Dr. Thomas Jarmer

Dr. Thomas Jarmer is a Senior Scientist at the Institute of Computer Science at Osnabrück University, Germany, where he is a member of the Remote Sensing and Digital Image Analysis research group. His research focuses on remote sensing and its applications to environmental monitoring and precision agriculture, with particular expertise in hyperspectral data analysis, UAV-based remote sensing, field and laboratory spectroscopy, and the remote sensing-based characterization of soil and vegetation properties.

He received his Ph.D. from the University of Trier, where his research explored the use of spectrometry and satellite imagery for the analysis of soil properties in semi-arid and arid environments. His academic career has also included research positions at the Free University of Berlin and the Technion – Israel Institute of Technology.

Over more than two decades of research, Dr. Jarmer has contributed to numerous studies combining Earth observation, image analysis, and data-driven methods for agricultural and environmental applications. His recent work includes UAV-based crop and weed monitoring, precision agriculture, biodiversity monitoring, crop mapping, and the application of machine learning and deep learning to remote sensing data. 

Dr. Justin Dauwels

Dr. Justin Dauwels is an Associate Professor at the Delft University of Technology (TU Delft) in the Netherlands, affiliated with the Signal Processing Systems group in the Department of Microelectronics and serving as co-Director of the Safety and Security Institute. His research focuses on data analytics with key applications in intelligent transportation systems, autonomous systems, and the analysis of human behavior and physiology.

He earned his Ph.D. in electrical engineering from the Swiss Federal Institute of Technology (ETH) in Zurich, following which he held research and postdoctoral positions at institutions including the RIKEN Brain Science Institute and the Massachusetts Institute of Technology (MIT).

Over his academic career, he has contributed extensively to signal processing, machine learning, and data-driven transportation through leadership roles in IEEE technical committees, editorial boards, and international conferences. His lab's work bridges academia and industry, resulting in technologies adopted by startups, agencies, and multinational corporations across healthcare, smart vehicles, and logistics.

Dr. Francisco Siles

Dr. rer. nat. Francisco Siles Canales is a Full Professor at the University of Costa Rica (UCR), where he is the founder and coordinator of the Pattern Recognition and Intelligent Systems Laboratory (PRIS-Lab), and serves as Director of both the Center for Research in Human Movement Sciences (CIMOHU) and the Graduate Program in Electrical Engineering (PPIE). He is also an affiliated researcher at the Center for Research in Surgery and Cancer (CICICA) and a faculty member in the Master's Program in Bioinformatics and Systems Biology. His research focuses on artificial intelligence, computer vision, and pattern recognition, with core applications in biomedical engineering, surgical robotics, and high-performance physical modeling.

He earned his doctorate in Natural Sciences (Dr. rer. nat.) in Pattern Recognition and Intelligent Systems from the Technical University of Munich (TUM), Germany, following his B.Sc. and M.Sc. in Electrical Engineering from the University of Costa Rica. His academic trajectory includes postdoctoral research appointments in Computational Biology at the University of Kansas (USA) and in Computational Optical Physics and 3D Reconstruction at the University of Valencia (Spain), alongside collaborative research initiatives with the LHCb experiment at CERN.

Over more than two decades of research and academic leadership, Dr. Siles has authored over 65 peer-reviewed scientific publications and spearheaded transdisciplinary consortia bridging advanced computing with healthcare and physics. An IEEE Senior Member, he serves as Principal Investigator for major research initiatives, including BreastInsight (democratizing 3D tomosynthesis precision for public breast cancer screening via explainable AI), DeepDXA with the University of Maryland (Baltimore), and GPU-accelerated algorithms for LHCb-CERN. His work is dedicated to developing trustworthy AI and digital twins that translate computational innovations into clinical practice and public health solutions.

Dr. Katya Rodríguez Vásquez 

Dr. Katya Rodríguez Vásquez is a full-time Senior Researcher at the Institute of Research in Applied Mathematics and Systems (IIMAS) of the National Autonomous University of Mexico (UNAM). She earned her degree in Computer Engineering from the Faculty of Engineering at UNAM in 1994 and subsequently pursued doctoral studies from 1995 to 1999 at the University of Sheffield, United Kingdom, in the field of Systems Engineering. Her research focuses on artificial intelligence, evolutionary and bio-inspired algorithms, multi-criteria optimization combined with parallel processing, and their applications in diverse areas such as Hydraulic Engineering, Biology, and Economics, among others. She has supervised doctoral, master's, and undergraduate theses and mentored high school students. She has published in prestigious conferences and journals in her research areas. She is a regular member of the Mexican Academy of Computing (AMEXCOMP) and the Mexican Academy of Informatics, A.C. (AMIAC) and the Mexican Academy of Sciences (AMC), as well as the Association of Computing Machinery (ACM). She belongs to the National System of Researchers, served as Academic Secretary of her institute from September 2020 to December 2024, and participated in the Technical Advisory Committee of the Preliminary Electoral Results Program (COTAPREP) for the 2020-2021 and 2023-2024 Electoral Processes in Mexico.

Dr. Bonny Banerjee

Dr. Bonny Banerjee received M.S. in Electrical Engineering and Ph.D. in Computer Science (major AI, minor Cognitive Science) from the Ohio State University, USA. Just after graduating with Ph.D., he spent 3.5 years (2007-2011, through the Great Recession) leading the research at a startup, which resulted in a number of patents, substantial investor funding, and launch of a commercial product for the end-user which received wide media coverage. The intellectual property was acquired by the leading company in the field. For the last 15 years, he has served as a faculty at institutions of higher education, and as a consultant for small and large businesses in the U.S. and abroad. Dr. Banerjee holds 8 patents and has published over 75 peer-reviewed articles in reputed journals and conference proceedings on AI agents and related areas. He received the Best Paper Award at a NeurIPS 2023 Workshop. He has served as the Principal Investigator of research projects funded by the U.S. National Science Foundation, Department of Homeland Security, Army, St. Jude Children’s Research Hospital, and startup investors. He serves on the editorial boards of IEEE Transactions on Cybernetics, Neural Networks (Elsevier), and Brain Theory and Intelligence Science (Springer Nature) journals. For more information, please visit: https://www.linkedin.com/in/bonnybanerjee/