Mihaela Girtan is an Associate Professor in the Faculty of Sciences at the University of Angers, heading the Thin Films for Photovoltaic Applications research group. Her work spans thin-film technologies, solar cells, and optoelectronic devices, with expertise in physical/chemical deposition methods and nanomaterials. Education: PhD in Physics, University of Stuttgart (1995) Her research investigates charge transport in oxides, organic/perovskite solar cells, transparent conducting films, plasmonics, and fluid dynamics in CVD reactors. She develops innovative materials for energy conversion, including oxide/metal/oxide electrodes and polymer-based photovoltaics. Recent publications focus on climate-agriculture interactions, including drought risk modeling, irrigation dynamics, and crop yield sustainability. Her work integrates remote sensing, machine learning, and climate modeling to address food security challenges. Scientific Awards: Consistently ranked in top 2% of researchers worldwide since 2020 She leads international collaborations and advises PhD students in materials science. Her group maintains advanced thin-film deposition and characterization facilities at Angers Photonics Laboratory.
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.
Yeyin Shi is an Associate Professor and Agricultural Intelligence Engineer at the University of Nebraska-Lincoln, Department of Biological Systems Engineering. His research focuses on applying artificial intelligence and remote sensing technologies to enhance agricultural productivity and sustainability. He teaches courses such as AGST 316: Technologies and Techniques for Digital Agriculture and AGEN/AGRO/AGST 431/892: Site-Specific Crop Management. He holds a Ph.D. in Biosystems and Agricultural Engineering from Oklahoma State University (2014), an M.S. (2010), and a B.S. in Mechanical Engineering from Nanjing Forestry University (2007). Research Interests: Agricultural data generation/analysis, remote sensing systems (satellite/UAV-based), crop stress sensing, precision crop management, and high-throughput phenotyping. His work bridges machine learning, robotics, and agronomy to address challenges in sustainable farming practices. Recent projects include maize tassel detection via deep learning, UAV-based weed detection, and nitrogen stress indices for maize using hyperspectral imagery. Awards: ASABE Outstanding Manuscript Reviewer (2015), 1st Place Postdoc Research Poster (2015), 2nd Place Student Robotic Competition (2012) Grants: Active collaborations on USDA-funded projects for precision agriculture and phenotyping Labs/Teams: Leads the Agricultural Intelligence Research Group at UNL, focusing on AI-driven agricultural solutions His research emphasizes scalable solutions through edge computing and cloud-based frameworks for irrigation scheduling and crop monitoring, aiming to optimize resource use in both row crops and livestock 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.
Professor Roger Woods is a prominent academic and researcher affiliated with Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science, part of the Faculty of Engineering and Physical Sciences. He holds the rank of Professor and is actively involved in advancing research and innovation in embedded systems, FPGA technologies, and AI-driven solutions for industry challenges. His work emphasizes practical applications through close collaboration with industry partners. His research interests span novel computing architectures (e.g., multi-precision and edge computing), FPGA-based systems for data analytics, and secure IoT communication protocols. Notably, he co-founded and serves as Chief Scientist of Analytics Engines Ltd, a data analytics company. He has led significant initiatives like the Kelvin-2 Tier-4 High Performance Computing centre and contributed to semiconductor reviews through EFutures. Professor Woods has been recognized with prestigious awards, including the IET Northern Ireland Engineering Excellence Award and IEEE Fellowship. He has supervised numerous PhD students focusing on topics like FPGA-based image processing, secure wireless communications, and embedded AI platforms. His publications reflect interdisciplinary strengths in hardware acceleration, physical layer security, and structural health monitoring. Key Collaborations : Projects with industry and institutions on semiconductor design, bridge monitoring, and AI hardware. Grants : Principal Investigator for multiple research grants, including Core Equipment Awards for advanced instrumentation. Labs/Teams : Active in Queen's Advanced MicroEngineering Centre and the EFutures network.
Samsung Lim serves as an Associate Professor of geographic information systems (GIS) in the School of Civil and Environmental Engineering at the University of New South Wales (UNSW) Sydney. With expertise spanning data science, artificial intelligence, and machine learning, Lim applies geospatial technologies to critical real-world challenges in natural disaster management and public health research. Lim's interdisciplinary work bridges engineering, computer science, and public health domains to develop practical decision-making tools for emergency response and disease surveillance. Ph.D. in Aerospace Engineering and Engineering Mechanics, University of Texas, Austin, TX, USA M.A. in Mathematics, Seoul National University, Seoul, South Korea B.A. in Mathematics, Seoul National University, Seoul, South Korea Lim's research focuses on applying GIS to natural disaster management and public health challenges. Key areas include machine learning methods for bushfire susceptibility mapping, spatial clustering for landslide susceptibility analysis, city-scale evacuation management in flood scenarios, and social media-based natural disaster assessment. In public health, Lim investigates geo-correlations between environmental factors and asthma occurrence, computational approaches to avian influenza outbreaks, emerging hot spot analysis of COVID-19, and early detection systems for emerging infectious diseases. This work combines advanced spatial analytics with machine learning to address complex environmental and health challenges. The recent publication record demonstrates a clear interdisciplinary trajectory where geospatial science intersects with public health emergency response and natural hazard management. Lim's work consistently applies machine learning techniques to geospatial data, with particular emphasis on disaster susceptibility mapping, disease outbreak detection, and infrastructure monitoring. The research spans multiple continents and addresses both immediate emergency response needs and long-term environmental health challenges, reflecting a commitment to practical applications of geospatial science. Associate Editor of Geospatial Information Science National Delegate of Commission 3 of International Federation of Surveyors (FIG) National Representative of the International Cartographic Association (ICA) Commission on Sensor-driven Mapping Senior Member of Institute of Electrical and Electronics Engineers (IEEE) Lim actively contributes to the development of early warning systems for emerging infectious diseases through collaborations with public health researchers. The work on EPIWATCH demonstrates how AI can enhance surveillance capabilities for outbreak detection. Lim's research on cruise ship transmission of diseases and the spread of avian influenza through bird migration patterns and poultry trade networks shows strong engagement with real-world public health challenges. These projects often involve multidisciplinary teams spanning engineering, computer science, epidemiology, and veterinary medicine. Lim's work integrates multiple geospatial data sources and analytical techniques to address complex environmental and public health challenges. This includes developing frameworks for performance analysis of OpenStreetMap data, creating specialized road datasets for pedestrian navigation, and applying Persistent Scatterer Interferometry for land motion monitoring. The research combines traditional geospatial methods with cutting-edge machine learning approaches to extract meaningful insights from complex spatial datasets.
Joseph Talghader is the Cymer Professor in the Department of Electrical and Computer Engineering at the University of Minnesota, where he has been a faculty member since 1997, progressing from Assistant to Full Professor. He leads the Optical Micro+Nanosystems Group and holds appointments in the College of Engineering. Dr. Talghader's educational background includes a B.S. in Electrical Engineering from Rice University, followed by an M.S. (1993) and Ph.D. (1995) from UC Berkeley, where he was awarded an NSF Graduate Fellowship. Prior to joining academia, he worked at Texas Instruments and Waferscale Integration in process development and memory design. His research spans optics and micro/nano-mechanical systems with particular focus on infrared detectors, optical coatings, heat transfer mechanisms, and microsensors. His group has developed groundbreaking technologies including the highest sensitivity uncooled thermal detectors and the first tunable multispectral thermal detectors. Recent work has expanded into applications for glacial ice analysis and high-power laser systems. His research integrates theoretical modeling with advanced fabrication techniques, particularly atomic layer deposition. Analysis of his 15 most recent publications reveals a consistent focus on infrared technologies, optical coatings, and thermal phenomena. His work demonstrates strong interdisciplinary connections between electrical engineering, materials science, and optical physics, with increasing emphasis on practical applications in environmental sensing and high-power laser systems. Among his notable recognitions are three 3M Faculty Awards and being a Finalist for the Minnesota Cup for entrepreneurs. He has served on various program committees including the Army Research Office Electronics Division strategic planning panel and has chaired multiple IEEE conferences. Dr. Talghader actively mentors students and postdocs, with numerous publications listing junior researchers as lead authors. His group has secured significant research funding, though specific grant details aren't provided in the source material. He currently serves as an Editor for the NPG journal Light: Science and Applications, demonstrating his standing in the optics research community. The Optical Micro+Nanosystems Group maintains strong industry and interdisciplinary collaborations, with research spanning from fundamental materials properties to practical device implementation. Current projects focus on improving infrared detection technologies, developing advanced optical coatings for high-power applications, and exploring novel sensing mechanisms for extreme environments.
Nik Callow is an Associate Professor at the UWA School of Agriculture and Environment and co-Director of the UWA Centre for Water and Spatial Science. His expertise spans hydrology, geomorphology, remote sensing, and GIS. He leads major projects like the Australian Plant Phenomics Network (APPN) and WaterSmart Dams, focusing on water-dependent ecosystems and spatial science innovations. Callow oversees UWA’s drone operations and supports ~60 drone pilots. He teaches courses in geographical sciences and environmental monitoring, and his research integrates drone technology with climate change studies. Education: PhD in Geography (UWA, 2007), GCHEd (UQ, 2011) Affiliations: Member of the Western Australian EPA Expert Scientific Advisory Council, Resilient Landscapes Hub (NESP), and multiple industry collaborations. Research interests include ecohydrology, marginal snowpacks, and palaeoclimate studies. Projects address water management, biodiversity, and climate resilience in Australia and globally. His work has received the EGU Jim Dooge Award (2020) for contributions to wetland salinity research. Active grants include partnerships with Snowy Hydro, Rio Tinto, and the Grains Research and Development Corporation. Teaching focuses on field science, GIS, and climate processes.
Melanie Kalischuk is an Assistant Professor in the Department of Plant Agriculture at the University of Guelph, Ontario Agricultural College. She holds a B.Sc. in Biological Sciences from the University of Lethbridge, an M.Sc. in Forest Biology from the University of Alberta, and a Ph.D. in Biomolecular Science from the University of Lethbridge. Her research focuses on biotic and abiotic interactions impacting specialty crops such as wine grapes, berries, hazelnuts, ginseng, hops, and high-value vegetables. Key areas include early detection of plant pathogens, developing strategies to enhance crop resilience under environmental stress, and translating research into industry solutions through interdisciplinary collaboration. Her work leverages advanced tools like UAV-assisted multispectral imaging and molecular assays for rapid disease detection. She is affiliated with the Edmund C. Bovey Building and the Ontario Crops Research Centre – Simcoe. Dr. Kalischuk’s contributions span plant pathology, agricultural biotechnology, and crop improvement, with publications addressing fungal pathogens, RNA interference applications, and virus resistance mechanisms. No scientific awards are explicitly listed in her profile. Her research narrative emphasizes practical applications in crop protection, including whitefly-transmitted virus resistance and disease management in cucurbitaceae. While no advising or grant details are provided in the text, her lab focuses on innovation in diagnostics and sustainable agricultural practices.
Ferdous Sohel is a Professor of Information Technology at Murdoch University and inaugural lead of the Agricultural Technologies program. His research spans AI, computer vision, and digital agriculture, with applications in medical imaging and environmental monitoring. He received the Mollie Holman Doctoral Medal and Vice Chancellor's Early Career Research Award. Research Impact: Developed innovative AI models for aquaculture oxygen prediction, 3D object tracking, quantum neural networks, and prohibited item detection. His work advances precision agriculture through hyperspectral classification frameworks and irrigation decision systems. Professional Service: Associate Editor for IEEE Transactions on Multimedia and senior IEEE member. Current projects include adversarial robustness for LiDAR systems and lightweight dormitory security networks.
Eythan Levy serves as Senior Assistant in Digital Archaeology at the University of Zurich's Institute of Classical Archaeology within the Faculty of Arts and Social Sciences. Previously, he led an SNSF SPARK project at the University of Bern (2024) and conducted postdoctoral research on stamp seals from the Southern Levant (2022-2023). His research interests focus on computational approaches to archaeological problems, particularly: Computer applications and quantitative methods in archaeology Ancient chronology of the Iron Age Levant Northwest Semitic epigraphy and paleography Archaeology of the Southern Levant Ancient Egyptian archaeology and epigraphy His work bridges computer science and archaeology through innovative methodological frameworks. Levy's publication trends demonstrate consistent interdisciplinary output combining computational methods with archaeological analysis. Recent work focuses on chronological modeling tools, epigraphic analysis of Hebrew seals, multispectral imaging of ostraca, and computational approaches to ceramic typology. His research shows strong emphasis on developing formalized schemes for synchronizing archaeological data and creating specialized software solutions. Levy has developed several significant archaeological software tools : ChronoLog : For computer-assisted chronological modeling Scrypt : Web application for computer-assisted decipherment of ancient inscriptions TPQ Composer : For displaying stratigraphic termini post quem Artifacts Analyzer : For analyzing archaeological artifact datasets These tools represent his commitment to creating practical computational solutions for archaeological challenges. His academic background uniquely combines computer science and archaeology: PhD in Archaeology (Tel Aviv University, 2017-2021) PhD in Computer Science (Université Libre de Bruxelles, 2003-2009) Multiple MA degrees in Archaeology and Ancient Oriental Languages Teaching certificate for higher education This dual expertise enables his innovative approach to digital archaeology.
Shreya Goel is an Assistant Professor at the University of Utah , affiliated with the College of Pharmacy (Molecular Pharmaceutics) and the School of Medicine (Radiology and Imaging Sciences). Her research focuses on integrating molecular imaging , biologics engineering , and theranostics to develop innovative cancer therapies. PhD: University of Wisconsin-Madison Her work leverages positron emission tomography (PET) , optoacoustic imaging , and nanotechnology to visualize disease microenvironments, optimize radionuclide therapies , and enhance pharmacokinetic/pharmacodynamic modeling for drug development. Current projects include mitochondrial metabolism targeting in pediatric tumors, ultrasmall nanoprobes for surgical guidance, and hypoxia alleviation strategies in cancer treatment. Publications highlight advancements in imaging-guided radiotherapy , nanoprobe design , and multispectral optoacoustic tomography for tumor microenvironment analysis. Her lab actively recruits graduate students and postdoctoral researchers for interdisciplinary projects in pediatric oncology , radiopharmaceuticals , and biologics .
Gurpreet Singh Gill is a Research Fellow at The University of Western Australia (UWA), School of Engineering, Department of Electrical, Electronic and Computer Engineering. He holds a Ph.D. from UWA (2022) and prior degrees from Punjab Technical University and Sri Guru Granth Sahib World University, Punjab, India. His research focuses on MEMS/NEMS, thin-film materials, optical MEMS, and infrared sensing/imaging technologies. He previously worked at the Central Electronics Engineering Research Institute, India, and currently leads projects in micro/nano electromechanical systems and their applications in optoelectronics and infrared sensing. **Education**: B.Tech in Electronics & Communication Engineering (2013, Punjab Technical University) M.Tech in Electronics & Communication Engineering (2015, Sri Guru Granth Sahib World University) Ph.D. in Microelectronics (2022, The University of Western Australia) **Research Interests**: MEMS/NEMS device design and applications Thin-film materials for optical and infrared systems Optical MEMS and optoelectronic devices Infrared sensing and imaging technologies **Awards**: Nanoscale Advances Poster Prize (2019) ADHOC Postgraduate Scholarship (2017) Scholarship for International Research Fees (SIRF) (2017) **Grants & Advising**: Gill has received scholarships for international research fees and postgraduate support. He collaborates with interdisciplinary teams and leads research projects funded by UWA and external grants. His work contributes to UN SDGs related to affordable and clean energy, industry innovation, and infrastructure. **Labs & Teams**: Active in UWA’s Microelectronics Research Group and collaborates with global institutions on MEMS-based sensing systems.
Introduction Dr. Shelley Xuelian Meng is an Associate Professor in the Department of Geography and Anthropology at Louisiana State University (LSU), part of the College of Humanities & Social Sciences. Her research focuses on leveraging remote sensing technologies (e.g., UAVs, LiDAR, multispectral imaging) to study coastal dynamics, wetland restoration, vegetation health, and precision agriculture. Education Ph.D. in Geography and GIScience, Texas State University (2010) M.S. in GIS and Cartography, Chinese Academy of Sciences (2003) B.E. in Information Engineering, Wuhan University (2000) Research Interests Meng’s work emphasizes the application of advanced geospatial technologies to address environmental challenges. Key areas include: Coastal wetland die-off and restoration using multi-scale remote sensing LIDAR and UAV-based terrain and vegetation mapping Object-oriented classification algorithms for environmental monitoring GIS integration for precision agriculture and disaster management Awards & Recognition 2023 Tipton Team Award (for Roseau cane die-off research) 2014 Best Paper Award in Remote Sensing CPGIS Young Scholar (2012) Grants & Projects Notable funded projects include: USDA-funded Roseau cane die-off studies ($1.6M+ across multiple years) Development of LiDAR and thermal sensing tools for coastal research Acquisition of terrestrial LiDAR equipment for multidisciplinary studies Labs & Affiliations Meng directs the Technology Intensive Geospatial and Remote Sensing (TIGeRS) Lab , which houses advanced equipment including drones, LiDAR scanners, and multispectral sensors. The lab collaborates with the LSU Coastal Studies Institute and other institutions.
Hannu Hyyppä is a Research Director and Project Employee at Aalto University's Department of Built Environment, affiliated with the MeMo research group. He leads the Research Institute of Measuring and Modelling for the Built Environment, focusing on advanced laser scanning, 3D modeling, and geoinformatics. His work spans interdisciplinary collaborations across engineering, geography, and arts, with a strong emphasis on applications in cultural heritage preservation, urban planning, and environmental monitoring. Education: Doctoral degree (D.Sc.) in Engineering and Technology, Helsinki University of Technology (2000) Licentiate degree in Engineering and Technology, Helsinki University of Technology (1989) Master's degree in Engineering and Technology, Helsinki University of Technology (1986) Research Interests: Laser scanning technologies, point cloud utilization in forestry and urban mapping, virtual reality for cultural heritage, and sustainable infrastructure modeling. His expertise includes photogrammetry, geographic information systems (GIS), and decision support systems for environmental management. Recent Contributions: Over 550 publications and 30+ active projects, including the Centre of Excellence in Laser Scanning Research (2014-2019) and the Pointcloud project (2015-2021). His work advances applications in autonomous road inspection, 3D cultural reconstructions, and smart city technologies. Awards: Recipient of the 2019 Kansallinen avoimen tieteen palkinto for innovative open science contributions. Grants & Leadership: Principal Investigator for projects like DICA (Digital Cultural Heritage) and ToToRo (Automatic Road Inspection). Active in organizing workshops and international conferences on 3D technologies and laser scanning. Labs/Teams: Oversees the MeMo group and collaborates with national organizations like the Finnish Geospatial Research Institute. Develops tools for real-time 3D mapping and virtual environments.
