committees

Jakub Nalepa (Senior IEEE Member) is currently an Associate Professor at the Silesian University of Technology, Poland. He is also the Scientific Advisor with KP Labs where he shapes the scientific and industrial AI objectives of the company related to, among others, Earth Observation (EO), on-board and on-the-ground satellite data analysis, machine learning, and image analysis. He has been pivotal in designing the on-board deep learning capabilities of the Intuition-1 mission (KP Labs), and has contributed to other missions, including CHIME and OPS-SAT (European Space Agency). His interests focus on (deep) machine learning, multi/hyperspectral data analysis, signal processing, remote sensing, and tackling practical challenges, which arise in EO to deploy scalable EO solutions. Dr. Nalepa was the General Chair of the HYPERVIEW Challenge at IEEE ICIP 2022 focusing on the estimation of soil parameters from HSIs on board Intuition-1, and the General Chair of the HYPERVIEW 2 Challenge at the Explainable AI for Space (EASi) Workshop at ECAI 2025.

Przemyslaw Biecek is Director of the Centre for Credible AI at the Warsaw University of Technology and a Full Professor in the Faculty of Mathematics, Informatics and Mechanics at the University of Warsaw. His research focuses on Model Science—responsible and explainable artificial intelligence—with emphasis on model interpretability, controllability, and verifiability. He has authored or co-authored more than 200 scientific publications, including books and monographs, and has led numerous research and applied projects on interpretable predictive modelling.is Director of the Centre for Credible AI at the Warsaw University of Technology and a Full Professor in the Faculty of Mathematics, Informatics and Mechanics at the University of Warsaw. His research focuses on Model Science—responsible and explainable artificial intelligence—with emphasis on model interpretability, controllability, and verifiability. He has authored or co-authored more than 200 scientific publications, including books and monographs, and has led numerous research and applied projects on interpretable predictive modelling.

Marek Kraft is an assistant professor at the Poznań University of Technology (PUT), where he leads the PUT Computer Vision Lab. The lab focuses on developing intelligent algorithms for extracting meaningful information from images, videos, and signals. This work has applications across diverse fields, including Earth observation, agriculture, and robotics (including space robotics). Kraft's current research involves close-range remote sensing image analysis, specializing in small object detection for environmental monitoring. He also collaborated on European Space Agency projects aimed at extraterrestrial rover navigation and autonomy, making use of his knowledge of embedded systems. His research has led to over 80 publications and several patents, and a history of securing competitive research grants. Kraft is a member of IEEE and ACM.

Nicolas Longépé received the M.Eng. degree in electronics and communication systems and the M.S. degree in electronics from the National Institute for the Applied Sciences, Rennes, France, both in 2005, and the Ph.D. in signal processing and telecommunication from the University of Rennes I, Rennes, France, in 2008. From 2007 to 2010, he was with the Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Tsukuba, Japan. From 2010 to 2020, he was with Collecte Localization Satellites (CLS), Plouzané, France, where he was a Research Engineer with Space Observation Division. Since September 2020, he has been an Earth Observation Data Scientist, Φ-Lab Explore Office, European Space Research Institute (ESRIN), European Space Agency (ESA), Frascati, Italy. His main scientific interests include EO remote sensing and digital technologies such as Machine (Deep) Learning. He has been working on the development of innovative SAR-based applications for environmental and natural resource management (ocean, mangrove, land and forest cover, soil moisture, snow cover, permafrost) and for maritime security (oil spill, sea ice, iceberg, and ship detection/tracking). At the Φ-Lab, he is particularly involved in the development of innovative EO missions where Artificial Intelligence is directly deployed at the edge (on the spacecraft).

Evridiki Ntagiou is a Computer and Electrical Engineer, with a MSc on Automation and Robotics. She completed her PhD in a joint partnership of the European Space Agency, the commercial operator Surrey Satellite Technology (SSTL) and the University of Surrey, where she focused on the use of AI for optimal mission planning of real constellation missions. She has numerous publications, primarily in the areas of automated planning, computer vision applied to space robotics and space safety missions, as well as AI assistants for mission operations and data management & governance topics.

Lukasz Tulczyjew received his B.Sc. (2020), M.Sc. (2021) and Ph.D. (2026) from Silesian University of Technology (SUT). He is currently a Senior AI Specialist at KP Labs (Gliwice, Poland), where he focuses mainly on hyperspectral image analysis including both supervised and unsupervised segmentation, classification and unmixing. He was key in the projects funded by ESA and focusing on hyperspectral image analysis using classic and deep machine learning algorithms. In general, his research and engineering interests include machine learning (which focal point being deep learning) and high-performance Python programming, especially in the context of deep learning. Łukasz was the Technical Chair of the HYPERVIEW Challenge at IEEE ICIP 2022 tackling the estimation of soil parameters from hyperspectral images on board Intuition-1, to maintain farm sustainability through improving the agricultural practices.

Agata M. Wijata received her M.Sc. (2015) and Ph.D. (2023) degrees in Biomedical Engineering at the Silesian University of Technology, Poland. Currently, she works as an Assistant Professor at the Silesian University of Technology and as a Machine Learning Researcher at KP Labs, where she has been focusing on hyperspectral image analysis. Her areas of research interest include medical image processing, multi- and hyperspectral image processing, multimodal data processing, and artificial intelligence. Agata has been contributing to the Copernicus Hyperspectral Imaging Mission for the Environment (European Space Agency) and Intuition-1 Mission (KP Labs) from the artificial intelligence and data processing perspectives. Agata is involved in the WoundScanning project from the perspective of multimodal image processing. She is a Member of IEEE.

Krzysztof Kotowski received his MSc (2016) and PhD (2022) degrees in computer science from the Silesian University of Technology, Gliwice, Poland. He also holds an MSc (2016) in digital signal processing from Cranfield University, UK. Currently, he leads the AI department of KP Labs, Gliwice, Poland. He has 10 years of professional R&D experience in machine learning and algorithms for industrial machine vision, medical imaging, and signal processing in EEG and satellite telemetry. He is a lead organizer of the https://www.kaggle.com/competitions/esa-adb-challenge ESA Spacecraft Anomaly Challenge accepted for the special session at the ECML PKDD 2025 conference. He is the main author of top algorithms for brain tumor segmentation awarded in BraTS 2021, BraTS 2022, and FeTS 2022 competitions, and for protein disorder prediction in the CAID-3 competition. He is a laureate of the Witold Lipski Award 2024 for outstanding young Polish applied computer scientists.