Jiaoyan Chen is a Lecturer (Assistant Professor) in the Department of Computer Science at The University of Manchester, set to become a Senior Lecturer (Associate Professor) from July 2025. Previously, she served as a Senior Researcher at the University of Oxford and held postdoctoral roles at Heidelberg University. Her research focuses on neural-symbolic knowledge representation, ontology engineering, and integrating large language models with knowledge graphs. Education: PhD in Knowledge Reasoning and Predictive Analytics (Zhejiang University, 2011-2016) and BEng in Computer Science (Zhejiang University, 2007-2011). She also spent time as a visiting scholar at Zurich University (2014-2015). Research Interests include: Knowledge Graphs, Ontologies, Large Language Models, Retrieval Augmented Generation, and Machine Learning applications in knowledge-aware systems. She leads major grants such as the EPSRC New Investigator Award (EP/Y017706/1) and collaborates internationally through initiatives like the Manchester-Melbourne-Toronto Fund. Teaching: Leads units like 'Data Engineering Technologies' and 'Advanced Topics in Knowledge Representation'. She actively advises PhD students and co-develops tools like OWL2Vec* and DeepOnto. Service roles include Associate Editor of Transactions on Graph Data and Knowledge (TGDK), membership in the EPSRC Peer Review College, and leadership in ontology alignment initiatives like OAEI Bio-ML Track.
Dr. Rachel Seary is a Lecturer in Marine Conservation at the University of Kent's Durrell Institute of Conservation and Ecology (DICE). She holds an MSc from the University of St Andrews and a PhD in Geography from the University of Cambridge. Her work focuses on applied marine conservation solutions that balance ecological preservation with community needs, particularly in coastal and fishing communities. Key areas include dynamic ocean management, mangrove-fisheries interactions, and mitigating human-wildlife conflicts in fisheries. Professional Roles: Member of PICES Working Group 51, Editorial Board Member for Frontiers in Marine Science and Bulletin of Marine Science . Education: PhD in Geography, University of Cambridge (2019) MSc in Ecosystem-based Management of Marine Systems, University of St Andrews Research Interests: Social-ecological systems, sustainable fisheries, marine protected areas, and participatory conservation approaches. Her research spans global contexts including California, Indonesia, Cambodia, Greece, and the UK. Notable projects include studying whale-fishery interactions on the US West Coast and assessing mangrove-fisheries in South-East Asia. She advocates for interdisciplinary solutions to ensure biodiversity goals align with human well-being under climate and regulatory changes. Teaching includes modules on environmental sustainability, the Anthropocene, conservation policy, and climate change impacts. She supervises postgraduate research in marine conservation and resource management topics.
Professor Jason Dykes is a leading figure in the field of information and geovisualization at City, University of London, where he holds the position of Professor in the Department of Computer Science and co-directs the giCentre , a renowned research centre in visualization. He is affiliated with the School of Mathematics, Computer Science and Engineering and maintains an active research and teaching profile. His academic journey includes a PhD in Geography from the University of Leicester and extensive leadership in both research and education. Education: PhD in Geography, University of Leicester, 2000 MSc in Geographic Information Systems, University of Leicester, 1991 BA/MA in Geography, University of Oxford, 1989 Jason Dykes' research is centered on designing visual methods and tools for exploring, analyzing, and presenting information, with a strong emphasis on geographic data. His work integrates cartography, information visualization, GIScience, and human-computer interaction , leading to the development of innovative techniques such as geowigs, ODmaps, BallotMaps, and AttributeSignatures. He has published extensively in top-tier journals like IEEE Transactions on Visualization & Computer Graphics, with over 20 papers in the last decade, and co-authored the seminal book Exploring Geovisualization (2005). His research is supported by major funders including EPSRC and the EU, with projects like RAMP VIS (Covid-19 response) and VALCRI (criminal intelligence). The most recent articles highlight a consistent trend in applied and human-centered visualization , focusing on responsive design, education, pandemic modeling, and novel visual metaphors for complex data. His work increasingly emphasizes methodological rigor, design exposition, and the role of visualization in interdisciplinary and emergency contexts. Scientific Awards and Recognition: National Teaching Fellow, Higher Education Academy (2005) Best Paper Awards at GIS Research UK (consecutive years) Honorable Mentions, IEEE InfoVis (2009, 2010, 2016, 2018) Security Innovation Commercialisation Award (EU, 2022) Research Supervisor of the Year, City Student Union (2020) Innovations in Teaching Award and multiple teaching grants at City Jason Dykes has supervised eight PhD students to completion and advised many others, including notable researchers like Roger Beecham, Sarah Goodwin, and Susanne Bleisch. His teaching includes modules such as Visualizing Society and Data Presentation. He has received significant grant funding from UK research councils and the EU for projects like DIVA, VALCRI, and RAMP VIS. His service to the community includes leadership roles in IEEE VIS, ICA Commission on GeoVisualization, and editorial positions at IEEE TVCG and the Journal of Visualization and Interaction. He leads the giCentre , a dynamic research group that fosters innovation in visualization, and has been instrumental in establishing the field’s educational and methodological foundations through participation in Dagstuhl seminars and publications on visualization pedagogy.
Oliver Gasser is a researcher at the Max Planck Institute for Informatics (MPI-INF) and the Technical University of Munich (TUM), where he has co-lectured courses such as Advanced Computer Networking and Master Course Computer Networks. His research focuses on Internet measurement, security, and privacy, with a strong emphasis on IPv6, DNS, BGP, and web tracking technologies. His research interests include Internet measurement, IPv6 deployment, BGP security, DNS infrastructure, web tracking, privacy technologies, and network resilience. He has made significant contributions to understanding IPv6 hitlists, router fingerprinting, hypergiant content delivery networks, and consent banner manipulation on the web. His work combines large-scale active measurements with data analysis to uncover systemic issues in Internet infrastructure and privacy practices. The recent publications highlight a consistent focus on measurement-driven research across networking, security, and privacy. Trends include analyzing IPv6 adoption patterns, detecting covert tracking mechanisms in web cookies, evaluating security of Internet protocols like DNS and BGP, and improving measurement methodologies for large-scale network studies. His work often involves developing open tools and datasets that advance reproducibility in networking research. PAM 2023 Best Paper Award TMA 2023 Best Paper Award TMA 2023 Fast Track Award PAM 2018 Best Paper Award IRTF Applied Networking Research Prize 2018 IMC 2017 Community Contribution Award TMA 2017 Best Dataset Award CoNEXT 2023 Community Contribution Award Oliver Gasser has advised or co-advised over 40 master’s and bachelor’s theses at MPI-INF and TUM, demonstrating strong mentorship in academic research. He has led several measurement projects that have received external funding, including development of the IPv6 Hitlist Service and tools for analyzing web tracking. His community service includes extensive participation in program committees for major networking conferences such as IMC, CoNEXT, PAM, and TMA. He leads and contributes to several open research initiatives including the IPv6 Hitlist Service, SNMPv3 Measurement Service, MPTCP Measurement Service, DNS Observatory, and the BannerClick tool for automated cookie banner interaction. These platforms provide valuable resources for the global networking research community and support reproducible science.
Zakir Durumeric is an Assistant Professor of Computer Science at Stanford University, leading the Stanford Empirical Security Research Group. His research focuses on Internet security, trust, and safety, emphasizing large-scale network measurement and open-source tool development. He founded Censys, a platform providing global Internet device data, and maintains tools like ZMap, ZGrab, and Retina. Research interests include cybercrime prevention, censorship analysis, disinformation tracking, and platform governance for online harassment. Notable contributions include studies on the Mirai botnet, TLS certificate ecosystems, and vulnerabilities like Heartbleed and Logjam. Awards include the IRTF Applied Networking Research Prize (2015) and a Test of Time Award (2022). Teaches courses: CS155 (Computer & Network Security), CS356 (Systems & Network Security), and CS249i (Modern Internet). Advises over 20 students, including Catherine Han, Kimberly Ruth, and Liz Izhikevich. Develops open-source software such as ZMap Toolkit and ASdb, and maintains datasets like CrUX Top Million Websites. Recent work explores toxic online behavior, misinformation ecosystems, and regional censorship mechanisms in China. His lab’s tools are widely adopted in academia and industry for security research and policy guidance.
Dr. Gaël Kermarrec is a researcher at the Boundary Layer Meteorology Group , part of the Institute of Meteorology and Climatology within the Faculty of Mathematics and Physics at Leibniz University Hannover . His work focuses on atmospheric turbulence, GNSS applications, and remote sensing for environmental monitoring. Boundary layer meteorology Turbulence theory GNSS signal processing Terrestrial laser scanning Climate change impacts Geodetic time series analysis His research integrates advanced mathematical models like LR B-splines and Matérn covariance with large eddy simulations to study: Atmospheric turbulence effects on optical/GNSS signals Hydrospheric mass loading Deformation analysis of terrain/port infrastructure Climatic sea-level changes Machine learning for remote sensing The 15 most recent articles (2025-2023) demonstrate his focus on: GNSS-based turbulence detection AI-enhanced climate mapping Advanced surface approximation techniques Multi-sensor data fusion Stochastic modeling of geodetic observations Environmental impacts on optical measurements He has developed tools like the Klimascanner QGIS plugin for urban climate resilience and contributes to: Understanding atmospheric scale lengths Improving TLS/GNSS deformation monitoring Analyzing hydrospheric changes Wavefront modeling Ionospheric corrections
Benjamin Ricaud is an Associate Professor and Group Leader in Machine Learning at UiT The Arctic University of Norway's Department of Physics and Technology. His core affiliations include membership in the Machine Learning Group, Visual Intelligence center, and co-directorship of the Digital Technology Innovation Lab focused on Arctic-region tech startups. He also co-chairs the annual Northern Light Deep Learning conference. Ricaud's research spans: Fundamental ML : Graph signal processing, explainable AI, and generative models Applications : Microfossil classification, medical diagnostics (retinal aging), drug analysis, and climate data interpretation Emerging domains : Self-supervised learning and biological data analysis using Raman spectroscopy His recent publications (2020-2025) cluster in three domains: Graph ML methodologies (35%) Biomedical/biological applications (40%) Geoscience/climate informatics (25%) with consistent focus on interpretability and real-world data challenges. Teaching includes Image Processing (FYS-2010), Pattern Recognition (FYS-3012), and Machine Learning (FYS-2021). He leads outreach initiatives developing AI exhibits for Tromsø Science Centre.
Jay Pujara is a Research Associate Professor in the Department of Computer Science at the University of Southern California (USC), affiliated with the Viterbi School of Engineering and the Information Sciences Institute (ISI). He directs the Center on Knowledge Graphs and leads research in artificial intelligence, specializing in knowledge graph construction, scalable machine learning, and probabilistic models. Education : PhD in Computer Science (University of Maryland, 2016), MS and BS in Computer Science from Carnegie Mellon University (2005 and 2004), with minors in Robotics, Mathematical Sciences, and Logic & Computation. Research Interests : His work focuses on probabilistic models for dynamic data, knowledge graph construction, entity resolution, and applications in NLP and social network analysis. He emphasizes scalable algorithms and real-world impact in domains like finance, climate science, and healthcare. Awards : Includes the SWSA Ten-Year Award (2023), Best Paper Awards at IUI 2019 and ISWC 2013, and grants totaling over $9M from DARPA, NSF, and industry partners. Grants & Mentorship : Principal Investigator on projects like "Artificial Domain-Understanding and Collaborative Agency" (DARPA) and "Explainable and Robust AI Agents" (NSF). Mentored over 50 students in PhD, MS, and undergraduate programs, focusing on knowledge graphs, NLP, and machine learning. Labs & Teams : Leads ISI’s Knowledge Graph and Neurosymbolic AI teams, coordinating the Open Knowledge Network (OKN) and tools like KGTK. Active in academic service, including roles on PhD admissions committees and ISI’s Space Management Committee.
Jennifer Mason is an Associate Professor of Practice and Associate Director of the Geographic Information Science & Technology (GIST) Program at the University of Arizona. She holds a Ph.D. in Geography (GIScience) from Penn State University, an M.S. in GIScience from San Diego State University, and a B.A. in Geography from UCLA with a GIS&T minor. Her research focuses on GIScience, cartography, and geovisual analytics, particularly exploring uncertainty visualization in maps and spatial decision-making. She teaches courses such as Web GIS, Geovisualization, and Raster/Vector Spatial Analysis, emphasizing practical applications of geographic information systems. Jennifer's work bridges theoretical research and pedagogy, with a strong emphasis on improving cartographic design and usability for diverse audiences. Her publications consistently address spatial uncertainty representation, cognitive aspects of geographic visualization, and open-source tools for education. She has contributed to advancing methodologies for visualizing spatial data uncertainty through noise annotation lines and thematic mapping techniques.
Thierry Badard is an Associate Professor at the Department of Geomatics Sciences , Université Laval, where he also serves as Director of the Center for Research in Geospatial Data and Intelligence (CRDIG) . With over 28 years of experience in geospatial science, he leads research initiatives at the intersection of GeoAI , LiDAR processing , and smart city technologies . Director, CRDIG (2016-2022) Steering Committee Member, Big Data Research Centre (CRDM) Researcher, Institute for Intelligence and Data (IID) Research Expertise spans geospatial big data, GeoNLP, and IoT applications for digital twins. His work addresses flood risk modeling , 3D urban analytics , and environmental monitoring through AI-driven solutions. Recent publications focus on contrastive learning for LiDAR segmentation and geospatial ontologies for early warning systems. Grant Leadership includes collaborative projects on smart insurance analytics (2018-2025), Arctic bioaerosol research (2019-2025), and Quebec-Morocco digital twin partnerships (2022-2023). He has advised 15+ graduate students in geomatics and related fields.
Juan-Pablo Correa-Baena is an Associate Professor at the Georgia Institute of Technology , holding the Goizueta Early Career Faculty Chair in the School of Materials Science and Engineering. He leads the Materials for Solar Energy Harvesting and Conversion research initiative at the Institute for Materials (IMat) and Strategic Energy Institute, aiming to consolidate Georgia Tech's expertise in photovoltaics and interdisciplinary energy research. Education: PhD in Environmental Engineering, University of Connecticut (2014) MS in Environmental Engineering, University of Connecticut (2011) BS in Management and Engineering for Manufacturing, University of Connecticut (2008) His research focuses on the chemistry-structure-property relationships of low-cost semiconductors for optoelectronic applications. Key areas include halide perovskites , nanoscale control , and advanced deposition/characterization techniques . He develops atomic layer deposition and synchrotron-based imaging to address metastable material behavior. Recent publications highlight innovations in dimensional control , machine learning for thermal stability , and flexible photovoltaic devices . His work integrates materials synthesis , quantum phenomena , and industrial scalability . Scientific recognition: Highly Cited Researcher (Web of Science, 2019–2021) Nature Index Leading Early Career Researcher in Materials Science (2019) NSF, DoE, and industry-funded projects Students and team: He advises 14 graduate students and postdocs, including Sanggyun Kim, Diana LaFollette, and Leonardo Josué Lugo Salas, fostering interdisciplinary collaboration through workshops and symposia.
Asunción Gómez Pérez is a Spanish computer scientist and Full Professor at the Technical University of Madrid (UPM) . She currently serves as Vice-Rector for Research, Innovation and Doctoral Studies at UPM and holds a seat at the Real Academia Española . She has authored over 300 publications and accumulated 20,000 citations. Education : PhD in Computer Science (UPM, 1993), MBA (Comillas Pontifical University) Leadership Roles : Director of the Department of Artificial Intelligence (2008–2016), Academic Director of AI Master’s/PhD programs (2009–2016), Executive Director of UPM’s Artificial Intelligence Lab (1995–1998) Her research focuses on Semantic Web and Ontology Engineering , with applications in knowledge representation, machine-machine communication, and multilingual data integration. She pioneered methods for ontology validation, metadata licensing, and AI-driven social inclusion. Key publication trends include: Ontology evaluation frameworks (e.g., OOPS!) Linked Data quality models and validation tools Multilingual and cross-lingual AI applications Interoperability solutions for smart cities and healthcare Machine Learning for social exclusion prediction Ontology-driven library and lexicography systems Scientific Awards Fellow of the European Academy of Sciences Ada Byron Prize She has led projects like the NeOn Methodology for ontology development and contributed to the European framework for linked data rights (LD Terms). Her work bridges theoretical research with practical implementations in AI and Semantic Technologies.
Robert P. Anderson is a Professor of Biology in the Division of Science at City College of New York (CCNY), part of the City University of New York (CUNY) system. His research laboratory is located in Marshak Science Building (Room 810), with additional affiliation as a Research Associate at the American Museum of Natural History (AMNH) Mammalogy Department. As a Highly Cited Researcher (2019-2023) and AAAS Fellow (2023), he leads an interdisciplinary biogeography research program focused on modeling species niches and distributions. Dr. Anderson's research spans biodiversity modeling, biogeography, and ecology with specialization in mammals. His lab develops ecological modeling software widely applied in conservation biology, invasive species management, zoonotic disease studies, and climate change impact assessments. Key research themes include: Characterizing spatial configuration of environmental suitability for species Developing machine learning approaches (particularly Maxent) for species distribution modeling Studying climate change effects on biodiversity Conservation applications of biogeographic models Neotropical mammal systematics and ecology His work has resulted in significant software contributions including Wallace, ENMeval, and spThin, with recent publications emphasizing methodological improvements in species distribution modeling and conservation applications. The lab maintains active projects funded by NASA and the National Science Foundation, focusing on small mammals of North and South America. Scientific recognition includes: AAAS Fellow (2023) Web of Science Highly Cited Researcher (2019-2023) Blavatnik Science Scholar (New York Academy of Sciences) Most Downloaded Paper in Ecography (2023-2024) Most Cited Paper in Ecography (2023) Dr. Anderson mentors graduate students through the CUNY Graduate Center and CCNY Master's programs, with recent advisees receiving prestigious awards including the ASM Horner Award and NASA FINESST Fellowship. His lab trains students in environmental biology through interdisciplinary research combining fieldwork, morphology, climatology, remote sensing, physiology, and genetics. Current lab members include Andrew Gaier (NASA Fellow), Mariano Soley-Guardia, and Kass (lead author on highly cited Wallace v2 paper). The Anderson Lab operates from CCNY's Marshak Science Building as part of the university's biodiversity group studying ecology, evolution, and geography of life on Earth. The lab emphasizes software co-design between end-users and developers to enhance conservation utility, with recent work focusing on neighborhood approaches for range estimation and operationalizing expert knowledge in species assessments.
Emanuel Sallinger is a Full Professor at TU Wien's Databases and Artificial Intelligence Group and Vice Dean of Academic Affairs for Business Informatics and Data Science. He leads the Knowledge Graph Lab, focusing on scalable knowledge-based systems, reasoning in knowledge graphs, and AI integration. His research spans computational logic, database theory, and blockchain applications. Education: PhD in Computer Science (awarded 'sub auspiciis praesidentis rei publicae'), Master's degrees in Computational Intelligence and Informatics Management, and a Bachelor's in Software and Information Engineering. Research Interests: Knowledge graphs (construction, reasoning, scalability), logic-based systems, AI/ML integration with databases, enterprise architecture modeling, and financial knowledge systems. His work emphasizes practical applications like enterprise modeling, sustainable waste management, and regulatory compliance. Grants & Projects: Lead Vienna Science and Technology Fund (WWTF)-funded Knowledge Graph Lab. Involved in projects like 'Knowledge Graph-driven Tour Management' (sustainability), 'SustainGraph' (waste processing), and 'Enterprise Architecture Knowledge Graphs'. Teaching: Offers courses on Knowledge Graphs, Generative AI, Database Systems, and research methodology. Supervises doctoral and master's students in AI, databases, and knowledge representation. Labs/Teams: Knowledge Graph Lab at TU Wien, collaborating with industry on blockchain-based systems, financial AI, and enterprise architecture frameworks.
Natalia Villanueva-Rosales is an Associate Professor in the Department of Computer Science at The University of Texas at El Paso (UTEP). As Co-Principal Investigator at the NSF-funded Cyber-ShARE Center of Excellence, she leads the iLink Research Group focusing on semantic technologies and smart city initiatives. Ph.D. in Computer Science, Carleton University (2011) M.Sc. in Artificial Intelligence, University of Edinburgh (2005) B.Sc. in Computer Science & Statistics, Universidad Panamericana & CINVESTAV-IPN (2002) Her research bridges Semantic Web technologies with Smart Cities applications, particularly in Water Sustainability and Senior Mobility . Key projects include ontology-based frameworks for freight performance data integration and community-driven smart mobility solutions. Recent publications demonstrate her interdisciplinary approach across Environmental Informatics (2022-2025) and Urban Mobility (2019-2022). She holds editorial and leadership roles in semantic science initiatives while actively mentoring through the ACM-W WICS student group. 2019 HEENAC Education Award 2019 NCWIT Undergraduate Research Mentoring Award Her NSF grants include IRES-1658733 for US-Mexico Smart Cities collaboration and OAC-1835897 for the SWIM water sustainability project. The iLink Research Group under her leadership develops ontological frameworks for cross-domain data integration and trust establishment in collaborative environments.
