Caner Özer is a Researcher affiliated with Istanbul Technical University's Department of Artificial Intelligence and Data Engineering and the University of Twente's MIA group. He holds a PhD in Computer Engineering from Istanbul Technical University (2020), an MSc in Telecommunication Engineering (2017-2020), and a BSc in Electronics and Communications Engineering (2013-2017). His research focuses on medical imaging AI, explainable artificial intelligence (XAI), deep learning applications in healthcare, and computer vision techniques for artifact detection in medical imaging. He has conducted visiting research at the University of Twente (2024) and serves on academic committees at Istanbul Technical University. Research interests include developing explainable models for mammogram analysis, enhancing medical image quality assessment via transformers and neural networks, and addressing challenges in cardiovascular MRI segmentation through motion artifact detection. His work bridges deep learning theory with practical clinical applications, emphasizing transparency and accuracy in AI-driven medical diagnostics. Notable contributions include cross-domain artifact correction for cardiac MRI, joint CNN-RNN models for intracranial hemorrhage detection, and XAI methods for chest X-ray analysis. His research has been published in top-tier venues with a focus on medical imaging and deep learning advancements.
Albert J. Sinusas, M.D., is a Professor of Medicine (Cardiovascular Medicine and Radiology & Biomedical Imaging) at Yale University School of Medicine and holds adjunct roles in Biomedical Engineering. He leads the Yale Translational Research Imaging Center (Y-TRIC) and directs Advanced Cardiovascular Imaging at Yale New Haven Hospital. His roles include Chairman of multiple committees (Yale Radioactive Drug Research Committee, Radiation Safety Committee) and Board Member of the Intersocietal Accreditation Commission (IAC) for Nuclear/PET imaging. Dr. Sinusas earned his MD from the University of Vermont and completed training in Internal Medicine at the University of Oklahoma and Cardiology/Nuclear Cardiology at the University of Virginia. His research focuses on cardiovascular imaging innovations, including molecular imaging of myocardial injury, angiogenesis, and peripheral artery disease. His translational work employs multidisciplinary modalities such as PET/CT, SPECT/CT, MRI, and echocardiography. He leads NIH-funded grants and trains researchers through a T32 grant. With over 250 peer-reviewed publications, he co-edited textbooks on cardiovascular molecular imaging and hybrid imaging in cardiovascular medicine. Key research interests include developing novel imaging tracers, AI-enhanced diagnostic tools, and non-invasive assessment of cardiovascular pathophysiology. Notable contributions include advancements in PET-derived myocardial blood flow quantification and SPECT imaging optimization using deep learning. Dr. Sinusas has received prestigious awards like the SNMMI Hermann Blumgart Award (2008) and is frequently recognized in 'Best Doctors in America.' He serves on editorial boards for Journal of Nuclear Medicine , Journal of Nuclear Cardiology , and JACC: Cardiovascular Imaging . His clinical expertise includes ECG, stress testing, and interpretation of SPECT/PET imaging studies. He oversees Y-TRIC’s mission to bridge preclinical and clinical imaging research, fostering collaboration across engineering, radiology, and cardiology.
Ali Gooya is a Senior Lecturer (Associate Professor) in Machine Learning at the School of Computing Science, University of Glasgow, UK. His research focuses on probabilistic deep learning applied to medical imaging, particularly in cardiology and oncology, emphasizing semi/unsupervised methods due to sparse expert annotations. He holds a PhD in medical image analysis from the University of Tokyo (2007) and has held academic positions at the University of Leeds and Sheffield before joining Glasgow in 2022. Affiliations: Senior Lecturer in Machine Learning, University of Glasgow (2022–present) Lecturer in Computing, University of Leeds (2018–2022) Lecturer in Computing, University of Sheffield (2016–2018) Postdoctoral Researcher, University of Pennsylvania (2008–2011) Research Interests: Deep learning for medical imaging, probabilistic modeling, cardiac and cancer imaging, computational anatomy, and marker discovery. Key applications include motion analysis, segmentation, and predictive modeling in healthcare. Key Achievements: Won prestigious fellowships including Allen Touring Institute (2022), JSPS Short-Term (2020), Marie-Curie IIF (2014), and JSPS-PDRA (2008). Pioneered Bayesian deep learning frameworks for cardiac motion assessment and generative models in medical imaging. Grants & Supervision: EPSRC Impact Acceleration Award (PI) EPSRC New Investigator Grant (EP/S012796/1) Actively supervising PhD students in areas like Bayesian deep atlases for cardiac motion analysis. Labs & Teams: Leads research in medical AI within the School of Computing Science, collaborating on projects integrating imaging and patient metadata for clinical decision support.
Giulia Boato is an Associate Professor at the University of Trento’s Department of Information Engineering and Computer Science (DISI). She teaches courses in Probability and Multimedia Data Security. Her expertise spans Cyber Security, Digital Forensics, and Multimedia Analysis, focusing on image and signal processing for data protection, forensics, and anti-forensics. She collaborates internationally with institutions like Tampere University of Technology and Dartmouth College, co-advising PhD students and contributing to European projects like LIVINGKNOWLEDGE and GLOCAL. Education: PhD in Information and Communication Technology (2005), M.Sc. in Mathematics (2002), Scientific Lyceum (1998) with bilingual Italian-German certification. Past roles include Assistant Professor at DISI (2006–2018) and visiting researcher at the University of Vigo (2006) and University of Innsbruck (2018). Research interests include multimedia data protection, image forensics (tampering detection, computer vs. natural data discrimination), and intelligent data management. She leads projects on social media forensics, event-based retrieval, and synthetic media detection. Awards include Best Paper at IEEE WIFS 2012 and Top 10% Paper at MMSP 2012. Professional contributions include roles as co-chair of workshops, Technical Program Committee member for ICIP and ICC, and reviewer for journals like IEEE Transactions on Information Forensics and Security. She has advised PhD theses and contributed to datasets like TrueFace and WILD for synthetic media analysis.
Diego Patiño is an Assistant Professor in the Department of Computer Science and Engineering at the University of Texas at Arlington (UTA), a position he began in September 2024. He earned his Ph.D. in Computer Engineering from the National University of Colombia in 2020, following M.S. and B.S. degrees from the same institution. Prior to joining UTA, he served as a Postdoctoral Fellow at Drexel University and a Postdoctoral Researcher at the GRASP Laboratory, University of Pennsylvania. B.S. in Computer Engineering, National University of Colombia, 2010 M.S. in Computer Engineering, National University of Colombia, 2012 Ph.D. in Computer Engineering, National University of Colombia, 2020 Dr. Patiño's research centers on geometric computer vision and machine learning, with applications in robotics and 3D vision. His primary interests include 3D reconstruction, graph neural networks, symmetry detection, physics-informed machine learning, and reinforcement learning. He develops algorithms that integrate geometric priors and physical constraints into deep learning models to improve robustness and generalization in real-world robotic systems. His recent publications demonstrate a strong trend in leveraging implicit neural representations for 3D shape reconstruction, applying graph neural networks to swarm robotics, and enhancing computer vision tasks with self-supervised and physics-informed learning. Work spans high-impact venues such as IEEE RA-L, ICRA, ICPR, and MICCAI, showing a consistent focus on geometric reasoning, robotic perception, and medical imaging applications. His scientific contributions have been recognized with awards from the UTA Division of Student Affairs for exceptional dedication and positive impact (2024 and 2025). He is actively involved in securing research funding, with multiple grants under review from NSF, Air Force SBIR, and industry partners like Sony. Exceptional dedication and positive impact recognition, UTA Division of Student Affairs (December 9, 2024) Exceptional dedication and positive impact recognition, UTA Division of Student Affairs (April 30, 2025) Dr. Patiño advises and serves on committees for multiple graduate students in computer science and engineering, including doctoral and master’s candidates. He is also leading or co-leading several research grants under review, covering topics such as aerial swarm navigation, neuromorphic sensing, and industrial computer vision. He teaches graduate courses in computer vision and is involved in service roles including PhD admissions and faculty appointments committees. He is affiliated with research initiatives at UTA, including the UTARI Research Institute, where he has presented on geometric modeling and physics-informed learning. His lab focuses on developing next-generation computer vision algorithms for robotics, industrial inspection, and safety-critical systems.
Dr. Anna Bendrat is an Assistant Professor at the Department of English and American Studies, Maria Curie-Skłodowska University, Poland. A scholar in Rhetoric, American Drama, and Cognitive Poetics, she is actively involved in interdisciplinary research, particularly through the Cognitive Studies Team and the International Federation for Theatre Research (IFTR). Her research interests span Rhetoric, Social Communication, Identity Studies, New Media, and Affect Studies. She has led the EU Erasmus+ project MigraMedia (2023–2026) and co-founded the journal New Horizons in English Studies . Her work bridges academic rigor with public engagement, including organizing the Media in America, America in Media conference series. Anna’s recent publications interrogate urban trauma in Pulitzer-winning drama, AI’s role in reconstructing memory, and cognitive texture in multi-perspective narratives. Her scholarly activities are enriched by editorial roles in Res Rhetorica and New Horizons in English Studies , alongside grants for research in New York and Poland. She mentors the UMCS Philology Student Circle, promoting anglophone cultures, and maintains a focus on Polish-American academic collaborations. Her research team explores digital rhetoric, migration narratives, and the intersection of literature with cognitive theory.
Renzo Huber serves as an Associate Professor and Investigator in the Department of Radiology at Harvard University, affiliated with the Mass General Research Institute. He joined the Martinos Center in summer 2025 as Neuroscience Director of the MGB 7T Center, overseeing high-quality functional neuroimaging operations across three human 7T MRI scanners. His research specializes in layer-specific fMRI (layer-fMRI) methodology development, including 3D-EPI sequences, whole-brain layer-fMRI implementation, and functional blood volume mapping using VASO. He focuses on transforming layer-fMRI into a turn-key neuroscience tool while establishing rigorous standards for high-resolution acquisition, reconstruction, and processing in ultra-high-field MRI environments. No scientific awards are documented in available sources. No student advisement or research grant details are provided. Dr. Huber leads the layer-group at the Martinos Center, dedicated to advancing mesoscale vascular imaging and neuroimaging standards for 7T MRI applications.
Hannu Hyyppä is a Research Director and Project Employee at Aalto University's Department of Built Environment, affiliated with the MeMo research group. He leads the Research Institute of Measuring and Modelling for the Built Environment, focusing on advanced laser scanning, 3D modeling, and geoinformatics. His work spans interdisciplinary collaborations across engineering, geography, and arts, with a strong emphasis on applications in cultural heritage preservation, urban planning, and environmental monitoring. Education: Doctoral degree (D.Sc.) in Engineering and Technology, Helsinki University of Technology (2000) Licentiate degree in Engineering and Technology, Helsinki University of Technology (1989) Master's degree in Engineering and Technology, Helsinki University of Technology (1986) Research Interests: Laser scanning technologies, point cloud utilization in forestry and urban mapping, virtual reality for cultural heritage, and sustainable infrastructure modeling. His expertise includes photogrammetry, geographic information systems (GIS), and decision support systems for environmental management. Recent Contributions: Over 550 publications and 30+ active projects, including the Centre of Excellence in Laser Scanning Research (2014-2019) and the Pointcloud project (2015-2021). His work advances applications in autonomous road inspection, 3D cultural reconstructions, and smart city technologies. Awards: Recipient of the 2019 Kansallinen avoimen tieteen palkinto for innovative open science contributions. Grants & Leadership: Principal Investigator for projects like DICA (Digital Cultural Heritage) and ToToRo (Automatic Road Inspection). Active in organizing workshops and international conferences on 3D technologies and laser scanning. Labs/Teams: Oversees the MeMo group and collaborates with national organizations like the Finnish Geospatial Research Institute. Develops tools for real-time 3D mapping and virtual environments.
Tobias Ofner-Graff is a researcher at the Institute of Forest Growth within the Department of Ecosystem Management, Climate and Biodiversity at the University of Natural Resources and Life Sciences, Vienna (BOKU). Based at Peter-Jordan-Straße 82, 1190 Wien, his work focuses on advanced forest monitoring technologies. His research interests include: LiDAR and remote sensing applications in forestry Automated forest inventory systems Forest regeneration quantification Airborne Laser Scanning (ALS) data analysis Sustainable forest harvesting planning Recent project contributions include: Leading lidar-based forest monitoring systems development Developing spatial forest growth models Implementing digital inventory workflows His publications demonstrate expertise in: Quantifying forest resources through 3D point clouds Advanced timber stack measurement techniques ALS data integration for forest modeling Mobile laser scanning applications Forest climate adaptation strategies
Dirk Van Hulle holds the position of Professor of Bibliography and Modern Book History within the University of Oxford's Faculty of English, with significant cross-institutional leadership roles. Chair of the Oxford Centre for Textual Editing and Theory (OCTET) Director of the Centre for Manuscript Genetics at the University of Antwerp Co-director of the Beckett Digital Manuscript Project Editor of the Journal of Beckett Studies Series Editor for Cambridge UP's 'Elements in Beckett Studies' His research centers on Beckett Studies, James Joyce Studies, and textual scholarship methodologies, specializing in genetic criticism to trace literary creation through manuscript evolution. Van Hulle bridges traditional bibliography with digital humanities, examining how modernist authors like Beckett and Joyce transformed drafts into finished works, with particular focus on material textuality and archival preservation. Analysis of his major publications reveals consistent emphasis on digital approaches to manuscript analysis, especially regarding 20th-century literary giants. Works like Modern Manuscripts (2014) and James Joyce's Work in Progress (2016) demonstrate methodological innovation in reconstructing compositional processes through digital archives, highlighting the Beckett Digital Manuscript Project's role in advancing genetic criticism. His scholarly recognition includes: 2019 Prize for a Bibliography, Archive or Digital Project from the Modern Language Association (MLA) Van Hulle directs the Oxford Centre for Textual Editing and Theory (OCTET), which develops interdisciplinary frameworks for textual scholarship, and the University of Antwerp's Centre for Manuscript Genetics, specializing in genetic analysis of literary manuscripts. The Beckett Digital Manuscript Project under his co-direction provides a comprehensive digital archive of Beckett's manuscripts, integrating high-resolution images with transcriptions and scholarly annotations to enable global research access.
Sidonie Christophe is a Senior Researcher (Directrice de Recherche, DR1) at UMR LASTIG, a joint research unit of Université Gustave Eiffel, IGN-ENSG, and EIVP. She serves as co-director of the LASTIG laboratory and leads research in geovisualization, map design, and interactive spatial data exploration. She also holds a part-time advisory role (60%) at the French Ministry of Higher Education and Research in the domain of digital technology, environment, climate, and sustainable urban development. PhD in Geographic Information Sciences Senior Researcher, DR1, MTECT Co-Director, LASTIG Laboratory (since 2021) Former Team Leader, GEOVIS (Geovisualization, Interaction, and Immersion) Advisor, Environment and Urban Climate, French Ministry of Higher Education & Research Her research centers on innovative methods for 2D/3D and nD geospatial data visualization, with a focus on enabling spatio-temporal understanding through visual and non-visual spatial thinking. Her work integrates principles from geographic information science, human-computer interaction, and computer graphics. Key areas include urban climate visualization, tactile and augmented reality for accessibility, expressive cartographic rendering, and cognitive aspects of map design. She investigates how aesthetic and semiotic choices impact map comprehension and utility. The 15 most recent publications reflect a strong trend in interactive and accessible geovisualization, particularly for urban and environmental applications. Topics include neural map style transfer, 3D urban climate analysis, tactile maps for the visually impaired, augmented reality in geography, and visual analytics for crisis and climate data. There is a consistent emphasis on user-centered design, interdisciplinary integration, and the development of tools for decision-making under uncertainty. Scientific Recognition and Service: Invited speaker at major conferences (IEEEVIS, AGILE, ICC, CPGIS) Co-organizer of international workshops (e.g., GeoVIS, ISPRS AR/VR sessions) Leader of national research projects (ANR ORACLES, ANR ACTIVmap, ANR ECOCIM) Recipient of international mobility grants (AMICI I-SITE FUTURE) Contributor to national glossaries and research strategy (e.g., French photogrammetry glossary) Advising and Grants: Sidonie Christophe actively supervises PhD students and postdoctoral researchers, including Markie Jiang, Maria-Jesus Lobo, and Alexandre Mielniczek. She leads or participates in multiple funded research projects such as ANR ORACLES (marine flooding visualization), ANR ACTIVmap (tactile 3D maps), and ANR ECOCIM (eco-design of city information models). Her advisory role at the MESR involves shaping national research strategy in digital and environmental sciences. Labs and Research Teams: She is a core member of the GEOVIS team (Geovisualization, Interaction, and Immersion) at LASTIG and previously served as its leader. As co-director of LASTIG, she plays a central role in the leadership and strategic direction of the entire laboratory, which comprises over 100 researchers across four teams: ACTE, GEOVIS, MEIG, and STRUDEL.
Caroline Crockett is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Virginia, part of the School of Engineering and Applied Science. She holds a Ph.D. in Electrical Engineering from the University of Michigan and a B.S. from the University of Virginia. Her academic role emphasizes teaching and engineering education research. B.S., Electrical Engineering, University of Virginia, 2015 Ph.D., Electrical Engineering, University of Michigan, 2022 Her research interests are centered on engineering education, particularly how students develop conceptual understanding in core electrical engineering topics and learn to troubleshoot. She also has a background in machine learning and image reconstruction, though her current work focuses on pedagogy. She actively engages undergraduate students in research projects related to education and is a member of IEEE and ASEE. Her recent publications reflect a strong trend toward engineering education research, especially in signals and systems comprehension and affective student responses to active learning. Earlier work includes advanced image reconstruction techniques using bilevel optimization, showing a transition from technical signal processing to educational research. Caroline Crockett does not supervise graduate students or maintain a research lab, but she mentors undergraduates interested in engineering education. She has taught several key courses including Fundamentals of ECE 2, Fundamentals of ECE 3, and an Introduction to Machine Learning. She is committed to undergraduate instruction and curriculum development. She is involved in the broader academic community through her memberships in IEEE and ASEE, contributing to educational research and dissemination through conferences and publications. Outside of her academic duties, she enjoys knitting, reading, crafts, and spending time with her family and rescue dog Oreo. She is also a licensed amateur radio operator.
Krista A. Ehinger is an Associate Professor and co-lead of the AI group at the University of Melbourne's School of Computing and Information Systems. She holds a PhD from MIT and has held postdoctoral positions at York University and Harvard Medical School. Her research focuses on the intersection of human and computer vision, including scene recognition, visual search, and depth perception. Methodologically, she combines Bayesian models, deep learning, and behavioral experiments like eye tracking. Current projects explore AI applications in space systems (e.g., SpIRIT satellite) and ethical implications of workplace surveillance via computer vision. Recent work emphasizes amodal completion (e.g., reconstructing occluded objects) and AI reasoning systems. She collaborates on medical imaging (TCAM-Diff model), autonomous driving (truck speed detection), and 3D reconstruction. Her lab actively engages in open-source tools like the SUN Database for scene understanding. Professional activities include AI ethics discussions and academic service. She advises students on Masters/PhD projects and contributes to conferences like CVPR and NeurIPS.
Manfred Kern serves as Professor and Head of the Department of German Studies at Paris Lodron University Salzburg. With an extensive publication record dating back to 1995 and continuing through 2025, he maintains an active research profile in medieval literature and digital humanities. His leadership role as department head and project manager for significant research initiatives demonstrates his standing within the academic community. Professor Kern's research interests center on medieval literary cultures, particularly through the lens of digital humanities. His work on the Wenceslas Bible represents a significant interdisciplinary contribution, combining traditional philological approaches with cutting-edge computer vision techniques. His recent editorial work on disability representation in art ( Kunst und Gebrechen ) demonstrates expanding scholarly interests at the intersection of cultural history and visual studies. His research consistently bridges historical scholarship with contemporary methodological innovations. Kern's publication trends reveal a strategic evolution from traditional literary studies toward digital humanities applications. His most recent work (2024-2025) shows a strong emphasis on computational analysis of historical manuscripts, particularly the Wenceslas Bible project, while simultaneously developing theoretical frameworks for understanding disability representation in historical art contexts. This dual focus represents a sophisticated integration of technical and humanistic approaches to cultural heritage. As project manager for significant research initiatives including WB-DEA (The Wenceslas Bible - Digital Edition and Analysis, 2022-2024), TALC_ME (Textual and Literary Cultures in Medieval Europe, 2014-2017), and ALIENA (Old literature re-aestheticized in the experience space, 2010-2013), Professor Kern has secured substantial research funding and built collaborative networks across institutions. His organizational role in numerous academic events, including the IZMF lecture series and the In Nomine conference on medieval naming practices, further demonstrates his leadership in the field. Professor Kern actively participates in departmental and university governance, serving on habilitation committees and appointment committees (Berufungskommission). His academic service extends to editorial work and conference organization, reflecting his commitment to scholarly community building. His leadership of the German Studies department at Paris Lodron University Salzburg positions him at the center of academic activity in his field.
James M Martin-Hayden serves as an Associate Professor in the Department of Earth, Ecological and Environmental Sciences within the College of Natural Sciences and Mathematics at the University of Toledo. With over 25 years of service at the institution, he has established himself as a prominent hydrogeologist specializing in groundwater systems and environmental geology. Education: B.A. from University of Maine, M.S. and Ph.D. from University of Connecticut (1994) Current Position: Associate Professor of Geology Department: Earth, Ecological and Environmental Sciences University: University of Toledo Dr. Martin-Hayden's research focuses on hydrogeology, with particular emphasis on groundwater-surface water interactions in wetland ecosystems, numerical groundwater modeling, and hydrogeologic field methods. His work primarily investigates the Oak Openings Region of northwest Ohio, examining how drainage modifications have altered natural groundwater flow regimes that support wet prairies. He has made significant contributions to understanding wellbore flow dynamics, groundwater sampling methodologies, and the impacts of evapotranspiration on groundwater recharge. His research integrates field observations, numerical modeling, and geophysical techniques to address complex hydrogeological problems. Analysis of Dr. Martin-Hayden's publication record reveals a consistent research trajectory focused on hydrogeological systems, particularly in the Great Lakes region. His work spans from fundamental investigations of wellbore flow dynamics to applied studies of regional aquifer systems and wetland hydrology. Recent publications demonstrate increasing integration of geophysical methods with traditional hydrogeological approaches, reflecting an evolution toward more comprehensive characterization of complex subsurface systems. His research shows particular strength in addressing the hydrological impacts of human modifications to natural systems, especially in wetland ecosystems. Dr. Martin-Hayden has mentored several students, including Lucas Groat (thesis on Hydrogeology of Wet Prairies) and Pryanka More (undergraduate thesis on Influences of ET on Groundwater Recharge). His collaborative work shows strong connections with researchers including Timothy G. Fisher, Kennedy Okioghene Doro, and Richard H. Becker, indicating active participation in research networks focused on Great Lakes geology and hydrogeology.
