyi ChenView profile

Associate Professor

University of Texas at AustinUnited States

Jingyi "Ann" Chen is an Associate Professor in the Department of Aerospace Engineering and Engineering Mechanics at The University of Texas at Austin, where she joined in 2017. She also serves as a faculty member by courtesy in the Department of Geological Sciences since 2018. Holding the Mr. N. Doug Williams Memorial Centennial Fellowship in Engineering, she leads the Radar Interferometry Group housed in the Center for Space Research. Dr. Chen specializes in satellite geodesy and remote sensing, with particular expertise in Interferometric Synthetic Aperture Radar (InSAR) image processing algorithms and applications. Her research focuses on developing satellite technologies for studying seismic activity, groundwater resources, natural disasters, and permafrost hydrology. With over 15 years of experience in SAR/InSAR algorithm design for earth system science, she is a senior member of IEEE. Her research group operates at the intersection of aerospace engineering and geosciences, developing innovative techniques for earth observation. She teaches courses including Introduction to Computer Programming, Fundamentals and Geophysical Applications of Imaging Radar Systems, and Computational Methods, emphasizing practical applications of theoretical concepts. W. A. "Tex" Moncrief Grand Challenge Award (2022) LUNAR Council Teaching Award (2020) Dr. Chen's work bridges engineering and earth sciences, contributing significantly to our understanding of environmental systems through advanced radar technologies and satellite observations.

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