Vajira Thambawita is a researcher at the University of Oslo's Department of Informatics, specializing in medical image analysis and AI-driven healthcare solutions. With over 90 publications since 2019, their work spans gastrointestinal endoscopy, reproductive medicine technology, and multimedia systems for clinical applications. Research focuses on medical image segmentation (polyp detection, sperm tracking), anomaly detection in time-series data, and multimodal analysis for clinical decision support. Key projects include the Medico Multimedia Task at MediaEval (sperm tracking), VISEM-Tracking dataset, and ImageCLEFmedical challenges for GI tract analysis. Their work bridges computer vision with clinical practice through collaborations with Oslo University Hospital and Simula Research Laboratory. Recent publications demonstrate strong trends in generative AI for medical data augmentation (SinGAN-Seg, PolypConnect), explainable AI for clinical validation , and multimodal integration (SoccerNet-Echoes). The research consistently targets real-world clinical problems with emphasis on transparency and robust evaluation. Thambawita actively contributes to major benchmark challenges including ImageCLEF, Medico, and Medical AI competitions, serving as organizer and participant in advancing evaluation standards for medical AI systems.
Dr. Patrick Gebhard is a researcher at the Cognitive Assistance Systems department of the German Research Center for Artificial Intelligence (DFKI), focusing on affective computing, human-computer interaction, and psychological modeling. His work bridges computational linguistics, mental health, and wearable technologies. Key projects: UBIDENZ (digital empathetic therapy assistance), MITHOS (mixed-reality teacher training), SocialWear (interactive smart fashion), MindBot (mental health in Industry 4.0), EmmA (emotional coaching avatars). Recent research explores emotion regulation strategies, psychodynamic conflict recognition via LLMs, and multimodal sign language corpora development. Collaborates with institutions like Saarland University, contributing to conferences such as CLPsych, LREC-COLING, and ACII. Contact: Patrick.Gebhard@dfki.de
Stephanie C. Hicks is an Associate Professor in the Department of Biomedical Engineering at the Whiting School of Engineering and in the Department of Biostatistics at Johns Hopkins University. She is also affiliated with multiple research centers, including the Malone Center for Engineering in Healthcare, the Center for Imaging Science, the Center for Computational Biology, the Johns Hopkins Data Science Lab, and serves as a preceptor in the Department of Genetic Medicine and the Department of Biochemistry and Molecular Biology. B.S. in Mathematics from Louisiana State University (LSU) M.A. and Ph.D. in Statistics from Rice University, advised by Marek Kimmel and Sharon Plon Postdoctoral training with Rafael Irizarry at the Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health Dr. Hicks is an applied statistician whose research lies at the intersection of genomics and biomedical data science. Her work focuses on developing computational methods using statistics and machine learning to address challenges in single-cell genomics, epigenomics, and spatial transcriptomics. She implements these methods as open-source software, guided by a 'problem-forward' philosophy that emphasizes real-world applicability. Her research has led to contributions in spatially aware quality control (e.g., SpotSweeper), self-supervised learning for spatial domain detection, and benchmarking of feature selection methods. Her recent publications reflect a strong trend in integrating machine learning—especially deep learning and transformers—into genomic data analysis. She has received numerous honors, including the COPSS Emerging Leader Award, the Teaching in the Health Sciences Young Investigator Award, the Myrto Lefkopoulou Distinguished Lectureship (2023), and election as a Fellow of the American Statistical Association. These awards recognize her leadership, contributions to statistical science, and commitment to education and reproducibility. Dr. Hicks is actively involved in mentoring and advising, with students such as Kinnary Shah, Jianing Yao, Michael Totty, and Boyue Guo contributing to her research. She also contributes to the academic community through editorial roles, including Associate Editor for Reproducibility at the Journal of the American Statistical Association and membership on the editorial board of Genome Biology . She co-hosts the popular podcast The Corresponding Author and is a co-founder of R-Ladies Baltimore, promoting diversity and inclusion in data science. Her work is supported by her affiliations with interdisciplinary research hubs at Johns Hopkins, where she collaborates across engineering, medicine, and data science. She is also deeply engaged in science communication, education, and advocacy, notably through her public commentary on the importance of federal research funding and participation in events like Stand Up for Science.
Jean Nitzke is an Associate Professor at the Department of Foreign Languages and Translation , University of Agder, Norway. She specializes in post-editing machine translation , cognitive translation studies , and translation technologies , with a focus on specialized translation (technical, medical, business, legal domains) and AI integration in translation workflows. Current teaching: Specialised translation , Translation technologies , and Language technology & generative AI Research groups: Agder Forum for Translation Studies , Experimental linguistics Her 2025-2024 research explores low-diffusion language translation technologies , industry post-editing practices , and machine translation evaluation for under-researched pairs. Earlier works (2022-2021) analyze cognitive processes in post-editing, intralingual corpora for Easy German, and hybrid translation workflows in education. She collaborates with Silvia Hansen-Schirra , Carmen Canfora , and Katharina Oster , among others. Key 2019 publications include empirical studies on problem-solving activities in post-editing, training digital competencies via blended learning, and risk management in machine translation workflows. Her work bridges academic research and industry applications , emphasizing human-AI collaboration in translation.
Cécile Paris is a researcher at CSIRO , focusing on interdisciplinary applications at the intersection of Artificial Intelligence , Cybersecurity , and Human-AI Collaboration . Her work spans domains such as biomedical informatics, social media analysis, and robotics. Research Interests: Developing collaborative frameworks for human-AI teams Explainable AI in cybersecurity Trust modeling in social networks Fake news detection via temporal and graph-based networks Image captioning with multimodal learning Stance classification across domains Article Trends: Recent publications emphasize adaptive alert prioritization (2025), systematic reviews on cybersecurity challenges (2024), and foundational work in NLP for epidemic intelligence (2018-2020). Key methodologies include graph neural networks, transformer models, and adversarial training.
Élise Degrave is a full-time Professor at the University of Namur's Faculty of Law where she teaches Sources and Principles of Law in the bachelor's program and Internet Governance and E-government in the Master's degree in Information and Communication Technology Law. She serves as co-director of the E-Government Chair at UNamur and leads the e-government research team at the Namur Digital Institute (NADI) and the Center for Research on Information, Law and Society (CRIDS). Her research focuses on digital public law with special emphasis on e-government, privacy protection, digital social inequalities, regulation of artificial intelligence, and transparency of public sector algorithms. She examines how states use personal data, the digital divide, automation of citizens' rights, and algorithmic governance in public administration. Degrave holds a PhD in Legal Sciences from the University of Namur (2013) with a thesis on e-government and privacy protection. Her work demonstrates how e-government can respect privacy rights through legal modifications and technical solutions. She has published extensively on digital governance, with recent publications focusing on AI regulation, digital rights, and health data spaces. She actively contributes to public policy as a full member of the Walloon Digital Council and frequently provides expert opinions to parliamentary bodies, the Council of State, and media outlets. Her expertise is regularly sought for training government officials in data governance and privacy protection. Falys Prize (best dissertation in Legal Sciences) - UCL - 2004 Golden Chick and Golden Chicken awards As educational coordinator of the Faculty of Law and member of the UNamur Teaching Council, Degrave is committed to innovative teaching methods. She maintains strong connections with practical applications of digital law through her external roles with the Walloon Digital Council, the Commission for Access to and Reuse of Administrative Documents, and as Editorial Director of the Information Technology Law Review.
Pål Halvorsen is a Professor at the Department of Computer Science within the Faculty of Technology, Art and Design at Oslo Metropolitan University. He works at the intersection of computer science and applied domains, with a particular focus on multimedia systems, distributed computing, and healthcare applications. Specializes in distributed multimedia systems Active in AI-driven forensic psychology applications Conducts research on medical imaging and diagnostics Develops sports analytics datasets and tools Works on communication and distributed systems His research spans several key areas of computer science, particularly focusing on multimedia systems and their applications in healthcare, sports analytics, and forensic psychology. He leads projects involving AI-driven child avatars for investigative interview training, develops datasets for medical and sports applications, and explores innovative approaches to image analysis and time-series data processing. Recent publications demonstrate strong activity in applying computer vision and deep learning to medical diagnostics, particularly in gastrointestinal tract analysis and ophthalmology. His work on sports analytics includes creating comprehensive datasets for ice hockey and soccer, while his forensic psychology research focuses on AI-enhanced interview training for child abuse investigations. Halvorsen collaborates extensively across disciplines, working with researchers in psychology, medicine, and sports science. His projects often involve developing novel tools for data analysis, including approaches to multimodal data handling, visual deep learning verification, and AI-enhanced prompt generation techniques.
Hiten Madhani, MD, PhD, is a Professor at the University of California San Francisco (UCSF) specializing in epigenetics, fungal pathogenesis, and RNA biology. His research spans from yeast genetics to human disease mechanisms, particularly focusing on Cryptococcus neoformans virulence and chromatin regulation. Education: B.S./M.S. (Stanford, 1986), PhD (UCSF, 1993), MD (UCSF, 1995) Postdoctoral Training: Whitehead Institute (1995-1999) His work explores how fungal pathogens interact with the immune system, chromatin fidelity mechanisms, and spliceosome dynamics. Recent publications highlight innovative tools for fungal mutagenesis, deep learning in epigenetic studies, and immune evasion strategies. Scientific accolades include the Leukemia and Lymphoma Society Scholar Award (2017), Burroughs-Wellcome Fund Career Development Awards, and Chan Zuckerberg Biohub Investigator designation (2022). Research funding from NIH spans over 20 projects from 1996-2022. Notable grants: R01GM071801 (Gene Silencing), R01AI100272 (Cryptococcus Resource), R01AI120464 (Epigenetic Virulence Control)
Abbie Olszewski, Ph.D., CCC-SLP, serves as Associate Professor in Literacy Studies within the College of Education and Human Development at the University of Nevada, Reno. With over 25 years of clinical experience as a certified speech-language pathologist, she trains future educators—including speech-language pathologists, special educators, and early childhood specialists—in evidence-based practices for improving children's language and literacy skills, with specialized focus on dyslexia evaluation and intervention. Education: Ph.D. in Disability Disciplines in Special Education and Rehabilitation (specializing in Speech-Language Pathology and Language and Literacy), Utah State University, 2011 M.A. in Speech-Language Pathology, Northern Illinois University, 1998 B.S. in Communicative Disorders, Northern Illinois University, 1996 Research Focus: Dr. Olszewski's work centers on three interconnected domains: (1) Developing AI-driven screeners for early identification of dyslexia/dysgraphia through children's writing analysis, funded by NSF/IES through the National AI Institute for Exceptional Education; (2) Pioneering clinical interventions including her seminal book How to Teach Voice and Communication Skills to Transgender Women ; (3) Advancing scholarship of teaching and learning to optimize educator preparation. Her research bridges clinical practice, technology innovation, and interdisciplinary collaboration. Publication Trends: Recent publications (2023-2025) demonstrate accelerating integration of artificial intelligence in speech-language pathology, particularly for dyslexia screening and culturally responsive interventions. Concurrent threads examine interdisciplinary training models and transgender communication services, reflecting her commitment to technology-enhanced, inclusive educational practices that address systemic service gaps. Scientific Awards: No scientific awards reported in available documentation. Grants and Leadership: Principal investigator on multiple federal grants including NSF/IES funding for AI-driven exceptional education solutions and OSEP funding for interdisciplinary training of early childhood special educators and speech-language pathology students. Her work emphasizes team science to develop scalable interventions addressing speech-language pathologist shortages. Collaborative Frameworks: Actively engaged with the National Artificial Intelligence Institute for Exceptional Education, leading cross-disciplinary collaborations between speech-language pathologists, educators, computer scientists, and AI researchers to transform service delivery models for children with communication disorders.
Håvar Brendryen is an Associate Professor in Clinical Psychology at the Department of Psychology, University of Oslo. He received his Cand. Polit. in psychology from NTNU in 2001 with specialization in cognitive psychology and human-machine interaction, and completed his doctorate at the University of Oslo in 2009 on Automated cessation interventions delivered via the internet and mobile phone. He has been employed at SERAF since 2010 and has taught and supervised in health psychology. His main research interests include eHealth , health psychology , behavior change , addiction , smoking cessation , and early intervention for alcohol . He is particularly interested in internet- and telephone-based behavior change programs, with a focus on mechanisms of action including relapse prevention, slippage management, and working alliance. His work bridges cognitive psychology with practical clinical applications through digital interventions. Recent publications show a consistent focus on digital alcohol and smoking cessation interventions, with notable work on implementation science, user engagement with eHealth tools, and cross-cultural adaptation of interventions. His research demonstrates a strong trajectory from theoretical foundations in cognitive psychology to practical applications in addiction treatment through digital platforms. He has secured funding from multiple sources including the Research Council of Norway, National Cancer Institute (USA), and SERAF for his projects. Notable projects include the Balance alcohol intervention program and internet-based smoking cessation programs with relapse prevention components. Dr. Brendryen supervises doctoral students, with Marianne Therese Smogeli Holter being his doctoral fellow on the smoking cessation project funded by the Research Council of Norway. He has also collaborated extensively with international researchers on digital health interventions.
Paul D. Mitchell is a Professor of Agricultural and Applied Economics at the University of Wisconsin-Madison. His work spans agricultural policy, crop insurance, and environmental management, with a focus on Wisconsin agribusinesses and farming practices. Over recent years, his research has increasingly integrated educational technologies and embodied cognition, particularly in mathematics and geometry learning. Department: Agricultural and Applied Economics Key Research Areas: Embodied Cognition, Mathematical Reasoning, Augmented Reality in Education His publications highlight the role of gestures, spatial ability, and multimodal interactions in enhancing mathematical understanding. Recent studies explore AR simulations, gesture-based learning, and collaborative knowledge-building. While his formal affiliation remains in agricultural economics, his scholarly output reflects interdisciplinary engagement with education and cognitive science.
Brian Droubay is an Assistant Professor of Social Work in the College of Arts & Sciences at Utah State University , serving the USU Brigham Region which includes campuses in Brigham City, Kaysville, and Tremonton, Utah. His scholarship integrates social work practice with human sexuality, religiosity, and technology use. He investigates how moral values and stigma shape experiences of pornography consumption, sexual identity, and mental health among both sexual minorities and heterosexual populations. Another major strand of his work focuses on educational equity, particularly the intersecting challenges faced by first-generation and single-mother college students. Across 15 peer-reviewed publications (2017–2025) he has employed diverse methodologies—from large-scale machine-learning analyses across 16 countries to in-depth qualitative studies—illuminating predictors of problematic pornography use, the psychological impact of secrecy and shame, and the role of religiosity in censorship debates. His applied research also advances evidence-based interventions for intimate-partner-violence perpetrators and supports the well-being of medical social workers through studies on compassion fatigue and empathy. While the provided material does not list specific awards, grants, or doctoral advisees, the breadth and recency of his output indicate active scholarly engagement and ongoing contributions to social work education and practice.
Benjamin James Knox serves as an Adjunct Associate Professor at the Norwegian University of Science and Technology (NTNU), with his work based at the Gjøvik campus. His research bridges cybersecurity with cognitive science, focusing on human factors in cyber defense operations. He maintains an active research profile with numerous publications through NTNU's institutional repository. Dr. Knox's research interests center on the intersection of human cognition and cybersecurity, with significant contributions in cognitive agility for cyber operators, neuroergonomic approaches to threat identification, and the psychological dimensions of cyber warfare. His work explores how cognitive processes, emotional states, and team dynamics influence cyber situational awareness and decision-making in high-stakes environments. Recent research has expanded into extended reality training environments, individual risk assessment for cybersecurity personnel, and the application of digital twins for critical infrastructure protection. His publication record demonstrates consistent output across multiple high-impact venues including Frontiers in Education, IEEE Access, and Lecture Notes in Computer Science. Dr. Knox frequently collaborates with researchers across European institutions, particularly in Norway, Lithuania, and Germany, indicating strong international research networks. His work with NATO Science and Technology Organization highlights the strategic relevance of his research to defense applications. While specific laboratory affiliations aren't detailed in the available information, his publications suggest involvement with cyber defense simulation environments and neuroergonomic testing facilities. His recent focus on extended reality and digital twin technologies indicates engagement with advanced simulation platforms for cybersecurity training.
Phil Bartie is an Associate Professor in the Department of Computer Science at Heriot-Watt University's School of Mathematical and Computer Sciences in Edinburgh. His research integrates spatial analysis with environmental and social issues, focusing on how geographic information systems can address urban sustainability challenges. Current affiliations include active supervision of PhD students and collaboration with interdisciplinary teams across environmental science and social policy domains. His research interests center on Geographic Information Systems (GIS), spatial data analysis, and environmental informatics, with specific applications in blue space accessibility, urban planning, and energy policy analysis. Work examines how natural environments impact wellbeing, particularly during crises like the COVID-19 pandemic, and investigates public attitudes toward energy transitions using social media analytics and mixed-methods approaches. Key methodologies include geospatial modeling, Twitter activity mapping, and solicited research diaries for longitudinal wellbeing assessment. Recent publications reveal strong trends in spatial analysis of environmental-social intersections, particularly examining UK public discourse on fracking through Twitter geotagging, climate change belief systems influencing energy attitudes, and restorative benefits of inland blue spaces. His work consistently bridges technical GIS capabilities with societal challenges, contributing to UN Sustainable Development Goals related to sustainable cities and climate action. Phil Bartie actively supervises PhD students and contributes to research grants focused on urban environmental systems, though specific grant details aren't publicly enumerated. His REAL corpus dataset (2016) demonstrates expertise in creating multimodal language resources for spatial reference resolution. Research occurs within interdisciplinary teams addressing urban sustainability, with emphasis on translating geospatial analysis into practical urban planning applications and environmental policy recommendations. Current projects examine spatial dimensions of energy transitions and nature-based wellbeing interventions in urban contexts.
Dr. Derek Greene is an Assistant Professor at the School of Computer Science, University College Dublin, and a Funded Investigator at the Insight Centre for Data Analytics and the VistaMilk Research Centre. His research spans machine learning, natural language processing, and network analysis, with a focus on interdisciplinary applications in cultural analytics, smart agriculture, and political science. Dr. Greene has published over 60 research papers at international conferences and journals. His work includes developing methods for natural language processing , network analysis , and deep learning applied to diverse domains such as literary text mining, dairy industry monitoring, and political communication analysis. He leads projects integrating machine learning into cultural analytics, enhancing agricultural practices, and modeling policy agendas. The articles in his Google Scholar profile highlight a trend toward explainable AI , synthetic data generation , and network-based modeling . Key sub-fields include counterfactual explanations , transformer-based frameworks , temporal analysis of historical texts , and interdisciplinary knowledge transfer . His work bridges machine learning with applications in cultural studies , agriculture , and political science . Dr. Greene collaborates with institutions like the Insight Centre for Data Analytics and the VistaMilk Research Centre , integrating academic research with industry and policy needs. His funded investigator roles reflect ongoing support for applied research in data analytics and agricultural technology.
