Philip Leroux is a Postdoctoral Researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology. He serves as an IOF Innovation Officer at IMEC, focusing on smart city technologies and IoT infrastructure. His research interests span Smart Cities Internet of Things (IoT) Wireless Networks Context-Aware Systems Resource Provisioning Electromagnetic Field Monitoring . His recent publications analyze RF-EMF exposure sensing networks IoT-based resource provisioning frameworks 5G network anomaly detection semantic intelligence for media automation mobile application usage prediction . These works emphasize wireless network optimization, smart city infrastructure, and cross-disciplinary IoT solutions.
Gregory Van Seghbroeck is a postdoctoral researcher at Ghent University's Faculty of Engineering and Architecture, Department of Information Technology (EA05). His work focuses on cloud computing, big data systems, and smart city infrastructure. Affiliation: Ghent University, IMEC research group Research Trends: Data placement optimization, workflow management, low-latency querying, cloud-native architectures He has supervised doctoral projects including Thomas Vanhove (2018), Leandro Ordonez Ante (2022), and currently advises Stan De Groeve (2025-2026). Key publication themes include: Interactive querying for latency-sensitive applications Geo-distributed data/cloud resource allocation Workflow orchestration frameworks (BRAHMA, SpeCH) Smart city data infrastructure
Christopher Goranson is a Professor at Carnegie Mellon University's Heinz College , specializing in GIS, data visualization, and design innovation at the intersection of public policy, technology, and analytics. He has extensive experience in federal government initiatives, including roles at 18F and as a Presidential Innovation Fellow during the Obama Administration. His work focuses on agile software strategies, user-centered design, and geospatial analysis for public health. Education: Master of Geographic Information Systems (Penn State University) Research Interests include GIS applications in public health, digital service modernization, and design thinking for policy innovation. His projects span spatial analysis, big data design, and technology-driven solutions for government agencies. Scientific Awards : National Science Foundation award for disease cluster detection research
Professor Tobias Blanke is a University Professor of Artificial Intelligence and Humanities at the University of Amsterdam and affiliated with King’s College London. His academic background spans computer science and political philosophy. He holds a dual role as Professor of AI and Humanities at UvA and Professor of Social and Cultural Informatics at King’s, where he previously served as Department Head (2016–2019). His research focuses on AI ethics, big data applications in human sciences, and critical digital practices. Key areas include algorithmic governance, predictive policing, and digital platform critique. Blanke leads projects like the European Holocaust Research Infrastructure (EHRI) and Our Data Ourselves, exploring datafication’s societal impacts. He directed DARIAH (2012–2016), a European Digital Humanities infrastructure. Awards include the ISA-STAIR award (2022) for Algorithmic Reason . His work bridges technical and normative dimensions of AI, emphasizing ethical implications and interdisciplinary collaboration. Blanke’s grants include an €8M EU grant for Holocaust research infrastructure and funding for born-digital data projects. He collaborates with institutions like the Open Data Institute and TacticalTech. His affiliations include the King’s Centre for Technology, Ethics, Law & Society (TELOS).
Yue Jiang is an incoming Assistant Professor at the University of Utah (Fall 2025) and is currently finishing her Ph.D. at Aalto University and the Finnish Center for Artificial Intelligence (FCAI). Her research focuses on human-centered technologies in HCI, computer vision, and deep learning, particularly in computational user interface understanding, eye tracking, and adaptive GUI layouts. She has held visiting roles at Carnegie Mellon University (CMU) and collaborated with institutions in Canada and the UK. She serves on program committees for CHI, VL/HCC, and IUI, and has organized computational UI workshops at CHI conferences. Education: Ph.D. in Intelligent Systems (Aalto University & FCAI, 2025) Visiting Ph.D. Student (CMU, 2024) M.Sc. in Computer Science (University of Maryland, 2020) B.Sc. in Computer Science (University of Toronto, 2018) Research Interests: Yue explores computational representations of UIs, human behavior modeling via eye tracking and motion capture, and adaptive interfaces. Her work bridges HCI, computer vision, and machine learning to enhance human capabilities through AI-driven systems. Awards: Meta Research PhD Fellowship (2023–2025) Heidelberg Laureate Forum Young Researcher (2024) Google Europe Students with Disabilities Scholarship (2022) Advising & Grants: Yue mentors students in areas like multimodal generative AI and seeks researchers for her group. She has received grants from FCAI, Adobe Research, and the National Science Foundation. Labs & Collaborations: Active in the Computational Behavior Lab (Aalto) and BIG Lab (CMU), she collaborates on projects like OR-Constraints for adaptive GUIs and graph-based UI modeling.
Markus Eckl is a Professor for Digitisation in Social Work at the Faculty of Social Work, Fulda University of Applied Sciences. His research focuses on digital transformation in social work, quantitative text analysis, social network analysis, and the economisation of social work. He leads projects like Social Work Research Map and generative AI applications in social work education. Key research areas include: Digital archiving and web analytics for historical discourse analysis Ethical challenges of big data in social work Collaborative networks in social work academia Geospatial systems (GIS) in social research His publications emphasize interdisciplinary methods from digital humanities and computational social science. Current projects involve European alliances like E³UDRES² for rural region development.
Fenwick McKelvey is an Associate Professor in Information and Communication Technology Policy at Concordia University's Department of Communication Studies. He co-directs Concordia's Applied AI Institute and leads the Machine Agencies working group at Milieux Institute. His research focuses on digital politics, AI governance, and internet policy, with a particular interest in network neutrality and algorithmic media. Education: PhD in Communication and Culture (York University/Ryerson University), MA in Communication and Culture (York/Ryerson), BA in Multidisciplinary Studies (Dalhousie University) McKelvey's research spans critical AI studies, computational political communication, and internet history. His work examines how algorithms shape democratic processes, media governance, and policy frameworks. He has published extensively on topics like digital disinformation , political bots , and platform studies . His recent publications include analyses of generative AI's societal impacts and special issues co-edited on topics like optimization and alt-right movements . McKelvey actively participates in policy discussions with institutions like the Canadian Radio-Television and Telecommunications Commission (CRTC) , focusing on issues like network-level blocking and internet governance . Scientific Awards and Grants: 2019 Gertrude J. Robinson Book Award for Internet Daemons Multiple SSHRC and FRQSC grants for AI and digital media research Collaborator in major initiatives like Hexagram (2020-2027) McKelvey frequently serves as a media commentator and policy expert, with appearances in CBC , The Guardian , and Wired Magazine . He is a founding member of the Canadian Disinformation Network and contributes to public debates on AI ethics and digital rights.
Dr. Maria Alejandra Pinero de Plaza is a Research Fellow at Flinders University's College of Nursing and Health Sciences and a member of the Caring Futures Institute . Her work bridges digital health , artificial intelligence , and implementation science to advance person-centred care for marginalized populations. Education : PhD in Health Promotion, Behavioural Science, and Marketing Science (Deakin University, 2013–2017) Master of Marketing Science (University of South Australia/Deakin University, 2010–2013) Postgraduate training in Social Anthropology (Venezuelan Institute for Scientific Research, 2004–2006) Licentiate in Social Communication (Universidad Católica Andrés Bello, 1993–1998) Research Interests focus on complex adaptive health systems , human-centred AI , and equity in healthcare . She develops evaluation frameworks like PROLIFERATE and PROLIFERATE_AI to measure technology adoption in clinical settings. Recent Articles examine AI in cardiac care, telehealth for homebound individuals, and care models for First Nations communities, reflecting her commitment to health inclusion and technological ethics . Scientific Awards : Healthcare Innovator Award 2024 CSIRO ON Prime Innovation Reward 2024 GEM Staff Recognition Award 2024 Vice-President & Executive Dean’s Awards (2021, 2022) Top Cited Article Recognition in Nursing Philosophy 2023 Grants include NHMRC funding for RAPIDx AI ($1.2M) and Safe@Home ($1.1M), with a focus on frailty , cardiac rehabilitation , and First Nations health .
Lisa Graham is a researcher at Northumbria University's Department of Sport Exercise and Rehabilitation , focusing on neuroscience and neurorehabilitation. Her work bridges biomedical engineering with clinical applications in movement disorders. Research Areas: Parkinson's Disease, Gait Analysis, Eye Movement, Wearable Technology, Neurological Biomarkers Collaborators: Stuart, Morris, Godfrey, Vitório, Walker Her recent publications highlight digital biomarkers for neurological conditions and wearable sensor barriers . She contributes to neurorehabilitation through clinical trials and systematic reviews. Notable trends include eye-tracking innovations and personalized gait interventions using blazepose technology. She co-authored works on cognitive-motor interactions in Parkinson's, with implications for fall prevention and freezing of gait.
Carsten Griwodz is a Professor in the Department of Informatics (IFI) at the University of Oslo, specializing in digital infrastructure and security. He leads the Distributed Infrastructure and Security (DIS) research group and contributes to several specialized labs including the Sustainable Immersive Networking Lab (SINLAB), Imagine Beyond 5G Blockchain Lab, and the AliceVision Association. Professor at Department of Informatics, University of Oslo Section leader for DIS: Distributed Infrastructure and Security Group member in Networks and Distributed Systems (ND) Active in sustainable immersive networking and blockchain labs Co-founder of AliceVision open-source photogrammetric framework His research focuses on network performance, edge computing, and immersive technologies. He has pioneered work in cloud gaming QoE, real-time 3D reconstruction, and low-latency systems. Current projects explore redirected walking in VR, GPU programming for tracking, and sustainable networking solutions. Recent publications (2021-2024) demonstrate his expertise in network delay analysis, point cloud compression, virtual reality environments, and GPU-accelerated systems. His work bridges computer science fundamentals with cutting-edge applications in multimedia, security, and health informatics. He supervises numerous master's theses covering diverse topics from wireless streaming challenges to medical imaging advancements, consistently mentoring on topics related to network optimization, immersive technologies, and GPU computing. Supervised 40+ master's theses (2004-2024) Thesis topics span network performance, GPU programming, VR systems, and multimedia processing Active in both theoretical and applied research domains Mentoring interests include HCI, distributed systems, and real-time processing Contributes to education through research-led supervision As a permanent faculty member with extensive publication records and active research groups, Griwodz maintains significant influence in academic circles through both his technical contributions and educational mentorship.
Jonathan W. Y. Gray is a Reader in Critical Infrastructure Studies at the Department of Digital Humanities , King's College London . He serves as Director of the Centre for Digital Culture and co-founded the Public Data Lab . Gray is also a Research Associate at the Digital Methods Initiative (University of Amsterdam) and médialab (Sciences Po, Paris). His research focuses on the role of digital data, methods, and infrastructures in shaping collective life , with projects spanning Humanities-based digital methods for environmental issues Critical technical practices in digital research Digital mobilization of East and Southeast Asian (ESEA) communities Public data cultures and open access politics Gray’s recent publications explore topics such as algorithmic misinformation , datafied ecological politics , and critical data infrastructures . He co-edited open-access books on scholarly communication and data journalism, including the Data Journalism Handbook . Scientific awards include Fellow of the Higher Education Academy He supervises PhD projects on AI ethics , open data in China , and social media in higher education . Gray also leads interdisciplinary initiatives like SUPERB: Upscaling Forest Restoration and KingsCAT , a social media research toolkit.
Richard V. McCarthy is a Professor of Business Analytics and Information Systems and Associate Dean for the School of Business at Quinnipiac University. His work bridges academia and industry through predictive analytics, data management, and virtual team pedagogy. BS, Central Connecticut State University MBA, Western New England College DBA, Nova Southeastern University Dr. McCarthy's research focuses on healthcare analytics, financial fraud detection, and data science pedagogy. He applies machine learning to prevent post-surgical falls, combat money laundering, and enhance educational strategies. His publications emphasize predictive modeling techniques, including decision trees, neural networks, and regression analysis, across healthcare, finance, and information systems domains. Computer Educator of the Year, International Organization for Computer Information Systems (2019)
Martin Giese is affiliated with the University of Oslo (Department of Informatics) and the University Clinic Tübingen (Department of Cognitive Neurology). He is a researcher with a focus on semantic technologies, ontology-based data access, and visual query systems. Research Themes : Semantic Web, Ontology Engineering, Knowledge Graphs, Geological Informatics, Probabilistic Logic, Automated Reasoning Key Collaborations : Siemens, Statoil, Norwegian Petroleum Directorate, and various European research institutions Technical Contributions : Developed visual query systems (OptiqueVQS), ontology-driven geological modeling (GeoFault), and semantic data integration frameworks for industrial applications. His work spans both theoretical logic and practical implementations in big data environments. Publications : Recent articles focus on fault ontologies, process representation, and semantic embeddings. Earlier work includes foundational research in automated theorem proving and UML formalization.
Ahmet Soylu is a researcher at Oslo Metropolitan University , Norway, with a focus on Semantic Web , Knowledge Graphs , and Machine Learning applications in Cloud Computing and Smart Manufacturing . His work bridges semantic technologies with data-driven solutions for industrial contexts, particularly in collaboration with Bosch . Key research themes: Knowledge Graph Embeddings, Cloud Cost Optimization, Industrial Data Analytics Collaborations: Dumitru Roman, Evgeny Kharlamov, Radu Prodan Recent publications (2024–2025) explore hyperbolic knowledge graph embeddings, sustainable LLM inference, and cloud storage optimization. These works integrate semantic modeling with ML for edge-cloud systems and industrial data extrapolation. His methodology emphasizes graph-based approaches for cloud cost modeling, microservice scheduling, and AI innovation discovery in open-source repositories. Applications include welding quality monitoring, maritime supply chain optimization, and semantic ML pipelines.
Vinayak R. Borkar is a researcher and software engineer affiliated with the University of California, Irvine, where he completed his PhD in 2016. His work focuses on big data platforms, database systems, and scalable query processing frameworks. PhD in Big Data Processing (UC Irvine, 2016) Contributions to Apache AsterixDB, Hyracks, and Pregelix Industry experience at BEA Systems (2000s) Research interests include database systems , big data management , XQuery optimization , and dataflow engines . His publications analyze scalable similarity queries, memory management, and declarative approaches to machine learning. Recent articles explore Apache AsterixDB , dataflow compilation , and graph analytics . Collaborators include Michael J. Carey and Alexander Behm.
