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Dimitris PoursanidisView profile

Research Fellow

• Environmental Mapping
• Environmental Monitoring
• Earth Observation
• +6 more

Dimitris Poursanidis serves as a Research Fellow at the Remote Sensing Lab (rslab.gr) within the Institute of Applied and Computational Mathematics at the Foundation for Research and Technology - Hellas (FORTH). His work focuses on environmental mapping and monitoring through innovative technological approaches. His educational background includes a Ph.D. in Marine Ecology (2016), an M.Sc. in Integrated Coastal Zone Management (2008), and a B.Sc. in Ecosystem Management (2004). His academic journey has been complemented by extensive field experience across multiple sectors. Poursanidis specializes in Environmental Mapping and Monitoring using Earth Observation, UAV technology, Non-Destructive Sampling, Photogrammetry, and Scientific Diving. His research particularly emphasizes Satellite Remote Sensing applications in coastal environments and Biodiversity exploitation through Species Distribution Modeling in both terrestrial and aquatic ecosystems. His work bridges the gap between technological innovation and ecological conservation, with a strong focus on Mediterranean environments. Analysis of his recent publications reveals a strong emphasis on Mediterranean marine ecosystems, particularly seagrass habitats like Posidonia oceanica. His work integrates satellite remote sensing with field validation methods to address conservation challenges, invasive species monitoring, and habitat mapping. A notable trend is his increasing use of cloud computing platforms like Google Earth Engine for large-scale environmental analysis, demonstrating technical innovation in processing satellite data for ecological applications. Throughout his career, Poursanidis has collaborated across diverse institutional contexts, working with academic institutions (NHMC, UNEP/MAP, HCMR, University of Athens, University of the Aegean), private sector companies (Marathon Data Systems, NCC ltd, NatureBureau ltd), and NGOs (WWF, IUCN, iSea). His projects have been funded by major European and national programs including LIFE+, INTERREG, EraNET, H2020, MAVA Foundation, THALASSA Foundation, and MEDPAN. At FORTH's Remote Sensing Lab, Poursanidis contributes to cutting-edge research that combines satellite technology with ecological field studies. His work on satellite-derived bathymetry, marine habitat mapping, and invasive species monitoring represents significant contributions to the understanding and conservation of Mediterranean coastal ecosystems.

Hannes MühleisenView profile

Professor

• Data Engineering
• Database Systems
• Query Processing
• +2 more

Hannes Mühleisen is Professor of Data Engineering at Radboud University's Faculty of Science, Institute for Computing and Information Sciences. He maintains a joint appointment as Senior Researcher at Centrum Wiskunde & Informatica (CWI) and serves as CEO of DuckDB Labs. His research focuses on analytical data management systems architecture, with applications in modern data-driven applications. Mühleisen's research interests center on data engineering challenges, particularly the architecture and design of analytical data management systems. He develops universally-useful software artifacts that transform how data systems operate in real-world applications, with emphasis on CPU-efficient processing and embedded analytics. His recent publications demonstrate a consistent focus on database system optimization, particularly in the areas of query processing, sorting algorithms, and web-based analytical processing. This research direction aims to improve the efficiency and scalability of data systems handling large-scale analytical workloads. Dutch Prize for ICT Research 2025 Best paper runner up award at SSDBM 2017 Mühleisen leads DuckDB Labs and collaborates with research teams at Radboud University on data engineering challenges. His work includes developing frameworks for responsible decentralized data architectures and teaching courses on Big Data Infrastructures & Technology.

• Aquatic Microbial Ecology
• Functional Biodiversity
• Organic Matter Cycling
• +3 more

Prof. Hans-Peter Grossart is a Professor of Aquatic Microbial Ecology and Functional Biodiversity at the University of Potsdam, within the Faculty of Mathematics and Natural Sciences and the Institute of Biochemistry and Biology. He leads the Aquatic Microbial Ecology research group at the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB), where he has been Head of the Department since 2002. His expertise spans microbial community dynamics, organic matter cycling, and applications of aquatic ecology in biotechnology. He has held roles including Head of ASLO’s Young Researcher’s Committee and speaker of the IGB’s Aquatic Biodiversity research focus. Grossart’s research integrates field studies, experimental approaches, and genomic tools to address environmental challenges like microplastic impacts, climate-driven ecosystem changes, and biodiversity conservation. Education: Diploma in Limnology (1991), University of Constance PhD in Limnology (1995), University of Constance Postdoctoral research at Scripps Institution of Oceanography (1996–1998) and Yigal Allon Kinneret Limnological Laboratory (1995–1996) Research Interests: Grossart’s work focuses on microbial roles in nutrient cycles, aquatic biodiversity, and the ecological impacts of human activities. He investigates topics such as microbial interactions in lake ecosystems, fungal diversity, and the effects of pollutants like microplastics and PFAS. His projects bridge fundamental and applied research, including biotechnology applications for waste management and bioactive compound discovery. Key Contributions: Global studies on microplastic effects and antibiotic resistance dissemination Pioneering work on lake snow aggregates and their ecological significance Leadership in large-scale ecological monitoring and long-term dataset analysis Labs/Teams: Heads the IGB’s Aquatic Microbial Ecology group and collaborates internationally on projects like the ParAqua initiative to study zoosporic parasites in aquatic systems.

• Internet of Things (IoT)
• Context-aware computing
• Edge and cloud computing
• +7 more

Prem Prakash Jayaraman is a Professor in the Department of Computer Science and Software Engineering within the Faculty of Science, Engineering and Technology at Swinburne University of Technology. His research focuses on the intersection of Internet of Things, context-aware computing, and distributed systems, with particular emphasis on practical applications in smart cities, digital manufacturing, and healthcare. Dr. Jayaraman's research interests span a wide range of topics within the IoT ecosystem, including context-aware computing, edge and cloud computing integration, digital twins for industrial applications, sensor network optimization, and performance evaluation of IoT middleware platforms. His work often addresses the challenges of real-world deployment, focusing on practical solutions for context management, data quality assurance, and resource optimization in distributed environments. He has made significant contributions to frameworks for context query generation, adaptive context monitoring, and caching strategies that enhance the efficiency of IoT applications. His recent publications demonstrate a strong trend toward applied research with practical implementations in smart city infrastructure, digital manufacturing, and healthcare applications. His work often combines theoretical frameworks with real-world validation, particularly evident in his studies on 5G-enabled smart cities, AI-driven roadside infrastructure monitoring, and digital twin implementations for manufacturing quality control. The research spans multiple sub-disciplines including context-aware systems, performance evaluation methodologies, and resource optimization techniques for distributed IoT environments. Dr. Jayaraman maintains an extensive collaborative network with researchers across Australia and internationally, particularly with Dimitrios Georgakopoulos, Rajiv Ranjan, Arkady Zaslavsky, and Abdur Forkan. His work appears in top-tier journals and conferences including IEEE Transactions on Industrial Informatics, Future Generation Computer Systems, IEEE Internet of Things Journal, and major conferences like MDM, HICSS, and IEEE Cloud.

• Artificial Intelligence
• Bioinformatics
• Natural Language Processing
• +3 more

Dr. Ahmad Aghaebrahimian is a researcher at the ZHAW School of Life Sciences and Facility Management, affiliated with the Institute of Computational Life Sciences. He specializes in computational methods applied to healthcare, natural language processing (NLP), and bioinformatics. His work integrates deep learning, ontology-based systems, and signal processing to address challenges in healthcare informatics, biomedical research, and security systems. Research Projects: Project Leader: Advancing Information Accessibility in Hospitals (LLMs) Project Leader: Multi-document Patient Records Summarization Project Leader: Plant Cell Cultures with Deep Learning Deputy Leader: Automatic Supply Chain Monitoring Research Interests: His research focuses on AI-driven solutions for healthcare, including ontology-aware relation extraction, medical text mining, and robust signal processing systems. He also explores NLP applications in question answering, entity disambiguation, and parallel corpus creation. Recent work includes drone detection using CNNs in low SNR environments and computational methods for natural products discovery. Publications Trends: Over the past decade, his publications emphasize interdisciplinary approaches combining machine learning with bioinformatics and medical informatics. Key themes include deep learning model optimization, biomedical knowledge graph construction, and practical applications of NLP in healthcare systems. Grants & Collaboration: Leads research initiatives on AI in colorectal cancer classification and supply chain monitoring, demonstrating expertise in securing project leadership roles within academic-industry collaborations.

Matthew OliverView profile

Professor

• Phytoplankton oceanography
• Biogeography
• Remote sensing
• +5 more

Matthew Oliver is the Patricia and Charles Robertson Distinguished Professor of Marine Science and Policy at the University of Delaware. He holds appointments in the School of Marine Science & Policy and the Department of Geography and Spatial Sciences within the College of Earth, Ocean & Environment. His research focuses on phytoplankton oceanography, biogeography, remote sensing, and polar marine ecosystems. He leads the Ocean Exploration, Remote Sensing, and Biogeography (ORB) Lab, which develops technologies like robotic systems and satellite data to study marine organisms' distributions and ecosystem dynamics. Oliver earned a Ph.D. in Oceanography from Rutgers University (2006), an M.S. in Biology from Cal Poly (2001), a B.S. in Ecology from Cal Poly (1999), and an A.A. in Natural Sciences from Cerritos College (1996). His work emphasizes understanding how physical ocean processes influence biological systems, with applications to conservation and fisheries management. His research interests span satellite-driven ecological forecasting, marine predator behavior, and Antarctic ecosystem studies. The ORB Lab's innovations include real-time ocean data platforms (e.g., Atlantic Sturgeon risk maps) and partnerships with agencies like NOAA and Delaware Sea Grant. Oliver's publications highlight interdisciplinary approaches linking oceanography with ecology, with recent work exploring submesoscale transport, Lagrangian coherent structures, and the role of eddies in biological hotspots. Advising focuses on students with quantitative skills, particularly in spatial analysis and programming. His lab actively collaborates with international teams on projects like Project CONVERGE (Antarctic ecosystem dynamics) and robotic ocean glider deployments. Current initiatives include advancing dynamic ocean management tools and integrating animal telemetry with remote sensing data. Labs/Teams: ORB Lab (lead), Robotic Discovery Laboratories. Key projects involve developing seascapes frameworks for marine conservation and improving ecological forecasting models for climate-sensitive species.

David RoonView profile

Researcher

• Aquatic Ecology
• Riparian Forests
• Aquatic-Terrestrial Linkages
• +5 more

David Roon is a Researcher in the Department of Forest Ecosystems & Society at Oregon State University's College of Forestry. His work focuses on aquatic-terrestrial linkages, particularly how forest disturbances like wildfires and insect outbreaks affect stream ecosystems. He holds a PhD in Fisheries Science from Oregon State (2021), an MS in Biology from the University of Alaska Fairbanks (2011), and a BA in Environmental Studies from Lewis & Clark College (2005). Roon's research emphasizes whole-ecosystem approaches to understand food web dynamics and disturbance impacts. Current projects investigate wildfire effects on Pacific Northwest aquatic systems, including thermal regime changes, fish habitat vulnerability, and post-fire recovery mechanisms in the Hinkle Creek watershed. He applies system dynamics models and GIS mapping to quantify ecological responses to environmental changes. His work bridges applied science and natural resource management, addressing questions like how riparian thinning affects stream temperatures and food webs in redwood forests. He has published extensively on topics ranging from invasive species impacts to disturbance ecology, with a focus on linking ecological processes across spatial and temporal scales.

Agostino PoggiView profile

Professor

• Multi-Agent Systems
• Distributed Computing
• Software Engineering
• +3 more

Prof. Agostino Poggi is a Full Professor of Computer Engineering at the Department of Information Engineering, University of Parma. He teaches Distributed Systems and Software Engineering in the Faculty of Engineering, leading the Centro Universitario di Servizi per la Didattica di Ingegneria. His research focuses on multi-agent systems, web technologies, and distributed systems, coordinating EU projects like COLLABORATOR and CoMMA. He developed the open-source JADE framework for multi-agent systems. With over 200 publications, he received awards for scholarly contributions and innovation. He serves on editorial boards for journals like the International Journal of Agent-Oriented Software Engineering. Education: Laurea (cum laude) in Electronics Engineering (1987), Ph.D. in Computers & Electronics Engineering (1992) from University of Genoa Projects: Led EU-funded projects (e.g., AGENTCITIES, ALIS TECNET) and coordinated JADE’s research unit at University of Parma Key Contributions: JADE framework, agent-based modeling for epidemiology, actor-based systems, and social network analysis Research emphasizes agent-oriented software engineering, distributed systems, and applications in healthcare, social networks, and e-health. His work spans theoretical foundations to practical implementations, with focus on scalability and interoperability. Recent studies include fine-grained agent-based simulations for pandemic modeling and bankruptcy prediction using machine learning. Awards: 1988 System Research Foundation Award, 2001 Innovation System Award Teaching: Courses include Software Engineering, Distributed Systems, and Object-Oriented Programming

Ryan DubnicekView profile

Researcher

• Digital Humanities
• Machine Learning
• Natural Language Processing
• +3 more

Ryan Dubnicek is a Digital Humanities Specialist at the School of Information Sciences, University of Illinois. Contactable at Room 5027, 614 E. Daniel St., and via phone (217) 333-3280 or email rdubnic2@illinois.edu. His work intersects digital humanities, machine learning, and digital library infrastructure. Research focuses include: Optical Character Recognition (OCR) error analysis and correction Entity extraction and genre classification in large-scale digital collections Development of open analytical tools like TORCHLITE Application of BERT embeddings and transformer models for text mining Creation of parallel corpora for digital scholarship Linked Data integration for enhanced digital library access His recent projects engage deeply with the HathiTrust Digital Library, Samuel Johnson's Dictionary, and frameworks for computational analysis of literary corpora. Collaborative work emphasizes open data initiatives and real-world applications of AI in humanities research.

Bogdan VrusiasView profile

Visiting Professor

• Generative AI
• Large Language Models
• Foundation Models
• +6 more

Bogdan Vrusias is a Visiting Professor at the University of Surrey's School of Computer Science and Electronic Engineering (part-time). He concurrently serves as Global Head of AI and Data Engineering at The Economist. His academic journey began at Surrey as an undergraduate (BSc Computing and Information Technology, 1998), followed by a PhD in multi-modal information retrieval (2004) and an MBA (2010). He is a Fellow of the Higher Education Academy (FHEA). Education: PhD, University of Surrey (2004) MBA, University of Surrey (2010) BSc Computing and Information Technology, University of Surrey (1998) His research spans Generative AI, Large Language Models, Foundation Models, Machine Learning, Deep Learning, Cloud Computing, Natural Language Processing, and Computer Vision . His work focuses on developing scalable AI architectures and semantic technologies for real-world applications. Publications consistently explore semantic systems, neural networks, and multimodal information retrieval . Recent articles emphasize video annotation frameworks and P2P network architectures, while earlier work established foundations in self-organizing maps and feature selection for high-dimensional data. Awards: FHEA (Fellow of the Higher Education Academy) He previously directed UG/PG programs at Surrey and created pioneering courses like Web Hacking Countermeasures. His industry leadership includes founding tech startups and heading Amazon Web Services' AI/ML Specialist Solutions Architects team for EMEA. At The Economist, he drives AI and data transformation.

Mridul ThomasView profile

Assistant Professor

• Aquatic Ecology
• Climate Change Biology
• Phytoplankton Ecology
• +3 more

Dr. Mridul Thomas is an Assistant Professor at the University of Geneva, specializing in aquatic ecology with a focus on phytoplankton dynamics, climate change impacts, and experimental design. His research integrates field observations, modeling, and citizen science to understand how environmental drivers like temperature, nutrients, and predation shape aquatic ecosystems. Recent work emphasizes the importance of multi-driver experiments and the underappreciated role of unrealistic experimental scenarios in global change biology. Key research themes include phytoplankton community responses to warming, cyanobacterial dominance under eutrophication, and the ecological implications of species interactions (e.g., chytrid parasites). Dr. Thomas collaborates on projects like the CoFish initiative to monitor Lake Geneva's phosphorus dynamics through fisher-scientist partnerships. His work bridges micro-scale microbial processes with large-scale ecological patterns, leveraging both observational and theoretical approaches.

• Spatial Data Science
• Artificial Intelligence (AI)
• Geographic Information Science (GIScience)
• +7 more

Krzysztof Janowicz is a Professor at the University of Vienna and Head of the Department of Geography and Regional Research. Previously, he held full professorships at the University of California, Santa Barbara (UCSB) and Pennsylvania State University. He directs the Research Network Data Science and is Editor-in-Chief of the Semantic Web journal. His research focuses on Spatial Data Science, GeoAI, and knowledge graphs, emphasizing the integration of semantic and data-driven approaches. Education includes a PhD in Geoinformatics from the University of Münster and postdoctoral work at the Institute for Geoinformatics. Teaching includes courses on spatial data science, cartography, and geoinformatics, such as field trips to Scotland and North America. He leads projects like the KnowWhereGraph, a large-scale geo-knowledge graph for interdisciplinary applications. His work addresses AI sustainability, geographic diversity evaluation, and privacy in geospatial AI. He has directed UCSB’s Center for Spatial Studies and contributed to disaster risk management frameworks through ontologies like HIP.

• Natural Language Understanding
• Natural Language Processing
• Machine Learning
• +3 more

Dr. Prashant Khare is a Researcher at Queen Mary University of London's School of Electronic Engineering and Computer Science. His research focuses on Natural Language Understanding, Machine Learning, and Social Data Science, with applications to organizational communication, crisis information analysis, and internet standards. He has contributed to datasets like LEDA for decision dialogue analysis and explores linguistic markers of influence in online organizations. His work bridges computational methods with real-world challenges in communication and crisis management. Key research interests include dialogue modeling, NLP for organizational contexts, and cross-lingual crisis data classification. He has analyzed social graphs of technical communities like the IETF and studied the co-spread of misinformation during global health crises. His technical contributions span RFC errata analysis, decision detection algorithms, and semantic validity assessment in linked open data. Though no formal awards are listed, his publications reflect sustained engagement with interdisciplinary challenges at the intersection of computer science and social systems. His research often involves collaboration with industry and standards bodies, as seen in his work on RFC deployment and large-organization email analysis.

• Distributed Systems
• Cloud Computing
• High-Performance Computing
• +3 more

Thilo Kielmann is an Associate Professor at the Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Computer Systems department) and the Network Institute. His research focuses on distributed systems, cloud computing, and high-performance computing, with emphasis on resource management, data locality, and scalable infrastructure. He has authored 95+ research outputs and supervised 8 PhD theses. Education details are not explicitly listed, but his academic role implies advanced qualifications in computer science. His work contributes to UN Sustainable Development Goals through innovative computing solutions. Research interests include distributed file systems (e.g., MemEFS), resource disaggregation, energy-efficient scheduling (e-BaTS), and scalable VM management. His publications span conferences like HPDC and journals like Future Generation Computer Systems. No scientific awards are explicitly mentioned. He teaches four courses, including Computer Programming and Large Research Project in Computer Science. Labs/teams involvement is not detailed, but his research collaborations and conference roles (e.g., HPDC15 Chair) suggest active participation in academic networks.

Jacopo UrbaniView profile

Associate Professor

• Knowledge Graphs
• Data Stream Reasoning
• Semantic Web
• +4 more

Jacopo Urbani is an Associate Professor at Vrije Universiteit Amsterdam, affiliated with the Faculty of Science, Computer Systems department, and the Network Institute. His research focuses on Knowledge Graphs, Stream Reasoning, and Distributed Computing. He explores scalable reasoning techniques for large-scale datasets, integrating semantic technologies with real-time data processing. His work emphasizes practical applications of logic-based systems, including existential rules, probabilistic reasoning, and trigger graphs for efficient knowledge base materialization. Recent contributions address challenges in handling dynamic data streams and enhancing the scalability of semantic web technologies. Urbani has published extensively in top venues like the Semantic Web Conference (ESWC) and the International Conference on Principles of Knowledge Representation and Reasoning (KR). Notable projects include the VLog rule engine for knowledge graphs and the Tab2Know platform for extracting structured data from scientific tables. He supervises PhD theses in areas like stream reasoning and knowledge graph embeddings. His research also involves collaborative efforts with institutions worldwide, addressing topics such as data compression, distributed computing architectures, and hybrid reasoning systems.