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James StewartView profile

Professor

• Computer-assisted surgery
• Image processing
• Computer graphics
• +3 more

James Stewart is a Professor at Queen's University's School of Computing. His research focuses on biomedical computing and surgical navigation systems. Education: Ph.D. in Computer Science from Cornell University (1992) Location: Office Goodwin 732 Contact: Phone 613 533-3156 Research Interests Professor Stewart's work bridges computer graphics, image processing, and medical applications. Key areas include: Computer-assisted surgical navigation 3D medical visualization Geospatial data representation Robust geometric computation Human-computer interaction in clinical settings Medical imaging uncertainty analysis Scientific Awards Best Poster Award (2013) for 'Image-guided Osteochondral Autologous Autografting of the Ankle' Publications His publications span multiple domains including: Computer graphics algorithms Medical imaging techniques Geospatial visualization Biomedical engineering applications Surgical navigation systems Robust geometric computation

• Cardiac Imaging
• Magnetic Resonance Imaging
• Computed Tomography
• +6 more

Ronald M Peshock is a Professor of Radiology and Internal Medicine at the University of Texas Southwestern Medical Center (UTSW), with a career spanning over four decades since completing medical school at UT Southwestern in 1976. His academic journey includes Internal Medicine training at Parkland Health & Hospital System (internship 1977, residency 1979) followed by a Cardiology fellowship (1982). Dr. Peshock's research focuses on cardiac imaging, particularly using MRI and CT technologies to assess cardiovascular risk and disease. His work heavily involves the Dallas Heart Study, examining left ventricular hypertrophy, atherosclerosis, and cardiovascular risk factors across diverse populations. In recent years, he has become a prominent researcher in artificial intelligence applications for radiology, with numerous publications on AI implementation in clinical workflows, diagnostic accuracy improvement, and integration of AI into radiology training programs. His publication record shows consistent productivity from 1979 through 2025, with 218 total publications according to available records. Recent work demonstrates particular expertise in cardiac CT, pulmonary embolism imaging, and developing quantitative imaging biomarkers for cardiovascular disease. His Scopus profile indicates an h-index of 67 with 14,914 citations, reflecting significant scholarly impact in his fields. Dr. Peshock maintains active clinical and research affiliations with Parkland Health & Hospital System and serves as a key researcher in the Dallas Heart Study. His work examining ethnic differences in cardiovascular disease, left ventricular hypertrophy patterns, and aortic stiffness has contributed significantly to cardiovascular imaging literature.

• Human-Computer Interaction (HCI)
• Virtual Reality (VR)
• Augmented Reality (AR)
• +7 more

Dr. George Fitzmaurice is a Research Fellow at Autodesk, leading the Human Computer Interaction and Visualization Research group. With over 120 publications and 95 patents, his work spans 25 years of innovation in interactive systems, focusing on technology-assisted learning , 3D visualization , and novel input techniques . His notable contributions include the Maya 1.0 UI and SketchBook Pro design, as well as pioneering Graspable UIs and Spatially-Aware Displays . Education : MIT (B.Sc. Math/CS), Brown (M.Sc. CS), Toronto (Ph.D. CS) His research explores immersive visualization and generative AI applications in design workflows, with recent work focusing on VR/AR tools like TimeTunnel for motion editing and WhatIF for AI-assisted narrative design. Current projects examine the intersection of large language models , 3D design systems , and collaborative environments . Key article themes include: Generative AI integration (3DALL-E, WorldSmith) Immersive motion analysis (AvatAR, VideoPoseVR) Creative workflow optimization (MoodCubes, Immersive Sampling) Privacy-aware VR systems (Vice VRsa) Scientific Recognition: 2019 - Inducted into ACM CHI Academy 2024 - Awarded ACM Fellow for computing contributions He has developed foundational interaction techniques like ViewCube™ and SteeringWheels™ , and his work continues to shape modern 3D UI paradigms and spatial computing approaches through projects like DreamSketch and Tesseract.

• Chiral Recognition
• Enantiomeric Separations
• Ionic Liquids
• +5 more

Daniel W Armstrong is a Professor at the University of Texas at Arlington in the Department of Chemistry and Biochemistry. With over 35 years of experience, he is a pioneering figure in chiral recognition, enantiomeric separations, and the biological relevance of D-amino acids. His work has led to over 740 publications, 35 patents, and 560 invited seminars worldwide. Developed first chiral recognition mechanism by cyclodextrins First to use macrocyclic antibiotics as chiral selectors Synthesized most new ionic liquids (ILs) globally Created ultra-fast separation techniques now standard in analytical chemistry Contributed to FDA 1992 guidelines on chiral drug separation His research focuses on chiral separations, ionic liquids, and the role of D-amino acids in biological systems. He has commercialized over 30 HPLC and GC columns, transforming analytical chemistry and pharmaceutical analysis. Recent publications demonstrate continued innovation in chiral chromatography, biomarker analysis, and AI-driven separation optimization. His grants include industry collaborations with Merck, Alcon, and Sigma-Aldrich, emphasizing practical applications of his work. Scientific honors include multiple lifetime achievement awards, fellowships in the Royal Society of Chemistry and American Chemical Society, the Chirality Medal, and induction into the National Academy of Inventors. He has mentored over 100 PhD students, many from first-generation college backgrounds.

Andreas RauscheckerView profile

Assistant Professor

• Artificial Intelligence
• Medical Imaging
• Neuroradiology
• +5 more

Dr. Andreas Rauschecker is a neuroradiologist at the University of California San Francisco (UCSF), specializing in advanced imaging technologies (CT, MRI) for diagnosing nervous system disorders in adults and children. He employs AI and image-processing techniques to enhance diagnostic accuracy and collaborates with multidisciplinary teams to improve patient outcomes. Fellowship in Neuroradiology, University of California San Francisco (2020) MD PhD in Neuroscience, Stanford University (2013) MSc in Neuroscience, Oxford University (2005) BS in Biology & Psychology, Georgetown University (2004) His research focuses on applying artificial intelligence to neuroimaging, particularly for conditions like multiple sclerosis, brain tumors, and developmental disorders. He investigates how AI can standardize myelination assessments, detect lesions, and reduce reliance on contrast agents in MRI. Recent publications highlight his work on automated lesion segmentation, transfer learning for MRI analysis, and large language models in radiology. Collaborative efforts include multi-institutional datasets for meningioma and glioma segmentation, emphasizing reproducibility and open science. UCSF Chen Scholar (2024-2026) UCSF Weill Award for Clinician-Scientists (2023) ASNR/ASfNR MIT-E Scholarship (2019) NVIDIA GPU Seed Grant (2018) RSNA Roentgen Fellow Research Award (2019) Rauschecker mentors trainees and collaborates on grants related to AI-driven radiology tools. His work bridges clinical practice and computational innovation, aiming to integrate cutting-edge technologies into standard neuroradiology workflows.

Virpi RotoView profile

Senior Lecturer

• Experience Design
• Human-Computer Interaction
• B2B Design
• +9 more

Virpi Roto is a Senior Lecturer at Aalto University's Department of Design (School of Arts, Design and Architecture). She specializes in Experience Design for business-to-business industries, focusing on transforming technology companies into experience providers through co-design and service design methodologies. Key research domains: Human-AI interaction, sustainable futures, and workplace experience design Collaboration hubs: Leads the Encore research group Global influence: Top-cited academic in UX research Her work explores the intersections between User Experience , Customer Experience , and Employee Experience , with a particular emphasis on automation maturity and sociomaterial approaches to transparency in remote teams. Recent publications highlight trends in Human-AI team dynamics and experience-driven industrial systems . She actively bridges Design Fiction with ethical awareness in co-design workshops and develops frameworks for measuring long-term UX. Virpi collaborates with researchers across Finland, Sweden, and international institutions, frequently co-authoring with experts like Philippe Palanque, Matthias Baldauf, and Wendy Ju.

• Ageing
• Smart Cities
• Digital Health
• +10 more

David Prendergast is a Professor in Science, Technology & Society at Maynooth University's Faculty of Social Sciences, where he also serves as Head of the Departments of Anthropology and International Development. With a PhD in Anthropology from the University of Cambridge (2002), his career spans academic roles at Maynooth and industry leadership at Intel, focusing on technology design for aging populations. Research interests: Ageing, Smart Cities, Digital Health, Visual Ethnography, East Asia, Human-Centred Design Key projects: Global Ageing Project, Urban Living Labs in London/Dublin/San Jose, Smart Stadium with Croke Park, Autonomous Vehicles for Older Adults (SFI-funded) His work bridges anthropology with digital innovation , particularly in East Asia contexts. Recent publications explore IoT applications in age-friendly cities , robotics in Japanese elder care , and visual ethnography for aging-in-place solutions. Scientific recognition includes: CHOICE Outstanding Academic Title (2016) Intel Involved Global Hero Award Fortune 500 Hero designation Intel Labs Gordon E. Moore Award As advisor to PhD graduates like Rebekah Maguire (2016) and Ciaran Walsh (2020), he leads Living Lab initiatives on air pollution monitoring and flood management systems . His Circuits of Care documentary (2021) examines human-robot interactions in Japan's aging society .

Fajar Juang EkaputraView profile

Academic

• Semantic Web
• Knowledge Graphs
• Neurosymbolic AI
• +4 more

Fajar Juang Ekaputra is a Tenure Track Assistant Professor at the Institute of Data, Process, and Knowledge Management (DPKM), WU Vienna and a part-time Postdoctoral Researcher at the Data Science research unit, TU Wien . With a focus on Semantic Web , Knowledge Graphs , and their integration with Machine Learning in Neurosymbolic AI systems, his work spans domains like Cyber-Physical Systems and Materials Engineering . Education: Dr.techn. (2018), TU Wien M.T. (2010) and S.T. (2008), Institute Teknologi Bandung (ITB) Research Interests center on hybrid AI systems combining Semantic Web and Machine Learning , with applications in Cyber-Physical Systems (e.g., smart grids, smart buildings), data privacy in smart cities, and materials engineering . His 102+ publications include frameworks like SWeMLS-KG and SHACL4Protege . Recent Articles (2024) address explainable AI in cyber-physical systems, privacy trust in data infrastructures, and neurosymbolic frameworks . Earlier works (2023–2022) explore ontology-based data management , auditable AI , and hybrid system architectures . Scientific Awards: Best Paper Awards (ICoDSE 2023, ICoDSE 2016) Best Poster Nomination (SEMANTiCS 2019) PhD Scholarship (Austria’s Agency for Education and Internationalisation, 2012) Advising includes supervising PhD students (e.g., Majlinda Llugiqi, Katrin Schreiberhuber) and master’s theses on topics like knowledge graph characteristics and data quality assessment . He leads projects such as FAIR-AI (FFG-funded, 2024–2026) and SENSE (Horizon Europe, 2023–2025).

• Health Informatics
• Digital Transformation
• Open Innovation
• +4 more

Teo Hock Hai is Provost's Chair Professor of Information Systems at the National University of Singapore's School of Computing, serving as Director for Humanities & Social Sciences Research in the NUS Office of the Deputy President. He previously headed the Department of Information Systems (2008-2015) and served as Vice-Dean for Corporate Communications. He holds PhD, MSc, and BSc degrees in Computer and Information Sciences from NUS. His research integrates Health Informatics , Digital Transformation , and Open Innovation , with current projects including multilingual dementia detection tools, AI-powered smoking cessation platforms, diabetes management apps, and crew fatigue prediction systems. His work emphasizes the design of IT artifacts to improve health outcomes, decision-making, and educational systems. His publications focus on AI applications in healthcare decision-making, behavioral responses to environmental data, digital platform architectures, and gamification strategies. Recent work examines AI's role in diagnostic workflows, pollution impact on exercise behavior, and emotion-driven information diffusion during health crises. Awards include the Information Management Research Award MIS Quarterly Reviewer of the Year (2004) Multiple best paper awards at international conferences He leads projects funded by national agencies and industry partners including Singapore Airlines, focusing on healthcare AI and digital resilience. He teaches doctoral courses on contemporary IS theories and mentors graduate researchers in health informatics and digital innovation.

Ayesha AliView profile

Professor

• Graphical Markov models
• Pollination networks
• Multivariate statistics
• +7 more

Ayesha Ali is a Professor of Statistics and Director of the Master of Data Science program at the University of Guelph. She holds a PhD in Statistics from the University of Washington (2002) and has expertise in statistical methods for complex high-dimensional systems, including ecological networks, causal inference, and bioinformatics. Her research integrates graphical Markov models, machine learning, and statistical computing to address challenges in plant-pollinator networks, livestock genetics, and disease risk modeling. Education: B.Sc. Honours in Statistics and Actuarial Science, University of Western Ontario (1996) M.Sc. in Statistics, University of Toronto (1998) Ph.D. in Statistics, University of Washington (2002) Research Interests: Graphical Markov models and ecological networks Causal inference and longitudinal data analysis Machine learning and high-dimensional predictive modeling Statistical methods for livestock genetics and animal health Computational statistics and bioinformatics Articles Trends: Her recent work spans interdisciplinary applications, including veterinary oncology biomarker discovery, remote sensing for agricultural suitability, and pipeline development for cross-species transcriptomics. She emphasizes graphical structure exploitation in regression and predictive modeling, with contributions to both theoretical and applied statistical methodologies. Awards: Canadian Journal of Statistics Award (2020) for groundbreaking work on doubly sparse regression NSERC Discovery Grant (2018) NSERC Collaborative Research and Development Grant (2015) Advising & Grants: She has supervised numerous graduate and undergraduate students on projects ranging from plant-pollinator network analysis to bioinformatics. Her grants include NSERC-funded research on milk fatty acid genetics and statistical methods for clustered data. Labs/Teams: Involved in the Bioinformatics program at the University of Guelph, contributing to interdisciplinary research collaborations in ecology and animal science.

• Databases
• Data Management
• Provenance Analysis
• +6 more

Val Tannen is a Professor at the University of Pennsylvania, specializing in database systems, provenance analysis, and programming languages. His research focuses on data management, query languages, and systems like DBSP and ORCHESTRA. Collaborations include work with co-authors such as Zachary Ives, Susan Davidson, and Todd Green. Key research interests include provenance for databases, incremental view maintenance, and data integration. His work bridges theoretical foundations and practical applications in systems like DBSP for stream processing and ORCHESTRA for collaborative data sharing. Publications span provenance frameworks, query optimization, and distributed systems. While no awards are explicitly listed, his contributions to database theory and systems are widely recognized.

Anna RogersView profile

Associate Professor

• Natural Language Processing (NLP)
• Large Language Models (LLMs)
• Model Interpretability
• +4 more

Anna Rogers is a tenured Associate Professor at the IT University of Copenhagen , where she leads research in the Data Science Section . Her work bridges NLP , large language models (LLMs) , and sociotechnical impacts of AI , with a focus on interpretability, robustness, and ethical frameworks. She serves as co-editor-in-chief of ACL Rolling Review and is a Villum Young Investigator and ELLIS fellow . Education: PhD in Computational Linguistics (University of Tokyo), Postdocs in Machine Learning for NLP (University of Massachusetts, Lowell) and Social Data Science (University of Copenhagen) Her research explores how LLMs can be designed for transparency and fairness, with recent grants like the Villum Synergy and Inge Lehmann supporting interdisciplinary collaborations. She organizes workshops (e.g., Dagstuhl seminar 24052) and co-leads projects like CAISA (National Centre for Artificial Intelligence in Society). Key themes include: Interpretability in NLP Robustness against synthetic content Data governance and ethical use Peer review systems and academic publishing Her lab has hosted researchers such as Max Müller-Eberstein (funded by DFF) and is actively recruiting for projects on generalization benchmarks and data attribution. She emphasizes collaboration across academia, industry, and policy, shaping Denmark's data science future through roles like the Danish Data Science Academy committee. Recent articles highlight trends in corpus analysis , temporal annotation , and LLM governance .

• Visual Perception
• Color Vision
• Sensorimotor Integration
• +4 more

Karl R. Gegenfurtner is a Professor of General Psychology at the Department of Psychology, Justus Liebig University Giessen. His research focuses on information processing in the visual system, particularly the interplay between low-level sensory processes, high-level visual cognition, and sensorimotor integration. He investigates how complex scenes are perceived, represented in the brain, and used to drive motor systems, with a specialization in color perception, material property recognition, and eye movement dynamics. Ph.D. in Experimental Psychology, New York University (1990) Diploma in Psychology, University of Regensburg (1986) Habilitation in Medical Psychology and Behavioral Neurobiology, University of Tübingen (1998) His work bridges visual neuroscience with computational modeling, examining color categorization in neural networks, cortical mechanisms of color vision, and dynamic recalibration of visual perception during eye movements. Recent projects include Color 3.0: An object-oriented approach to color (ERC Advanced Grant) and Dynamics in Vision and Touch (Marie Curie Actions). Publications highlight advancements in understanding saccadic suppression, predictive eye movements, and chromatic adaptation timelines. Scientific awards include the Wilhelm Wundt Medal (2016), Rank Prize Funds Lecture (2014), and ERC Advanced Grant (2020–2025). He has served on editorial boards of Journal of Vision , Vision Research , and Perception , and led initiatives like the Neuroscientific Workflow Assistance (NOWA) project. Collaborations span institutions in Germany, the U.S., Australia, and the U.K., with a focus on perception-action loops and neural mechanisms underlying visual stability.

Georg RehmView profile

Professor

• Natural Language Processing
• Computational Linguistics
• Artificial Intelligence
• +7 more

Georg Rehm is an Honorary Professor for Computational Linguistics and Language Technology at Humboldt University Berlin and a Principal Researcher at the German Research Center for Artificial Intelligence (DFKI) in Berlin, where he serves as Deputy Director of the DFKI Lab Berlin. He is also the Head of the German-Austrian Chapter of the World Wide Web Consortium (W3C) based at DFKI Berlin. Rehm has over 300 scientific publications and extensive experience in leading major research projects in computational linguistics and language technology. His research focuses on Natural Language Processing, Computational Linguistics, and Artificial Intelligence, with specific interests in multilingual language technologies, semantic web, digital humanities, and language data spaces. He has led numerous significant projects including European Language Grid, OpenGPT-X, and NFDI4DataScience. Rehm is particularly active in initiatives promoting digital language equality in Europe by 2030. Rehm's recent work demonstrates a strong focus on large language models, scholarly document processing, scientific knowledge representation, and climate-related fact-checking systems. His publications span across multiple high-impact venues including ACL, ESWC, and LREC, with a notable emphasis on practical applications of language technology in real-world scenarios. DFKI Research Fellow (2018) As an active member of the academic community, Rehm regularly serves as an expert for the European Parliament, reviews EU projects, and organizes numerous scientific conferences and workshops. His leadership extends to multiple European initiatives aimed at advancing language technology infrastructure and promoting digital language equality across Europe.

• Classics
• Ancient History
• Papyrology
• +5 more

Mark Depauw is a Professor at the Faculty of Arts , KU Leuven. He leads the Research Group Antiquity, Leuven and is deeply involved in digital humanities initiatives, particularly through the Trismegistos project and its extensions like Trismegistos+ and STUDIUM.AI . His work bridges classical studies with computational methods. Research Focus: Quantitative analysis of classical text reception in early modern Europe Network analysis of ancient literary and social connections Development of digital infrastructures (GLAUx Treebank, Trismegistos) for ancient textual studies Application of transformer models and named entity recognition to Greek and Latin texts Membership & Collaborations: Member of the Faculty Council of Arts Part of KU Leuven Institute for Digital Society (DigiSoc) Core contributor to LECTIO for textual transmission studies Collaborator on international projects like CLARIAH-VL+ and NIKAW Teaching: He contributes to courses in historical data management, Greek papyrology, and digital research methods. His pedagogical approach integrates computational tools with classical scholarship.