Prof. Dr.-Ing. Jörg Blankenbach holds the Chair of Construction Informatics and Geoinformation Systems at RWTH Aachen University's Geodetic Institute. His research focuses on the integration of digital technologies in civil engineering and geospatial systems. Current affiliations include: Chair of Construction Informatics and Geoinformation Systems, RWTH Aachen University Geodetic Institute, RWTH Aachen University Research interests span digital construction management, geospatial data modeling, BIM-GIS integration, and smart infrastructure systems.
Prof. Hansjörg Kutterer is a Professor and Dean at the KIT-Department of Civil Engineering, Geo and Environmental Sciences at Karlsruhe Institute of Technology (KIT). His primary affiliation is with KIT's Department of Civil Engineering, Geo and Environmental Sciences. He leads geodetic research initiatives focusing on Earth observation systems, atmospheric modeling, and geophysical data analysis. His research emphasizes advanced applications of GNSS, InSAR, and satellite gravimetry for monitoring climate-related phenomena such as water vapor dynamics, terrestrial water storage changes, and ground motion patterns. Key projects include developing machine learning-enhanced models for tropospheric delay corrections and integrated water vapor estimation in the Upper Rhine Graben region. Prof. Kutterer actively contributes to international geodetic frameworks like the Global Geodetic Observing System (GGOS), particularly through DA-CH regional collaborations. His work bridges geodetic methodologies with interdisciplinary challenges in climate science and environmental engineering. He oversees departmental operations as Dean, fostering innovation in geospatial education and infrastructure. His technical expertise spans geodetic deformation analysis, statistical robust estimation, and the integration of geophysical models with observational data.
Dr. Yizi Chen is a Researcher affiliated with the Professorship for Cartography at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. Their work focuses on advancing cartographic techniques through AI-driven methods, historical map analysis, and geospatial technologies. Key contributions include automated map vectorization, semantic segmentation of historical maps, and integrating multimodal data for robotic systems. They have published extensively in top-tier journals and conferences, addressing challenges in deep learning applications for geomatic engineering. Education details are not explicitly provided in the text. Research interests include semantic segmentation, generative AI for cartography, and steganography in image translation. Notable publications span topics from eye-tracking segmentation to urban land use mapping, reflecting a strong interdisciplinary approach. Dr. Chen collaborates on projects involving historical map digitization and benchmarking datasets for computer vision tasks. No awards or grants are mentioned. Their work contributes to advancing geomatic engineering through innovative solutions in digital mapping and spatial data analysis.
Xiaoye Liu is a Senior Lecturer at the School of Surveying and Built Environment, University of Southern Queensland. With a PhD from Monash University and over 20 years of tertiary teaching experience, she specializes in geomatic engineering, remote sensing, and spatial data analysis. Her role includes teaching courses like Photogrammetry and Remote Sensing, Urban and Regional Planning, and GIS practices, alongside administrative duties as Program Coordinator for the Associate Degree of Spatial Science. Research interests include GIS, LiDAR-based digital terrain modeling, 3D visualization, and applications in natural resource management and carbon accounting. Professional memberships: Member of the Surveying and Spatial Science Institute (SSSI) and the International Global Navigation Satellite Systems (IGNSS).
Jim Chen is a Professor at the Department of Marine and Environmental Sciences and holds an affiliation with the College of Engineering's Civil and Environmental Engineering at Northeastern University. His research focuses on coastal engineering and science, emphasizing numerical modeling to address coastal resiliency and sustainability, particularly in the context of hurricanes and sea-level rise. Education details are not explicitly provided in the text, but his expertise includes advanced modeling techniques applied to coastal systems. His work integrates field observations with computational methods, such as deep learning and physics-informed neural networks, to analyze wave dynamics, sediment transport, and vegetation effects on coastal processes. Key research areas include hurricane impact analysis on wetlands and engineered infrastructure, living shoreline restoration effectiveness, and the morphological evolution of coastal systems. His studies often involve rapid deployment of sensors during storms (e.g., Hurricane Laura) to monitor wave, current, and sediment dynamics, contributing to disaster preparedness and mitigation strategies. Notable collaborations include projects with the Shinnecock Indian Nation, Gandys Beach (New Jersey), and Chesapeake Bay, focusing on sustainable coastal management. His work bridges engineering and environmental science to enhance coastal resilience in vulnerable regions.
Federica Sandrone is a Lecturer at the School of Architecture, Civil and Environmental Engineering (ENAC) at École Polytechnique Fédérale de Lausanne (EPFL), where she also serves as a Scientist at the Laboratory of Experimental Rock Mechanics (LEMR) within the Institute of Civil Engineering. Her academic career spans over 15 years with continuous contributions to tunnel engineering and rock mechanics research. Her research focuses on the intersection of rock mechanics and tunnel engineering, with particular expertise in tunnel pathology analysis, TBM performance in challenging geological conditions, and long-term tunnel behavior. Sandrone's work bridges theoretical analysis with practical engineering applications, addressing real-world problems in tunnel infrastructure management and maintenance. Her research methodology combines field investigations, laboratory testing, and numerical modeling to understand complex geomechanical behaviors. Analysis of her recent publications reveals a consistent focus on tunnel inspection methodologies, TBM performance prediction in difficult ground conditions, and the long-term behavior of tunnel structures. Her work has evolved from fundamental tunnel pathology studies to more advanced applications involving GIS integration, probabilistic modeling, and modern inspection techniques including laser scanning and image analysis. Engineer at SBB-Infrastructure (2008-present) responsible for Tunnels Management and Maintenance Assistant for Tunnel Engineering courses (2007-present) PhD supervision including Erika Paltrinieri's 2015 thesis on TBM performance Development of tunnel inspection methodologies and condition assessment procedures Her teaching activities include courses in Rock Mechanics and Underground Construction, where students learn about the mechanical behavior of rock materials, tunnel excavation and support design, planning and management of underground works, and risk assessment in tunnel construction.
Alper Yilmaz is Professor with appointments in Civil Environmental and Geodetic Engineering and Computer Science and Engineering (courtesy) Departments at The Ohio State University. He serves as Director of PCVLab and is currently interim president for the ISPRS Technical Commission II. Dr. Yilmaz has been inducted to the U.S. National Academy of Inventors in 2020 and is a Fellow of the American Society for Photogrammetry and Remote Sensing (ASPRS) and senior member of IEEE. Dr. Yilmaz's research focuses on biomimetic navigation systems for unmanned systems, mining anomalies in multi-physics and multi-dimensional data for surveillance, and learning geospatial information for scene understanding. His expertise spans Deep Learning, Reinforcement Learning, Computer Vision, Photogrammetry, Data-centric Surveillance, Collaborative Swarm Navigation, and Indoor Positioning Systems. His recent work on biomimetic navigation systems has resulted in UbiHere Inc., an Ohio State University spin-off founded in 2018. Dr. Yilmaz has served as Editor-In-Chief for the Photogrammetric Engineering and Remote Sensing Journal (PE&RS) between 2016-2024, during which the journal's impact factor increased to its highest since 1934. He previously served as Associate Editor for Computer Vision and Image Understanding Journal (2014-2016) and Machine Vision and Applications Journal (2006-2011). Outstanding Service Award (2022, ASPRS) Innovator of Year (2020, OSU) Presidential citation (2019, ASPRS) Masao Horiba Award honorable mention (2016, Japan) Lumley Interdisciplinary Research Award (2015, OSU) Lumley Research Award (2012, OSU) Top 1% most cited researcher in Artificial Intelligence & Image Processing and Geological & Geomatics Engineering (2024) Dr. Yilmaz has advised 29 Ph.D. and 15 M.Sc. students to completion on topics ranging from photogrammetry, machine learning, and computer vision. His research has received over $13M in extramural funding from NASA, NSF, DOD, DOE, NIH, and industry partners including Ford Motor Company, Trimble Inc., and UbiHere Inc. PCVLab, located in Bolz Hall Suite 233, features a sensor calibration room, state-of-the-art workstations with GPUs for deep learning studies, and small robotic systems including ground and aerial units.
Bozidar Stojadinovic is a Full Professor and Chair of Structural Dynamics and Earthquake Engineering at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering. He leads the Institute of Structural Engineering and previously held professorships at UC Berkeley and the University of Michigan. His research focuses on community disaster resilience, seismic design, and experimental methods like hybrid simulation. Education: PhD in Civil Engineering, UC Berkeley (1995) MS in Civil Engineering, Carnegie-Mellon University (1990) BS in Civil Engineering, University of Belgrade (1988) Research Interests: Performance-based probabilistic resilience evaluation of civil infrastructure. Earthquake engineering, including seismic isolation and response modification techniques. Development of experimental testing methods, such as hybrid simulations for dynamic structural analysis. Awards: ICE Journal John Henry Garrood King Medal (2023) ACI Chester Paul Siess Award (2017) NSF CAREER Award (1999) Teaching & Advising: Teaches courses on seismic design and structural dynamics at ETH. Advised 49 doctoral students to date. His work integrates advanced methodologies to enhance structural resilience against natural hazards. Labs/Teams: Leads ETH's Institute of Structural Engineering, advancing research in seismic protection and infrastructure resilience through experimental and computational innovations.
Dr. Yun Zhang is a Professor and Canada Research Chair in the Department of Geodesy and Geomatics Engineering at the University of New Brunswick. He holds a PhD from the Free University of Berlin and has pioneered research in remote sensing, image processing, and computer vision since 2000. His patented technologies are licensed to global companies including PCI Geomatics and DigitalGlobe. Research Focus: Optical/radar image processing, digital photogrammetry, AI applications in geomatics, and sensor fusion for UAV systems. His work enables advanced geospatial analysis across environmental, urban, and defense sectors. Distinctions: First Giuseppe Inghilleri Award (ISPRS 2012) NSERC Synergy Innovation Award from Governor General of Canada (2011) ASPRS Talbert Abrams Grand Award (2005) Featured in CFI 20th Anniversary Book for breakthrough innovations Technology Impact: Solutions deployed by NASA, USGS, Google Earth, and DND Canada across five continents. Recognized among top 9 Canadian research achievements in AUTM's global case studies alongside MIT and Stanford innovations.
Ramon Arrowsmith is a Professor at Arizona State University's School of Earth and Space Exploration (SESE). His research focuses on earthquake geology, tectonic geomorphology, and active faulting, with a particular emphasis on leveraging high-resolution topography through initiatives like OpenTopography. He has over 35 years of experience in paleoseismology, geomorphic mapping, and fault zone analysis. Arrowsmith has held administrative roles such as Deputy Director of SESE and associate directorships in graduate studies and geological sciences departments. His work integrates remote sensing, lidar technology, and robotics to address geological hazards and landscape evolution. Key projects include the QUAKES mission for topographic data collection and the development of low-cost seismic tools like ShakeBot. His research spans global regions, including the San Andreas Fault, Pamir-Tien Shan collision zone, and volcanic fields in Arizona and Mexico. Arrowsmith's recent publications highlight advancements in fault slip modeling, seismic hazard assessment, and open-access geospatial data platforms. His contributions to education include courses on field geology and computational methods in earth sciences. Collaborations with international teams and interdisciplinary projects underscore his commitment to advancing geoscience through innovation and accessibility.
Dr. Jae Sung Kim is an Assistant Professor in the Department of Civil, Environmental, and Geospatial Engineering at Michigan Technological University (MTU). He holds a PhD in Geomatics from Purdue University and teaches courses in photogrammetry, UAV mapping, and geospatial technology. His research focuses on geospatial technologies, including remote sensing, GIS, and their applications in agriculture, environmental science, and planetary studies. PhD: Geomatics, Purdue University MSCE: Civil Engineering, Purdue University ME: Civil Engineering, Korea University BE: Civil Engineering, Korea University Dr. Kim’s research interests span photogrammetry, remote sensing, geodesy, and geospatial cyberinfrastructure. He develops tools for agricultural water management (FARMs system) and landslide analysis. His work often utilizes open-source geospatial technologies and integrates historical aerial photography with modern GIS systems. His recent publications include studies on volcanic lava flow modeling (2025), winter vegetation detection via remote sensing (2024), and automated orthorectification of archival aerial photos (2022). These reflect his expertise in combining traditional geospatial methods with cutting-edge technologies. Dr. Kim serves as an Associate Editor for the Journal of Applied Remote Sensing and Assistant Director of the Photogrammetric Applications Division at ASPRS. He has also contributed to watershed delineation tools and web-based water monitoring systems using open-source frameworks.
Dr. Hung Cao is an Assistant Professor of Computer Science at the University of New Brunswick, where he directs the Analytics Everywhere Lab. His work focuses on interdisciplinary research in Cyber-Physical Systems (CPS), IoT, Edge/Fog/Cloud Computing, and Explainable AI, addressing societal challenges through data-driven solutions. Prior roles include PostDoc Fellow and Data Scientist at the People in Motion Lab, UNB, and Lecturer/Researcher at Vietnam National University. He holds a Ph.D. in Geomatics Engineering (specializing in Data Science) from UNB (2020), an M.Sc. in Computer Science from University College Dublin (2015), and a B.Eng. from Vietnam National University (2011). Research interests span Smart Cities, Embedded AI, TinyML, Federated Learning, and Real-time Systems. He has led projects with Cisco, NB Power, and other industry partners to develop scalable analytics frameworks for IoT applications. Dr. Cao actively contributes to technical communities (IEEE Smart City, Edge Computing, etc.), serving as a reviewer for journals and conferences, and a Topic Editor for Electronics Journal . His innovations include the Analytics Everywhere framework for spatio-temporal data analysis, MACeIP platform for smart cities, and energy-efficient IoT systems for environmental monitoring. Current work emphasizes human-centered AI for healthcare diagnostics and industrial inspection systems.
Joni Storie is an Associate Professor in the Geography Faculty at the University of Winnipeg. She holds an office in Lockhart Hall (5L05) and teaches courses including Mapping in a Global World, Intro Remote Sensing, Advanced GIS, and Advanced Remote Sensing. Her research focuses on land-use/land-cover mapping, map automation with machine learning tools, spatial statistics, and terrestrial/aquatic resource management. Teaching expertise spans Regional & Physical Geography, Resource Conservation & Management, and Geomatics (GIS & Remote Sensing). Her work integrates geospatial technologies with environmental challenges, including flood mitigation, mangrove ecosystem analysis, and food environment patterning in urban areas. Research outputs emphasize remote sensing applications in coastal conservation, surface water detection, and vegetation dynamics. Over 13 peer-reviewed articles since 2004 demonstrate sustained academic contributions to geomatics and environmental geography. Current activities include advising on geomatics projects and contributing to the University of Winnipeg’s Geography program infrastructure.
Jane Law is an Associate Professor at the University of Waterloo, located in EV3 3251. She holds a Ph.D. in Geodesy and Geomatics Engineering from the University of New Brunswick (2000), a University Teaching Diploma from the same institution (1999), an M.Sc. in Land Information Systems from Hong Kong Polytechnic University (1994), and a B.Sc. in Survey and Mapping Sciences from North East London Polytechnic (1985). Her research integrates spatial analysis with public health and criminology, employing Bayesian methodologies to examine neighborhood effects on health outcomes and crime patterns. Law's research focuses on geographic information systems, Bayesian spatial modeling, spatial epidemiology, environmental criminology, and health-oriented urban planning. She explores how built environments influence community health outcomes and crime distribution using advanced statistical geospatial techniques. Her publications demonstrate consistent focus on Bayesian spatial modeling applications in public health and crime analysis, with recent work emphasizing mental health spatial patterns, nutrition environments, and temporal crime trends. Research consistently integrates GIS with statistical innovation for policy-relevant insights. Law has supervised 43 Master's and 5 PhD students to completion and currently advises 2 Master's and 1 PhD candidate. She secured a long-term research grant as Principal Investigator for 'Advancing spatial analysis methodologies using a Bayesian approach' (2009-2022).
Bernard A. Engel serves as the Glenn W. Sample Dean of Purdue University's College of Agriculture and holds the rank of Professor in the Department of Agricultural & Biological Engineering. He earned his B.S. and M.S. from the University of Illinois and his Ph.D. from Purdue. His research focuses on soil and water engineering, hydrologic modeling, environmental decision support systems, and the integration of GIS and artificial intelligence. He leads initiatives in sustainable watershed management, precision agriculture, and digital tools for environmental stewardship. Dr. Engel's academic contributions include advancing the USDA Water Erosion Prediction Project (WEPP) model and developing web-based tools like GeoAPEX-P for nonpoint source pollution assessment. He is a Fellow of the American Society of Agricultural and Biological Engineers (ASABE) and recipient of the Gilley Academic Leadership Award. His research spans climate change impacts on water resources, flood risk prediction, and invasive species management in China's coastal wetlands. As Dean of the College of Agriculture, he oversees strategic initiatives in food systems, agricultural technology, and interdisciplinary research. His work bridges engineering and agriculture to address global challenges in sustainability, water quality, and environmental resilience. Key collaborations include modeling urban stormwater control, optimizing nutrient management practices, and advancing the water-energy-food nexus framework.
