Dr. Gülsüm Çiğdem Çavdaroğlu Akkoç is a full-time Assistant Professor in the Information Technologies Department at Işık University's Faculty of Economics, Administrative and Social Sciences. She holds a multidisciplinary background with degrees in Mathematics Engineering, Geomatics Engineering, and Turkish Language & Literature. Education Ph.D. in Photogrammetry Engineering – Yıldız Technical University (2006–2013) M.S. in Photogrammetry Engineering – Yıldız Technical University (2003–2006) B.S. in Mathematics Engineering – Yıldız Technical University (1998–2003) B.A. in Turkish Language & Literature – Anadolu University (2016–2020) Research Interests Dr. Akkoç's research spans remote sensing , GIS , and machine learning , with applications in environmental monitoring, urban mobility, and health informatics. Her work leverages satellite imagery, mobile data, and AI to address challenges such as wildfire detection, air pollution tracking, and disease diagnosis. She actively integrates spatial data with AI to support smart city development and sustainable resource management. Scientific Awards First Prize – Mobilya Ar-Ge Proje Pazarı (2013), Entrepreneurship Category Supervision & Projects She has supervised four master's theses and led several EU and national projects including: BEE-OPTECH4Honey : Optimizing beekeeping routes using ICT TOP4HoneyChain : A sustainable smart honey value chain platform Open Data Platform for Precision Agriculture Labs & Teams Dr. Akkoç collaborates with interdisciplinary research teams in the fields of AI, geospatial technologies, and agricultural informatics. Her lab activities include developing machine learning models for real-world applications in health, environment, and urban systems.
Nikolaos Pelekis is a Professor at the Department of Statistics and Actuarial Science, School of Finance and Statistics, University of Piraeus, where he teaches courses in Data Science, Data Management, Information Systems, and Computer Programming. He has been actively involved in both undergraduate and postgraduate education, offering specialized courses such as "Statistical Data Mining Methods" in the Applied Statistics Master's program and "Big Data Management" in the Cybersecurity and Data Science postgraduate program. Born in 1975, Professor Pelekis earned his Bachelor's degree in Computer Science from the University of Crete (1998), followed by an MSc in Information Systems Engineering (1999) and a PhD in Moving Object Databases (2002) from UMIST University in the United Kingdom. His educational background laid the foundation for his distinguished career in data science and database management. Professor Pelekis' research spans multiple domains within data science and database management, with particular emphasis on mobility data analytics. His work focuses on data mining, big data management and analytics, with special attention to location and motion data including trajectories of moving objects. He has made significant contributions to spatial and spatiotemporal database management, moving object database systems, privacy-preserving data mining, and OLAP analysis. His research bridges theoretical foundations with practical applications, particularly in maritime and transportation domains. An analysis of Professor Pelekis' recent publications reveals a strong trend toward maritime data analytics and vessel traffic prediction. His work increasingly focuses on applying machine learning techniques to maritime trajectory data, developing systems for collision risk assessment, vessel location forecasting, and maritime route prediction. The research demonstrates a progression from foundational database management techniques to sophisticated analytics for time-critical mobility forecasting, with applications in aviation and maritime domains. Five best research paper awards 1st & 3rd place in the SemEval-2017 competition 3rd place in the ACM SIGSPATIAL Cup 2016 competition Best paper award at ACM SIGSPATIAL'14 (Path-based Queries on Trajectory Data) Best paper award at ER'13 (Baquara: A Holistic Ontological Framework for Movement Analysis with Linked Data) Best application paper award at ICDM'09 (Clustering Trajectories of Moving Objects in an Uncertain World) Ralf H. Güting best research paper award at SSTD'21 (A Novel Indexing Method for Spatial-Keyword Range Queries) Best Demo Paper award at SSTD'21 (MaSEC: Discovering Anchorages and Co-movement Patterns on Streaming Vessel Trajectories) Professor Pelekis has been actively involved in advising and research funding acquisition. He has participated in over 10 European and National Research and Development projects as principal investigator or key researcher. His leadership extends to directing research laboratories and coordinating large-scale collaborative projects. As co-founder of the Data Science Lab - DataStories at the University of Piraeus, he has mentored numerous researchers and students. His research has been supported by prestigious funding programs including Horizon Europe, Horizon 2020, and national research initiatives. Professor Pelekis co-founded and leads the Data Science Lab - DataStories at the University of Piraeus, which comprises 9 faculty members from 4 different Departments along with experienced and young researchers. He previously served as Head of Research for the Information Management Lab (InfoLab) at the Department of Informatics, University of Piraeus (2005-2014). His current research team is actively engaged in multiple European projects including "DAT.AI – Energy-efficient AI-ready Data Spaces" and "EMERALDS – Extreme-scale Urban Mobility Data Analytics as a Service," focusing on cutting-edge applications of data science in maritime and urban mobility contexts.
Dr. Dmytro Uhryn is an Associate Professor at the Department of Computer Science, Yuriy Fedkovych Chernivtsi National University. With a Doctor of Technical Sciences degree (2021) and specialization in Computer Science (12DC No. 029057, 2011), he actively contributes to research in swarm intelligence and geographic information systems . As a member of the Bukovina Information Technology Cluster since 2019, he focuses on intelligent forecasting systems , medical image analysis , and financial data modeling . Education: Applied Mathematics (2003, Chernivtsi National University) and Organizational Management (National Technical University "Kharkiv Polytechnic Institute") Research Interests: Information technologies for decision support, swarm intelligence systems, industry-specific GIS, medical image processing, and financial market algorithms. Recent publications (2023-2024) demonstrate expertise in swarm intelligence applications for migration forecasting, medical diagnostics using laser autofluorescence, and financial systems modeling. His 2021 dissertation established foundational methods for swarm intelligence in GIS . Professional development includes certifications in educational programming (Sigma Software University), NATO modeling , and international teaching methodologies (Lyublin Institute, 2023). He collaborates with researchers across Ukraine and Poland on biomedical optics, financial IT, and tourism technology projects.
Alex Arnall is a researcher at the University of Reading, specializing in climate change adaptation, human-environment interactions, and coastal community resilience. His work bridges environmental geography, policy analysis, and development studies, focusing on Sub-Saharan Africa, South Asia, and the Indian Ocean islands. Key Research Areas: Climate change, disaster resettlement, sediment dynamics, rural livelihoods, Anthropocene landscapes, and environmental justice. Recent Publications (2025-2021): Explored managed retreat in coastal zones, small-scale mining's role in rural economies, and climate displacement narratives. Interdisciplinary Networks: Collaborated on food systems literacy and adaptive social protection programs, emphasizing cross-sectoral learning. Arnall's work integrates spatial-temporal analysis, community agency, and policy critique, often published in journals like Climate Policy , Geoforum , and Global Environmental Change . His studies highlight the social dimensions of climate adaptation and the politics of environmental governance.
Dr. Ariel Greiner is an NSERC Postdoctoral Fellow in the Department of Biology at the University of Oxford and Pennsylvania State University, supervised by Dr. Katrina Davis and Dr. Katriona Shea. Her interdisciplinary research applies mathematical and statistical modeling to conservation challenges, with current focus on optimizing coral reef management in Melanesia through value-of-information frameworks and socioeconomic integration. Her academic foundation includes: PhD in Ecology and Evolutionary Biology from the University of Toronto (supervised by Dr. Martin Krkošek, Dr. Marie-Josêe Fortin, and Dr. Emily Darling) Bachelor of Science from McGill University (research with Dr. Andrew Gonzalez on ecosystem functioning debts and global genetic diversity patterns) Dr. Greiner's research centers on coral reef resilience under anthropogenic pressures, employing network theory and dynamical systems to model connectivity, regime shifts, and climate impacts. Her work bridges theoretical ecology with practical conservation, emphasizing equity in scientific practice. Recent publications demonstrate methodological innovation in state-space modeling, macrogenetics, and disease epidemiology while maintaining consistent focus on coral reef sustainability. Analysis of her 15 most recent publications reveals dominant themes in coral reef dynamics (73% of works), with significant contributions to disease modeling (13%) and conservation genetics (13%). Temporal trends show increasing integration of socioeconomic factors since 2021, while mathematical approaches consistently emphasize network connectivity and stability analysis across all publications. Her accolades include: Excellence in Doctoral Research Award (Canadian Society of Ecology and Evolution) Harold H. Harvey Prize for Academic Leadership NSERC Doctoral Scholarship NSERC Postdoctoral Fellowship Supported by NSERC funding throughout her career, Dr. Greiner has collaborated extensively with the Wildlife Conservation Society (WCS) Fiji and Melanesia, including fieldwork surveying Fijian reefs. While no formal advisees are documented, her work demonstrates strong mentorship through collaborative publications and educational contributions like the 'Ten Simple Rules' modeling guide. Her current Melanesian reef project exemplifies her signature approach: integrating mathematical optimization with community engagement to develop context-specific conservation strategies that balance ecological resilience and human needs.
Rizwan Bulbul is a researcher at the Institute of Geodesy , Graz University of Technology (TU Graz), Austria. His work bridges geodesy, geographic information systems (GIS), and computational modeling. Research Interests : Bulbul's research focuses on geospatial modeling, artificial intelligence integration, and sustainable urban development. Key areas include smart tourism simulations, energy transition policy analysis, and off-road robotic navigation using machine learning. His work also addresses forest fire prediction uncertainty, vertical photovoltaic potential, and cattle tracking in alpine environments. Publications : His research spans spatial optimization, 3D city modeling, and semantic routing. Recent projects involve leveraging AI for tourism simulations and energy policy evaluation, demonstrating interdisciplinary applications of geospatial technologies. Contact : Email: bulbul@tugraz.at Office: TU Graz, Steyrergasse 30/I, Room ST01122
Pascal O. Title serves as an Assistant Professor in the Department of Ecology and Evolution at Stony Brook University, leading the macroEEB Lab focused on large-scale evolutionary and ecological dynamics. His research integrates phylogenetic, trait, and spatial data to unravel biodiversity patterns across continents and through time. His educational background includes: Ph.D. from University of Michigan (2018) Dr. Title's work centers on four interconnected research pillars: Large-scale biodiversity patterns through analysis of museum collections and observational databases for Australian reptiles, marine fishes, and Neotropical birds Species responses to climate change via geographic range shift analyses linked to phylogenetic history Species distribution modeling methodology development addressing data biases and environmental variables Diversification rate quantification through simulation-based evaluation of macroevolutionary metrics His approach leverages global biodiversity networks and computational tools to address fundamental questions in evolutionary ecology. Analysis of his 2014-2025 publication record reveals consistent focus on macroevolutionary processes across diverse taxa, with increasing emphasis on climate change impacts and methodological innovations. Key thematic threads include latitudinal diversity gradients, adaptive radiation mechanisms, and computational tool development for integrating phylogenetic and spatial data. The macroEEB Lab operates as a collaborative hub for researchers investigating evolutionary dynamics across spatial and temporal scales, recently participating in the 2025 Evolution conference.
Rodolfo Metulini is a Researcher (RTD-B) in Statistics for Experimental and Technological Research (SECS-S/02) at the Department of Economics, University of Bergamo. He serves as Principal Investigator for the PRIN/PNRR project 'SIGNUM: Study of mobile phone signals for evaluating mobility-environment interconnections in Lombardy'. His career includes postdoctoral positions at the University of Brescia, Scuola Superiore Sant'Anna Pisa, and IMT Lucca. PhD in Statistical Methodology for Scientific Research (2013), University of Bologna Former Researcher at University of Salerno (RTD-A) Metulini's research spans three primary domains: travel flow analysis using gravity models and spatial interaction approaches for international trade studies; sports analytics focusing on player movement dynamics and marginal utility in football/basketball; and urban mobility modeling through mobile phone data with complex seasonality time series models. His methodological innovations combine matrix completion techniques with functional data clustering for environmental-socioeconomic applications. Recent research trends demonstrate cross-sectoral expertise in applying statistical learning to diverse domains: 1) environmental risk assessment using mobile network data for flood exposure forecasting; 2) urban policy analysis through counterfactual modeling of traffic restrictions; and 3) economic modeling for CO2 emissions prediction. His technical approach integrates dynamic harmonic regression with VARX models for mobility forecasting. As thesis advisor for Computer/Mechanical Engineering students, Metulini promotes data-driven approaches in mobility and sports domains. His publications in journals like Annals of Operations Research and Optimization Letters showcase interdisciplinary methodology combining statistical theory with practical applications in environmental risk management and sports performance analysis.
Dr. Elina Kaarlejärvi is an Academy Research Fellow and University Lecturer in Ecology at the University of Helsinki's Organismal and Evolutionary Biology Research Programme. She is also a Docent in Northern Biodiversity and Ecosystem Functioning, with supervisory roles in the Doctoral Programme in Wildlife Biology. Academy Research Fellow (2022-2027), Academy of Finland University Lecturer in Ecology, University of Helsinki Docent, Organismal and Evolutionary Biology Research Programme As a community ecologist, her research investigates biodiversity's role in ecosystem stability under climate change through observational data and experimental approaches. She has led major projects on: Functional diversity impacts on ecosystem functions (Swedish Academy funding) Arctic tundra plant-herbivore interactions (Umeå PhD thesis) Finnish forest undergrowth dynamics (collaboration with Luke Institute) Bayesian modeling for species distribution predictions (2024 Global Ecology & Biogeography) Her academic contributions include 26 publications and 3 Academy of Finland projects. She supervises multiple PhD/MSc theses and serves on international research committees. 2024 Nature publication on Arctic plant diversity patterns 2025 PNAS study on boreal community homogenization 2024 Environmental Evidence systematic review on herbivory Major awards: Academy Research Fellow (2022-2027) Finnish Cultural Foundation grant Swedish Academy of Sciences funding (2015-2018)
Andreas Braun is a Senior Lecturer at the Department of Geography, University of Tübingen, Germany. He leads lectures and courses on physical geography, geospatial methods, and remote sensing applications. Currently serving since January 2022, his academic responsibilities include teaching, thesis supervision, and research in geoinformatics with a focus on humanitarian response applications. PhD in Geography (2014-2019), University of Tübingen Baden-Württemberg Certificate in University Didactics (2015-2017) Professional experience at Stuttgart's Land Surveying Office (2013) His research bridges geospatial technologies with humanitarian applications, emphasizing remote sensing for environmental monitoring in refugee camps, urban structure analysis, and climate change adaptation. Key areas include SAR data utilization, geosimulation for landscape dynamics, and machine learning applications in geospatial projects. Scientific publications span topics like urban heat island effects in Vietnam, refugee camp monitoring using satellite imagery, and landscape change modeling. His work appears in journals such as IEEE Journal of Selected Topics in Applied Earth Observations , Remote Sensing , and Journal of Flood Risk Management . Teaching activities cover physical geography methods, GIS, remote sensing, and applied geoinformatics for both B.Sc. and M.Sc. programs. He supervises interdisciplinary projects connecting geography with social sciences, focusing on urban planning, climate adaptation, and environmental justice.
Prof. Jürgen Knies serves as Professor and Vice Dean of Faculty 2 (Faculty of Architecture, Civil Engineering and Geomatics) at Bremen City University of Applied Sciences. Based in the Department of Infrastructure Planning of Environmental and Energy Systems (building UB, room 107), his work integrates ecological principles, Geographic Information Systems (GIS), Building Information Modeling (BIM), and environmental law to address complex infrastructure challenges. His leadership extends to municipal heat planning initiatives and跨-institutional research networks across Northwest Germany. His research focuses on urban energy transitions , with particular emphasis on heat system transformation, spatial planning integration, and socio-technical implementation barriers. Key methodologies include GIS-based spatial analysis, BIM integration, and multi-stakeholder governance frameworks. Current investigations target cold district heating networks, wastewater heat recovery, solar cadastre validation, and equity considerations in energy transitions—always contextualized within Bremen's municipal challenges and North German regional cooperation frameworks. Analysis of his 15 most recent publications (2017-2025) reveals a consistent trajectory: evolving from foundational spatial energy modeling toward integrated socio-technical solutions for urban heat transitions. The body of work demonstrates increasing sophistication in Digital integration (E-Government/BIM fusion) Multi-scale spatial analysis (neighborhood to regional) Equity-focused implementation strategies Legal-regulatory-compliance frameworks with Bremen serving as both living laboratory and model for municipal energy planning. No scientific awards are documented in the provided materials. His advising activities center on thesis supervision in infrastructure planning, while grant leadership includes major projects: hyBit (Hydrogen for Bremen's industrial transformation; 2021-2022) Heat Transition Northwest (digitalization for heat implementation; 2021-2025) North German Research Associations coordination Bremen Heat Transition Network initiatives These involve partnerships with municipal authorities, industry, and regional research consortia. His operational ecosystem includes the GIS Laboratory for spatial analysis, active participation in Networking AG Wärme (Heat Working Group), and leadership in the Bremen Heat Transition Network . Current engagements extend through 2026, including coordination of the 3rd North German Conference on Thermal Research—demonstrating sustained commitment to advancing urban energy infrastructure through academic-practice integration.
Isaac Park is an Assistant Professor in the Department of Biology at Georgia Southern University, joining in 2024. His research focuses on plant ecology, phenology, and climate change impacts on vegetation, contributing to UN Sustainable Development Goals in environmental sustainability and plant conservation. Dr. Park's research centers on plant phenological responses to climate change, utilizing herbarium specimens and ecological observatory data to model spatiotemporal patterns. His work spans grasslands, shrublands, and Mediterranean ecosystems with emphasis on anthesis, flowering dynamics, and plant-pollinator interactions. Key methodologies include digital herbarium data analysis and cross-scale phenological forecasting. Recent publications demonstrate innovative integration of museum collections and ecological data to track climate-induced shifts in flowering and pollinator behavior. Themes include vulnerability of endemic species to fire regimes, macrophenology modeling, and resource availability changes for specialist versus generalist bees. Dr. Park serves as Co-Principal Investigator on two National Science Foundation grants: Active (2021-2026): Modeling phenology across spatiotemporal and taxonomic scales using ecological observatory and digital herbarium data Completed (2016-2020): Phenological sensitivity to climate across space and time through digital herbarium analysis His collaborative network spans ecological observatories and research institutions, leveraging mobilized digital collections for large-scale phenological studies while developing datasets for testing flowering prediction accuracy.
Laurent JÉGOU is a Teacher-researcher at the Interdisciplinary Laboratory for Solidarity, Societies, Territories (LISST) within the Department of Geography, Planning, Environment at the Daniel-Faucher Institute, University of Toulouse - Jean Jaurès. His office is located at the House of Research, 5 allées Antonio Machado, Toulouse, France. Dr. JÉGOU completed his doctoral thesis titled 'Vers une nouvelle prise en compte de l'esthétique dans la composition de la carte thématique : propositions de méthodes et d'outils' at Université Toulouse le Mirail - Toulouse II in 2013. His research focuses on aesthetics in cartography, geography of science, geovisualization, representation of flows, and graphic models. He teaches courses in history of cartography, cartography, geographic information systems, web mapping, graphic design, and network analysis and representation. His scholarly work demonstrates a consistent focus on improving cartographic communication and visual effectiveness. Recent publications show increasing attention to the integration of cartographic principles with digital technologies, urban climate mapping, and the spatial analysis of scientific production. His research bridges theoretical cartographic concepts with practical applications in urban planning and environmental management. Member of the committee of the Mappemonde journal Member of the committee of the International Journal of Cartography Dr. JÉGOU has been actively involved in collaborative research projects including the CAPARI project (Ville Région Occitanie), which explores university campuses as living laboratories for future cities, and research on mapping urban climate for summer comfort management in French urban planning. His work often involves interdisciplinary collaboration across geography, urban planning, and information science.
Dr. Ye Hong is a Researcher affiliated with the Institute of Cartography and Geoinformatics at ETH Zürich, specifically within the Department of Geoinformation Engineering. Their work focuses on geospatial data analysis, urban mobility modeling, machine learning applications in transportation systems, and sustainable urban planning. They contribute to open-source tools like Trackintel for mobility analysis and have published extensively on topics such as mobility data synthesis, traffic prediction, and privacy-preserving techniques. Research interests emphasize integrating multi-source geospatial data with deep learning to address challenges in urban sustainability, poverty reduction, and transportation efficiency. Their articles highlight innovations in trajectory generation, uncertainty quantification, and contextual-aware neural networks for spatial-temporal prediction. Dr. Hong’s publications explore the interplay between urban infrastructure, human behavior, and environmental impact. Key themes include accessibility measurement in cities, carbon footprint analysis, and the ethical implications of tracking mobility data. Their work bridges theoretical advancements in geoinformatics with practical applications in urban policy-making and infrastructure design. Notable contributions include frameworks for causal intervention in mobility data, methods to estimate poverty reduction efficiency using remote sensing, and analyses of tracking duration effects on location privacy. These efforts demonstrate a commitment to leveraging geospatial technologies for socially impactful research.
Konstantinos A. Tsintotas is an Assistant Professor at the Department of Information and Electronic Engineering, International Hellenic University. His research focuses on artificial intelligence, robotics, computer vision, and their applications in smart cities, healthcare, and manufacturing. He is actively involved in advancing AI-driven systems for critical infrastructure management, robotic vision, and embedded device technologies. His work spans theoretical advancements and practical implementations, including projects like SLAM algorithms for autonomous navigation, deep learning models for medical diagnosis, and IoT-integrated smart supply chains. Tsintotas also explores ethical implications of AI in human action recognition and contributes to neuromorphic computing through spiking neural networks. Key technical contributions include ReJSHand (real-time hand pose estimation), fall detection systems for embedded devices, and visual place recognition frameworks. His interdisciplinary approach bridges computer science, electrical engineering, and biomedical applications, reflecting a strong commitment to innovation at the hardware-software interface. Notable trends in his publications emphasize AI ethics, multimodal perception for robotics, and low-power embedded solutions. Ongoing work includes advancing digital twin technologies for supply chains and refining bio-inspired neural architectures for robotics applications.
