Kelly Filer Robinson is an Associate Professor and Assistant Unit Leader at the University of Georgia's Georgia Cooperative Fish and Wildlife Unit. She holds a Ph.D. in Forest Resources (Fisheries Science) from the University of Georgia (2011), an M.S. in Marine Biology from the College of Charleston (2006), and a B.A. in Biology and Spanish from the University of Virginia (2001). Her research focuses on fisheries and aquatic sciences, emphasizing invasive species management, structured decision-making frameworks, and ecological modeling. Key areas include controlling invasive Asian carps and sea lampreys in the Great Lakes, analyzing round goby invasions' impacts on native species, and addressing climate change challenges in aquatic ecosystems. She also explores interdisciplinary approaches to integrate social and ecological sciences in natural resource management. Her work bridges theoretical and applied ecology, with contributions to decision support tools for barrier removal prioritization, watershed restoration, and collaborative management strategies. She leads research on the adaptive capacity of benthic ecosystems and has published extensively on population dynamics and species interactions. Her lab affiliations include the Georgia Cooperative Fish and Wildlife Unit, a collaborative hub for fisheries and wildlife research.
David Newman serves as a Senior Enterprise Fellow within the Electronics and Computer Science department at the University of Southampton's Faculty of Engineering and Physical Sciences. His research focuses on the intersection of web science, scientific workflow systems, and semantic technologies, with particular emphasis on developing infrastructure for collaborative research environments. His primary research interests center around Web Science , Scientific Workflow Systems , and Research Objects , where he investigates how digital platforms can enhance scientific collaboration. Newman's work explores the social dimensions of scientific computing through projects like myExperiment, examining how researchers share and reuse computational workflows. His research bridges technical infrastructure development with social computing aspects of scholarly practice, contributing to the evolution of virtual research environments that support modern scientific collaboration across disciplines. Analysis of Newman's publication history reveals consistent contributions to the development of semantic platforms for scientific collaboration, particularly through the myExperiment project. His work spans from foundational research on scientific social objects (2011) to practical implementations like Erica the Rhino (2016) that demonstrate real-world applications of workflow systems. The publications show progression from theoretical frameworks for research objects toward applied implementations in digital art and news enrichment, reflecting both technical depth and interdisciplinary reach. While no specific scientific awards are documented in the available materials, Newman's contributions to the myExperiment platform represent significant impact in the research infrastructure community. His work has helped shape how scientists share and discover computational workflows, contributing to more efficient and collaborative research practices across multiple disciplines. As a Senior Enterprise Fellow, Newman contributes to the university's research ecosystem through development of digital research infrastructure rather than traditional student supervision. His work focuses on creating platforms that support researcher collaboration at scale, with implications for how scientific communities organize and share knowledge in the digital age. The myExperiment platform, in particular, has served as an important testbed for concepts now mainstream in research computing. Newman's research is closely associated with the Web & Internet Science group at Southampton, where he has contributed to the development of semantic technologies for research communities. His work represents an important strand of the university's leadership in web science and digital research infrastructure, connecting technical innovation with practical applications for scholarly communication and collaboration.
Badis Hammi is an Assistant Professor at Telecom SudParis, specializing in cybersecurity and network security. His research focuses on IoT security, blockchain applications, botnet detection, and vehicular networks. He has authored numerous peer-reviewed articles on topics such as malware analysis, phishing detection frameworks, and decentralized security solutions in smart homes and healthcare sectors. Education PhD in Cryptography and Security (2015), Université de Technologie de Troyes Research Interests Cybersecurity frameworks for IoT and blockchain systems Malware detection methodologies PKI security in cooperative intelligent transportation systems (C-ITS) Phishing prevention using graph neural networks Botnet activity analysis in cloud environments Recent Article Trends His recent work emphasizes blockchain's role in mitigating supply chain fraud, improving smart home security, and securing vehicular communications. He also explores machine learning approaches for detecting Sybil attacks and network anomalies in distributed systems. Grants & Advising Active in collaborative projects with industry partners on vehicular network security Advises on EU-funded initiatives for blockchain-based authentication systems Labs/Teams Affiliated with the SAMOVAR research lab at Telecom SudParis, focusing on network and system security.
Merethe Skårås is an Associate Professor in Education at MF University College of Theology, Religion and Society. She previously held positions at OsloMet and Svendstuen barneskole, and conducted guest research at George Mason University (USA) and Cape Peninsula University of Technology (South Africa). Her work focuses on education in emergencies, citizenship education, and history teaching in post-conflict societies like South Sudan. Skårås holds a PhD in Educational Sciences from MF University College (2013–2019), a Master's in Multicultural and International Education from Oslo Metropolitan University (2007–2009), and a primary teacher education degree from Hamar University College (2000–2004). She has extensive teaching experience in Norwegian primary schools since 2004. Her research investigates how history education constructs national narratives and supports reconciliation in divided societies. Key themes include authoritarian cosmopolitan citizenship, curriculum design in post-independence contexts, and the role of textbooks in shaping national identity. She has conducted fieldwork in Sudan/South Sudan analyzing how recent violent histories are taught in schools. Skårås' publications (2023–2016) critically examine South Sudanese education systems, focusing on history curriculum politics, citizenship education challenges, and the intersection of global-local identities. Her work emphasizes socially just pedagogical approaches in conflict-affected regions. She has held voluntary roles as Web Coordinator for the Comparative and International Education Society (CANDE) and served on Oslo Metropolitan University's PhD candidate coordination committee.
Oksana Zavalina is a Professor at the University of North Texas, specializing in information organization, metadata standards, and digital library systems. She holds a Ph.D. and M.L.I.S. from the University of Illinois (Urbana-Champaign) and a B.S. in Library and Information Science from Kiev State Institute of Culture. Her work focuses on metadata quality evaluation, digital language archives, and interdisciplinary collaboration in cultural heritage preservation. Her research interests include information retrieval systems, semantic web technologies, and the application of metadata standards in diverse contexts. Notable projects include the LAMlang Arc Training Project and studies on AI-generated metadata accuracy. She has also explored metadata practices in Arabian Gulf academic libraries and audiovisual resources in Kuwaiti institutions. Zavalina has published extensively on metadata change analysis, digital library infrastructure, and user interactions with digital collections. Her work bridges library science, linguistics, and technology to address challenges in knowledge representation and preservation. She actively contributes to workshops on historical linguistic datasets and digital archive stewardship, emphasizing education and community engagement in archival practices.
Håkan Örman is an Associate Professor at the Department of Biomedical Engineering, Linköping University, within the Faculty of Science and Engineering. He is actively engaged in teaching, research, and academic leadership, including serving as Chairman of the Board of Studies for Electrical Engineering, Physics, and Mathematics. His work bridges engineering and healthcare through digital innovation. His research focuses on health informatics and e-health , particularly in developing information models, ontologies, and knowledge representation systems to create interconnected, learning healthcare ecosystems. He advocates for rational use of digital tools to enhance accessibility, safety, and personalization in healthcare. The recent publications highlight a strong trend in digital health infrastructure , interoperability standards (e.g., openEHR, SNOMED CT), and educational development in engineering and health informatics. His work spans technical architecture, semantic modeling, and pedagogical innovation. Håkan is passionate about pedagogical development and views students as co-creators of knowledge. He teaches in the Master’s program in Biomedical Engineering, the Medical Program, and interdisciplinary eHealth courses. He collaborates with Didacticum for educational advancement and emphasizes dialogue, reflection, and sustainable skill development. He is involved in interdisciplinary initiatives at Linköping University, where students from medicine and engineering jointly develop digital health solutions. This reflects his commitment to collaborative, real-world problem solving and institutional investment in e-health education and research.
Bedoor AlShebli is an Assistant Professor of Computational Social Science at New York University Abu Dhabi (NYUAD), affiliated with the Division of Social Science. She holds a PhD in Interdisciplinary Engineering from Masdar Institute of Science and Technology, an MSc in Computer Science from the University of Illinois Urbana-Champaign, and a BSc in Computer Science from Kuwait University. BSc in Computer Science – Kuwait University MSc in Computer Science – University of Illinois Urbana-Champaign PhD in Interdisciplinary Engineering – Masdar Institute of Science and Technology (Khalifa University) Her research lies at the intersection of data science, machine learning, and social science, with a strong focus on the Science of Science . She investigates how diversity—particularly ethnic and gender diversity—affects scientific collaboration and impact, and examines structural inequities in academic publishing. Her work also explores disinformation in socio-technical systems, AI research collaboration between global powers, and the career trajectories of postdoctoral researchers. Her recent publications, appearing in Nature Human Behavior , Nature Communications , Science Advances , and PNAS , reveal trends in academic equity, scientific collaboration, and the use of computational methods to study social systems. Many of her studies employ large-scale data analysis and network science to uncover systemic patterns in science and society. Nature Human Behavior (2023): Gender inequality and self-publication among academic editors PNAS (2023): Underrepresentation of non-white scientists in editorial roles and citation gaps Scientific Reports (2022): Beijing’s central role in global AI research PNAS (2025): Postdoc productivity as a predictor of academic success Nature Human Behavior (2025): Impact of retractions on publishing careers Her research has been widely covered in Nature , Physics World , Forbes , Inside Higher Ed , and APS Physics Magazine , highlighting its societal relevance. She has contributed to policy discussions, including a policy brief on international science faculty in Saudi Arabia. She actively mentors undergraduate students through the Computer Science Capstone program and teaches courses in Computational Social Science and Applied Data Science. She co-organized the Winter Institute of Computational Social Science at NYUAD in 2024, fostering regional capacity in data-driven social research. Dr. AlShebli leads a research effort that combines rigorous computational methods with deep social inquiry, contributing to both scientific understanding and policy-relevant insights on equity and innovation in science.
Talal Rahwan is an Associate Professor of Computer Science at New York University Abu Dhabi and a Global Network Associate Professor at the Courant Institute of Mathematical Sciences, New York University. He leads the Data Science and AI Lab and is actively involved in cutting-edge research at the intersection of artificial intelligence, computational social science, and data science. Education: BEng, University of Aleppo PhD, University of Southampton (2007) His research focuses on artificial intelligence, multi-agent systems, game theory, and computational social science, with a strong emphasis on ethical and societal implications of AI. His work investigates fairness in academic publishing, algorithmic bias, human-AI cooperation, disinformation, and social network privacy. He has published extensively in top journals such as Nature Communications , Nature Human Behaviour , Nature Machine Intelligence , and PNAS . The 15 most recent publications reveal a consistent trend toward understanding the societal impact of AI, particularly in education (e.g., ChatGPT in homework), equity (racial and gender disparities in publishing), and security (disinformation attacks on infrastructure). His work combines computational modeling with large-scale data analysis to address real-world challenges. Scientific Awards: IEEE Computer Society's AI’s 10 to Watch British Computer Society's Distinguished Dissertation Award Dean’s Award for Early Career Researcher, University of Southampton Best Parallel Talk Award, IC2S2 Best Poster Award, IC2S2 Talal Rahwan has advised numerous PhD and postdoctoral researchers, many of whom have gone on to academic positions. He has secured significant research recognition and media coverage, and leads an active lab focused on data science and AI for societal good. His lab has produced influential work on hiding identities in networks, bias in recommendation systems, and the ethical dimensions of human-machine interaction.
Lukasz (Luke) Ziarek serves as Associate Dean for Academic Affairs and Associate Professor in the Department of Computer Science and Engineering at the University at Buffalo's School of Engineering and Applied Sciences. His work bridges theoretical computer science with practical systems engineering, focusing on real-time capabilities in distributed environments and safety-critical applications. His educational foundation includes a PhD in Computer Science from Purdue University (2011) and a BS in Computer Science from the University of Chicago (2003). Ziarek's research centers on formal verification of distributed protocols , real-time systems engineering , and mobile/embedded computing . He pioneers session type theory for IoT security, develops real-time variants of Android (RTDroid) and Standard ML (RTML), and investigates UAV software reliability. His work consistently addresses the tension between theoretical guarantees and practical system constraints in concurrency, timing, and security. Recent publications (2022-2025) reveal three dominant trajectories: formal methods for rate-based session types in IoT protocols, performance analysis of visual SLAM systems for robotics, and security vulnerabilities in embedded platforms like ARM TrustZone. These threads converge on ensuring correctness and timeliness in resource-constrained distributed systems. His scientific accolades include the IEEE Region One Technological Innovation Award (2023) and NSF CAREER Award (2018), reflecting dual excellence in research and education. IEEE Region One Technological Innovation (Academic) Award, 2023 President Emeritus and Mrs. Meyerson Award for Distinguished Undergraduate Teaching and Mentoring, 2022 NSF CAREER Award, 2018 SEAS Early Career Teacher of the Year, 2016 Halstead Award for Outstanding Research in Software Engineering, 2009 Intel Fellowship, 2008 GAANN Fellowship, 2004 Ziarek directs significant research initiatives including a $900K NSF UAV infrastructure project (as PI) and a $1.7M MRI grant for connected vehicle testing. His funding portfolio spans real-time systems, compiler design, and pocket-scale data management, emphasizing collaborative, interdisciplinary approaches to software reliability. CRI:CI-New UAV Infrastructure ($900K, PI 31%) NSF CAREER: Real-time Object-Oriented Systems ($500K, PI 100%) MRI: iCAVE2 Vehicle Testing ($1.7M, co-PI 14%) III: Just-in-Time Data Structures ($499K, co-PI 50%) II-EN: MLton Compiler Research ($606K, PI 63%) He leads an open-source ecosystem including RTDroid (real-time Android), Multi-MLton (parallel SML compiler), and BlueSeal (Android security analyzer), fostering community-driven advances in systems software.
Dolors Canals Ametller is a Full Professor at the Universitat de Girona in the Department of Public Law, specializing in Administrative Law. She leads the Research Group in Administrative Law (Grup de Recerca en Seminari de Dret Administratiu) and contributes to the Pere Bahí Housing Chair. Her work bridges legal frameworks with emerging technologies, focusing on digital transformation in public administration. Current research projects: Digital Privacy Evaluation (CoDiRa) , Climate Change Risk Regulation , and EU Normative Processes . Advisory roles: Expert for Catalonia's Generalitat transformation strategy (2024-2025), OECD regulatory quality assessments (2010-2011), and Spanish government accountability frameworks (2021-2022). Her academic output reveals trends in cybersecurity , digital privacy , and AI governance for public services, alongside gender impact assessments and administrative simplification strategies. Recent publications analyze hybrid security threats in digital public services and collaborative economy implications for local governments. Notable contributions include co-editing La digitalización en los servicios públicos (2023) and directing Ciberseguridad. Un nuevo reto (2021), with methodological expertise in regulatory impact assessments and EU policy alignment.
Stefan Ćirković is a Teaching Associate in the Department of Information Technologies at the Faculty of Technical Sciences in Čačak, University of Kragujevac. His office is located at Saint Sava 65, 32102 Čačak, Serbia. He is currently pursuing doctoral studies in Information Technology (2023–present) at the same institution. Education: Doctoral Academic Studies – Information Technology, University of Kragujevac (2023–present) Master of Academic Studies – Information Technology, University of Kragujevac (2022–2023) Basic Academic Studies – Information Technology, University of Kragujevac (2018–2022) Specialized Program – Cybersecurity, University of Kragujevac (2024) Research Focus: Ćirković specializes in applied artificial intelligence with significant work in cybersecurity, medical imaging, and network systems. His research demonstrates strong emphasis on practical AI implementations including real-time object detection (YOLO algorithm), anomaly detection in networks, federated learning for healthcare applications, and cybersecurity techniques using large language models. His work frequently intersects with medical informatics, particularly in diagnostic applications. Publication Trends: Recent publications (2024–2025) show predominant focus on AI/ML applications across multiple domains. Cybersecurity remains a core theme with novel approaches to web application security and network anomaly detection. Medical applications feature prominently, especially in diagnostic imaging (kidney stones, skin cancer) and hemodialysis optimization. Methodologically, there's consistent exploration of deep learning architectures and real-time systems. Laboratory Affiliations: Associated with the Computer Science Laboratory at the Faculty of Technical Sciences in Čačak. Utilizes institutional resources including the Moodle e-learning platform and Microsoft 365/Teams infrastructure for academic activities.
Sabine von Mering is a Biological Data Scientist at the Museum of Natural History Leibniz Institute for Evolution and Biodiversity Science in Berlin, Germany. Her work focuses on opening up and connecting natural history collections with particular attention to collection agents, including marginalized groups, research expeditions, and linked entities such as objects, localities, publications, and archival material. Her research spans biodiversity informatics, data science applications in natural history collections, plant systematics (particularly of plant families like Caryophyllaceae and Juncaginaceae), and the ethical dimensions of collection management. Dr. von Mering is particularly known for her work on making collection data more accessible through linked open data standards and for her research on the historical context of collections, including colonial-era collecting practices. Opening up and linking type catalogues in Wikidata Wikidata for Botanists and Linked Open Data Research on women honored in plant genera Provenance research on collections from colonial contexts Community curation of research expeditions data She actively contributes to several major initiatives including the Collectors project, the FIND working group (Women in natural history), and the international WOMNH network. She also participates in the TDWG Task Group on Modelling Research Expeditions and the Distributed System of Scientific Collections (DiSSCo) initiative. Dr. von Mering's scientific work demonstrates a strong commitment to interdisciplinary collaboration and the application of modern data science techniques to traditional natural history questions. She has made significant contributions to understanding taxonomic relationships within plant families and to developing better data models for representing the complex histories of museum collections.
Shahrear Iqbal is an Adjunct Associate Professor at Queen's University and a Cyber Security Researcher at the National Research Council (NRC) Canada . He holds a PhD in Cybersecurity (2017) and MSc in Combinatorial Optimization (2011) from Queen's University, along with a BSc in Computer Science and Engineering (2008) from Bangladesh University of Engineering and Technology. Research Focus: Security and Privacy of Smart Systems, including in-vehicle security, self-aware operating systems, IoT-cloud security, and AI-driven cybersecurity. Teaching: Previously taught CISC490: Cybersecurity at Queen's University. Key Projects: Droid Mood Swing (DMS) for context-aware Android security policies Securing ECU Communications in connected vehicles FCFraud for user-side click-fraud detection
Susan Halford is a Professor of Sociology at the University of Southampton and Co-director of the ESRC Centre for Sociodigital Futures at the University of Bristol. She co-founded the Web Science Institute and specializes in the politics and practices of digital data, infrastructures, and artifacts. Key research areas include sociomaterial practices in semantic Web development, epistemological politics of AI, and critical data infrastructure studies. Her work with semantic linked data and symbolic AI demonstrates the contested processes of knowledge representation at scale. She led an interdisciplinary project funded by the Economic and Social Research Council to model social class, aging, and health through semantic Web tools. This research revealed tensions between theoretical rigor and pragmatic computational limitations in ontology design and temporal reasoning. Scientific awards: Economic and Social Research Council grant ES/M0003809/1.
Jussara M. Almeida is an established computer science researcher specializing in social network analysis, misinformation detection, and human mobility modeling. Her extensive publication record (1996–2025) demonstrates active research in web science, political communication on messaging platforms (WhatsApp/Telegram), and cloud systems. She frequently collaborates with Brazilian institutions and international partners on large-scale data projects. Research Focus: Her core interests include: Modeling information diffusion in encrypted messaging apps (WhatsApp/Telegram) Predicting human mobility patterns and privacy implications Analyzing political discourse and election-related coordination online Developing computational methods for misinformation detection Optimizing cloud/edge computing performance Publication Trends: Recent work (2021-2025) shows intensified focus on: Telegram's role in political mobilization and information dissemination Advanced techniques for identifying fake news websites and image-based misinformation Privacy-preserving mobility analysis and edge computing Child safety in live-streaming platforms Collaborations & Impact: Key collaborators include Marcos André Gonçalves, Fabrício Benevenuto, and Marco Mellia. Her research provides critical insights into real-world problems like election integrity, platform governance, and user privacy.
