جستجوی استاد راهنمای دانشگاهی

Michał Paweł Michalak is an Assistant Professor at AGH University of Science and Technology in Kraków, affiliated with the Faculty of Geology, Geophysics and Environmental Protection and Department of Geoinformatics and Applied Informatics. His research spans computational geometry in geological modeling, machine learning applications in Earth sciences, statistical epidemiology, and ecclesiological dynamics. Doctoral degree from University of Silesia in Katowice Developed GeoAnomalia software suite combining C++, R, and ParaView Created unbiased risk metrics (WCSIR) for infectious disease surveillance Research focuses on: Subsurface geological modeling using combinatorial algorithms and machine learning; Spatial epidemiology emphasizing testing heterogeneity bias; Ecclesiological dynamics analyzing factional theological interactions. His 2020/37/N/ST10/02504 grant project received 'very good' evaluation for developing angular distance metrics in geological contacts. Scientific contributions include: 2025 Solid Earth paper on fault-related structure detection 2025 Frontiers in Public Health work on global pandemic risk evaluation 2023 AGH Rector award recipient Developer of open-source geological analysis tools Collaboration network includes Harvard University, Technische Universität Freiberg, and University of Texas at Austin. Currently teaching GIS modeling, optimization methods, and geoinformatics systems. Maintains a personal website with open data access.

• computational geometry
• machine learning in Earth sciences
• statistical methods in Earth sciences
• +۲ مورد دیگر

Iwona Kaczmarek is a Professor in the Department of Systems Research at the Wrocław University of Science and Technology's Faculty of Spatial Management and Landscape Architecture. Her work focuses on advancing spatial data infrastructure (SDI), geoinformatics, and machine learning applications in urban and regional planning. She leads interdisciplinary research integrating GIS, natural language processing (NLP), and graph neural networks to address challenges in spatial planning, policy analysis, and socio-economic modeling. Research interests include: Spatial data integration and interoperability Machine learning for geospatial analysis Semantic web technologies for open data Urban sustainability and transit-oriented development Policy text mining and stakeholder analysis Recent work emphasizes: 1. Combining media sentiment analysis with economic indicators during crises (2025) 2. GeoAI-driven quality of life predictions using graph neural networks (2023) 3. Knowledge graph extraction from spatial development plans (2023) 4. Harmonizing local planning documents via NLP (2022) Collaborations include projects like the EYE initiative analyzing remote sensing for economic trends and SDI implementations in academic contexts. Over 75 documented outputs highlight her contributions to geospatial innovation and policy-relevant research.

• Spatial Data Infrastructure (SDI)
• GIS Applications
• Machine Learning in Geoinformatics
• +۳ مورد دیگر

Jarosław Bosy is a Full Professor at the Institute of Geodesy and Geoinformatics at Wrocław University of Environmental and Life Sciences (WUELS), Poland. He served as Vice-Rector for Research and International Relations (2016–2020) and Rector (2020–2024). Since June 2024, he chairs the Committee on Geodesy of the Polish Academy of Sciences. He holds a PhD in Geodesy and Cartography (1996) and habilitation from AGH University of Science and Technology, Kraków. Awarded the Professor title in Technical Sciences by the Polish President in 2014. His research focuses on three core areas: GNSS-based reference frame realization at global/regional scales, GNSS meteorology (atmospheric state analysis via satellite signals), and GNSS applications in geodynamics. Key contributions include real-time troposphere delay models, integration of GNSS and numerical weather prediction (NWP), and development of the ASG-EUPOS positioning system in Poland. Bosy has authored 286 publications, supervised 23 PhD theses, and led 7 projects. His work bridges geodesy, meteorology, and geodynamics, with applications in climate monitoring, real-time positioning, and Earth system observation. He collaborates internationally, contributing to initiatives like GGOS and EPOS. His lab, GNSS&Meteo, develops services like real-time ZTD estimation and MSTID mitigation for precise positioning.

• Geodesy
• GNSS Meteorology
• Remote Sensing
• +۴ مورد دیگر

Ashraf A. Emam is a distinguished researcher and academic affiliated with Prince Sattam bin Abdulaziz University, specializing in earth sciences with a focus on Egypt's Southeastern Desert. His work integrates geological field studies with advanced remote sensing techniques to analyze mineral deposits, structural formations, and climate change impacts. His research spans geochemistry , petrogenesis , and sedimentological evolution , with significant contributions to understanding gold deposits, ophiolitic rock systems, and rare-metal granites. Emam pioneers methodologies like SAM-HIT for hyperspectral data transformation, bridging computational science and geology to decode Earth's processes through calcareous nannofossil assemblages and paleo-stress analysis. Publication trends reveal a strategic shift toward interdisciplinary remote sensing applications, particularly in converting multispectral to hyperspectral imagery for enhanced geological mapping. His work consistently targets high-impact journals like Lithos and Remote Sensing , emphasizing practical solutions for mineral exploration and climate reconstruction in arid regions. Emam secures substantial funding from elite institutions including the Medical Research Council, National Institutes of Health, and King Abdullah University of Science and Technology. His 97% co-authorship rate reflects deep international collaboration, while mentorship in earth sciences drives next-generation research despite no named students being publicly listed.

• Geology
• Remote Sensing
• Geochemistry
• +۴ مورد دیگر

Professor Jan Blachowski serves as Head of the Department of Geodesy and Geoinformatics at the Faculty of Geoengineering, Mining and Geology, Wrocław University of Science and Technology. He also holds a position as a Visiting researcher at the Department of Geoscience and Petroleum at the Norwegian University of Science and Technology (NTNU) under the NAWA Bekker programme. His professional standing is further evidenced by his membership in Academia Professorum Iuniorum for the 2024-2025 term and his role as Chief Specialist (mining and geology) at the Institute for Territorial Development (Marshal Office of the Dolnoslaskie Voivodeship). Professor Blachowski's research interests focus on the modeling and analysis of natural and anthropogenic systems using geographic information systems, with particular emphasis on deformation of mining and post-mining areas, mining surveying, satellite remote sensing, and spatial statistics. His work bridges geospatial technology with practical mining applications, creating valuable insights for environmental monitoring and land management in regions affected by mineral extraction. The interdisciplinary nature of his research connects geodesy, mining engineering, and environmental science to address complex challenges in post-mining landscape rehabilitation. An analysis of Professor Blachowski's recent publications reveals a strong trend toward integrating advanced geospatial technologies with mining impact assessment. His work increasingly incorporates machine learning techniques (particularly Random Forest algorithms), multi-sensor 3D mapping approaches, and sophisticated remote sensing methodologies to monitor and predict ground deformations in post-mining areas. The research demonstrates a clear progression from traditional geodetic monitoring toward more comprehensive, data-driven approaches that combine multiple data sources and analytical techniques for improved accuracy in deformation modeling and environmental impact assessment. Professor Blachowski leads the Geospatial Modeling and Analysis Laboratory and has served as Principal Investigator for numerous significant research projects, including Interreg Poland-Saxony Cooperation Programme, National Centre for Research and Development Polish German Cooperation Call, and multiple National Research Centre (NCN) OPUS projects. His research portfolio spans international collaborations with institutions in Germany, Norway, and other European countries, reflecting the global relevance of his work on mining impacts and geospatial analysis.

• Geographic Information Systems (GIS)
• Mining Deformation Analysis
• Remote Sensing
• +۵ مورد دیگر

Marcin Kulawiak serves as an Associate Professor in the Department of Geoinformation Systems within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His research bridges geospatial technologies with medical diagnostics, leveraging AI and UAV systems for practical applications. His research focuses on two primary domains: medical diagnostics AI where he develops open-source tools for hearing loss classification using pure tone audiometry data, and advanced remote sensing where he pioneers UAV-based hyperspectral imaging for environmental monitoring. His work integrates geoinformatics with healthcare innovation, particularly in creating accessible diagnostic support systems. The publication trends reveal a consistent trajectory toward AI-driven medical solutions since 2023, with three 2024 papers establishing methodological frameworks for hearing loss classification, followed by a 2025 open-source mobile application implementation. Concurrently, his remote sensing research explores novel UV-visible spectrum applications for vegetation analysis, demonstrating interdisciplinary technical versatility. No scientific awards were documented in the source material. As an academic supervisor, Kulawiak leads research projects in geoinformatics and medical AI development, though specific student names or grant details weren't provided. His work shows strong industry-academia collaboration potential through open-source medical applications and UAV remote sensing tools. His laboratory activities center on geospatial analysis systems and medical diagnostic software development, with the Geo-Survey Web-GIS platform representing foundational work in spatial cognition assessment before his pivot toward medical AI applications.

• Geoinformatics
• Spatial Cognition
• Medical Diagnostics AI
• +۲ مورد دیگر

Dr. Tomasz Berezowski serves as an Assistant Professor in the Department of Geoinformatic Systems at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology. His research spans hydrology, remote sensing, and geospatial analysis with particular focus on flood detection and wetland ecosystem monitoring. His research interests center on hydrological modeling, remote sensing applications for environmental monitoring, and water resource management. Dr. Berezowski has developed innovative methods for flood extent mapping using SAR imagery and has contributed significantly to understanding wetland hydrology and groundwater dynamics. His work bridges geospatial technology with practical environmental applications. Dr. Berezowski's recent publications demonstrate a strong focus on flood monitoring systems, with multiple 2024-2025 publications on SAR-based flood detection methods, hydrological modeling, and wetland ecosystems. His research shows consistent application of geospatial technologies to solve practical hydrological problems, particularly in Polish wetland environments like the Biebrza National Park. Dr. Berezowski leads the research project "Changes in hydrological and climatic characteristics and their impact on natural wetland ecosystems in the years 1900-2100" funded by the SONATA program (agreement UMO-2017/26/D/ST10/00665). He also participates in the "Marine port surveillance and observation system" project. His Floodsar software represents a significant contribution to open-source flood monitoring tools.

• Hydrology
• Remote Sensing
• Flood Detection
• +۴ مورد دیگر

Maciej Adamiak is an Assistant Professor at the Institute of Urban Geography, Tourism Studies and Geoinformation, Faculty of Geographical Sciences, University of Lodz. His research focuses on applying deep learning (DL) and machine learning (ML) methods to geospatial data analysis, remote sensing, and urban planning. He leads projects on topographic change detection via satellite imagery, illegal dumpsite identification using UAVs, and multimodal data integration for biodiversity protection. His goal is to bridge cutting-edge technology with academic and practical applications, emphasizing embedded AI solutions. Research Interests: Machine Learning/Deep Learning, Computer Vision, Geoinformatics, Remote Sensing, Spatial Analysis, and Data Engineering. Current projects include UAV-assisted waste monitoring and generative adversarial networks (GANs) for urban vegetation analysis. Adamiak’s work integrates advanced AI techniques with environmental and urban challenges, addressing topics like traffic analysis via satellite data and sound-based ecological studies. His recent publications span urban NDVI estimation, crime-education inequality in Rio, and participatory mobility indices like hiWALK/hiBIKE. He is affiliated with the University of Lodz and maintains active profiles on ResearchGate, Google Scholar, and LinkedIn. Office hours are Thursdays 10:00-12:00 at Kopcińskiego 31, Room 204F, Łódź.

• Machine Learning
• Deep Learning
• Computer Vision
• +۴ مورد دیگر

Dr. Przemysław Falkowski-Gilski serves as an Assistant Professor at the Department of Geoinformation Systems within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His research bridges geospatial engineering with computational intelligence, focusing on real-world applications in urban environments and sensor networks. His primary research domains include: Geoinformatics and GNSS positioning systems IoT infrastructure for smart cities Swarm intelligence optimization algorithms Edge computing resource allocation AI-driven data analysis for urban mobility Recent publications (2024-2025) reveal a cohesive research trajectory addressing critical challenges in smart city resource management through UAV-assisted edge computing, Android-based urban navigation, and sensor ontology integration. His work consistently applies advanced optimization techniques—such as Golden Jackal and Beetle Swarm algorithms—to solve practical problems in geospatial data processing and IoT systems, demonstrating strong interdisciplinary methodology.

• Geoinformatics
• Smart Cities
• IoT (Internet of Things)
• +۵ مورد دیگر

Tomasz Bieliński serves as an Assistant Professor in the Department of Geoinformatics Systems within the Faculty of Electronics, Telecommunications and Informatics at Gdańsk University of Technology. His academic profile demonstrates strong expertise in applying remote sensing technologies to hydrological research problems, particularly in flood monitoring and coastal mapping. His research interests span multiple interconnected domains including Remote Sensing , Hydrology , Machine Learning , and Geospatial Analysis . Bieliński's work focuses on developing innovative methods for processing satellite imagery, with particular emphasis on Synthetic Aperture Radar (SAR) technology for environmental monitoring applications. Analysis of his publication record reveals consistent contributions to flood mapping methodologies, bathymetry estimation, and satellite image processing techniques. His work shows increasing sophistication in integrating machine learning approaches with traditional remote sensing methods, particularly evident in his 2023 publication on Sentinel-2 derived bathymetry. Bieliński actively contributes to research projects including the Marine Port Surveillance and Observation System (MPSs), where he serves as a senior software developer working with mobile unmanned research units under the Norwegian and EEA Funds - Applied Research Program.

• Remote Sensing
• Hydrology
• Machine Learning
• +۴ مورد دیگر