Find Academic Supervisors

• 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.

• Computer Science
• Databases
• Knowledge Representation & Reasoning
• +7 more

Dr. Yacine Sam is a Lecturer in Computer Science at the Polytechnic School of the University of Tours (EPU), affiliated with the Fundamental and Applied Computer Science Laboratory of Tours (LIFAT). His research focuses on databases, knowledge representation & reasoning, web services, and semantic web technologies. Doctorate in Computer Science, Paul Cézanne University Aix-Marseille 3 (2008) Master 2 Research in Computer Science, Claude Bernard University Lyon 1 (2005) Dr. Sam's research spans multiple subfields including: Trustworthy execution of adaptive business processes Privacy ontologies for Web of Things Deep learning applications in personalized service recommendations Linked open data frameworks for semantic integration Blockchain implementations in distributed systems Health analytics using collaborative IoT data Contact: yacine.sam@univ-tours.fr

Dominik HuberView profile

Researcher

• Dynamic Resource Management in High-Performance Computing (HPC)
• Parallel & Distributed Programming Models
• Hardware-aware Programming
• +6 more

Dominik Huber is a Ph.D. candidate and researcher at the Technical University of Munich , affiliated with the Chair of Computer Architecture & Parallel Systems . His work focuses on Dynamic Resource Management in High-Performance Computing (HPC) , with expertise in Parallel & Distributed Programming Models and Hardware-aware programming . He has actively contributed to teaching courses like Parallel Programming Systems and Advanced Computer Architecture . His research emphasizes adaptive resource allocation in hybrid HPC clusters, leveraging technologies such as MPI Sessions , PMIx , and frameworks like LAIK and XBraid . Recent projects include the DynRes software suite for dynamic resource management and collaborations on quantum-HPC integration. Huber has advised students on topics ranging from Dynamic Resource Management in Charm++ to CI Systems for HPC Software , and his publications address challenges in malleability, scheduling, and power-constrained environments. Current affiliations include participation in the SEANERGYS (EuroHPC) and PlasmaPEPS projects.

• Architecture
• Urban and regional planning
• Design
• +5 more

Professor Alan Penn is a leading academic at University College London's The Bartlett School of Architecture , where he holds the title of Professor in Architectural and Urban Computing. He previously served as Dean of the Bartlett Faculty of the Built Environment from 2009 to 2019 and has been instrumental in establishing Space Syntax Ltd , a UCL knowledge transfer spin-out company. His affiliations include membership in the Space Syntax Laboratory, board membership of UCL Consultants Ltd, and trustee status at Shakespeare North Trust. Education: BSc (1978), Dip Arch (1980), MSc (1983) - all from University College London Alan Penn’s research investigates how spatial design influences social and economic behaviors through innovative space syntax methodologies . Key areas include: Agent-based simulations of human behavior Spatio-temporal representations of built environments Urban spatial network analysis Urban sustainability across multiple dimensions Cognitive markers in architectural design Historical urban growth modeling His recent publications demonstrate a strong focus on computational urbanism, evolutionary city patterns, and behavioral architecture. Research trends show interdisciplinary approaches combining architectural theory with: Machine learning applications Network science analysis Behavioral psychology insights Historical GIS techniques Complex systems modeling Public health considerations Scientific recognition includes: HEFCE Business Fellowship (2001-2005) KTP SE Region Award (2010) Multiple UCL Enterprise awards ‘Spirit of Enterprise’ Award (2008) As Principal Investigator he leads the £5m EPSRC-funded Urban Dynamics Lab , demonstrating sustained research excellence. His work extends to public engagement through: Shakespeare North Trust educational theatre development Media appearances (New Scientist, Slashdot) Public policy contributions

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.

Andrew DunningView profile

Research Fellow

• Medieval Studies
• Book History
• Digital Humanities
• +3 more

Dr Andrew Dunning is the R.W. Hunt Curator of Medieval Manuscripts at the Bodleian Library, University of Oxford, and a Hugh Price Fellow at Jesus College. He holds a BA from the University of Ottawa, followed by MA and PhD in Medieval Studies from the University of Toronto. His research focuses on medieval manuscripts, book history, and digital scholarship, with a particular emphasis on Oxford’s manuscript heritage and the cult of Saint Frideswide. He collaborates internationally with institutions like the British Library and Cambridge University Library. Dr Dunning teaches medieval manuscripts and digital methods at the Weston Library, supervises postgraduate students in medieval studies and cultural heritage projects, and chairs the MSt examination in Medieval Studies. He leads digitization initiatives for Jesus College manuscripts via Digital Bodleian and directs the Medieval Libraries of Great Britain dataset. His work bridges traditional scholarship with computational tools, including open-source projects like Citation Style Language and Pandoc. Key roles include: R.W. Hunt Curator at Bodleian Library Hugh Price Fellow at Jesus College Co-supervisor of the AHRC Collaborative Doctoral Award project on medieval chant and religious heritage Research interests span medieval book production, digital manuscript studies, and cultural heritage preservation. Recent projects include the forthcoming monograph Lives and Miracles of Saint Frideswide , funded grants from the British Academy and Zeno Karl Schindler Foundation, and editorial work on medieval Latin texts. His work emphasizes the intersection of material culture and textual transmission. Publications include critical editions of medieval works (e.g., Iohannis Scotti seu Eriugenae Carmina ) and articles on manuscript provenance, digital cataloging, and medieval liturgical practices. He actively contributes to scholarly communities through grants, fellowships, and open-access initiatives.

• Human-Computer Interaction (HCI)
• Data Visualization
• Information Design
• +3 more

Matt Brehmer is an Assistant Professor at the University of Waterloo's School of Computer Science, specializing in Human-Computer Interaction (HCI) and Data Visualization. He directs the ubietous Information Experiences research group. Previously, he was a Lead Researcher at Tableau and part of the EPIC HCI group at Microsoft Research. His work emphasizes novel methods for data communication and collaboration, particularly in spatial computing and multimodal interaction. Research interests include data visualization design, mobile visualization, and expressive storytelling through timelines and dynamic interfaces. He has contributed to tools like Timeline Storyteller and Charticulator, focusing on user-centered design and accessibility. His awards include the IEEE VIS Test of Time Award (2023) and Best Paper Honorable Mentions at ACM UIST and IEEE VIS. Brehmer actively serves on program committees for IEEE VIS, CHI, and Computation + Journalism, and leads initiatives to bridge academic research with industry needs. His recent work explores gesture-aware augmented reality for remote presentations, emoji-based data visualization, and flexible timeline authoring. Brehmer collaborates with institutions globally, including organizing workshops on multimodal data communication and contributing to visualization standards through IEEE.

• Machine Learning
• Interactive Machine Learning
• Healthcare Applications
• +5 more

Dr. Brian Mac Namee is an Associate Professor at the School of Computer Science, University College Dublin (UCD), and UCD Site Director at the Insight SFI Research Centre for Data Analytics since 2024. His research focuses on interactive machine learning, emphasizing human-centered model training, with applications in healthcare, agriculture, space technology, and virtual reality. He co-authored the textbook Fundamentals of Machine Learning for Predictive Data Analytics , translated into five languages. Education includes a PhD (2004) and BA (Mod) from Trinity College Dublin. He previously co-founded the Applied Intelligence Research Centre at Technological University Dublin and was a founding co-PI at CeADAR. He chairs the Artificial Intelligence Association of Ireland and directs training at Krisolis Ltd. Notable awards include the 2016 Data Science Award for Best Academic Research Team and UCD's Fiosraigh Research Excellence Award (2013). His teaching spans advanced machine learning, data science projects, and programming courses. He leads grants such as the SFI-funded Machine Learning & Virtual Reality for Pilot Training and co-directs the SFI Centre for Research Training in Machine Learning.

Cory SimonView profile

Associate Professor

• Machine Learning
• Bayesian Optimization
• Computational Materials Science
• +3 more

Cory Simon serves as Associate Professor in the Department of Chemical, Biological, and Environmental Engineering within Oregon State University's College of Engineering. His research integrates machine learning, optimization, and chemical engineering to advance materials discovery and environmental sensing systems. His academic foundation includes a Ph.D. in Chemical Engineering from the University of California, Berkeley and a B.S. in Chemical Engineering from The University of Akron. Simon's work centers on Bayesian methodologies for scientific challenges, featuring: Bayesian optimization for adaptive materials synthesis Statistical inversion of physical systems with uncertainty quantification Computational design of nanoporous sensor arrays Stochastic algorithms for robotic environmental monitoring Recent publications demonstrate accelerating focus on multi-fidelity optimization for molecular design and atmospheric water harvesting, bridging chemical engineering with computational science through data-driven approaches. Leading The Simon Ensemble research group, Simon champions a versatile 'buffet-style' research philosophy—drawing from mathematics, statistical mechanics, and machine learning to address interdisciplinary problems across chemistry, materials science, and environmental engineering.

Kevin SchneiderView profile

Professor

• Software Architecture and Design
• Software Evolution and Maintenance
• Software Analysis and Navigation
• +6 more

Dr. Kevin Schneider is a Professor in the Department of Computer Science at the University of Saskatchewan. His research focuses on software architecture, evolution, analysis, and visualization, with notable work in quantum computing applications and machine learning. He also explores collaborative software teams and domain-specific languages to enhance development processes. Education: Ph.D., Computing and Information Science, Queen’s University (2000) Research Associate, Computing and Information Science, Queen’s University (1991–94) M.Sc., Computing and Information Science, Queen’s University (1990) B.Sc.(Hon), Computational Science, University of Saskatchewan (1980) Research interests include software design principles, maintenance strategies, and the integration of AI/quantum computing into software engineering. He emphasizes reproducibility in scientific workflows and tools like VizSciFlow. His work often bridges theory and practice, addressing challenges in code clone stability, user feedback management, and healthcare-related machine learning frameworks. Scientific Awards: Most Influential Paper at SCAM 2001 for his work on software engineering via source transformation. Advising and grants: While no specific advisees are listed, his research involves large-scale projects such as the Nutrient App and automated polyp segmentation tools. He collaborates on grants related to quantum computing applications and cloud-based software systems. Labs and teams: His work centers on collaborative scientific data analysis groups and developing tools for real-time groupware systems in complex workflows. He contributes to projects like CloneCognition and FSECAM, aiming to improve software design and maintenance through advanced analytics.

Jan BernauerView profile

Associate Professor

• Nuclear Physics
• Particle Physics
• Proton Structure
• +3 more

Jan Bernauer is an Associate Professor in the Department of Physics and Astronomy at Stony Brook University with a joint position at RIKEN BNL Research Center. He obtained his Ph.D. from Johannes Gutenberg University Mainz in 2010 and previously held research positions at MIT from 2010-2018. Education: Ph.D. in Nuclear Physics, Johannes Gutenberg University Mainz (2010) Diplom in Physics, Johannes Gutenberg University Mainz His research focuses on precision nuclear physics at the intersection of particle and nuclear physics, including proton form factor measurements, two-photon exchange effects, and beyond-Standard-Model searches. Current projects involve sPHENIX streaming readout, MUSE (muon scattering), and TPEX (two-photon exchange) experiments. Research outputs emphasize precision measurement techniques, with recent work on detector development (40% of publications) and QCD fundamentals (30%). Collaborative projects span 15+ institutions including MIT, DESY, and Jefferson Lab. Awards & Recognition: Infinite Kilometer Award (MIT, 2017) NSF Career Award Stony Brook Foundation Award Research Teams: Leads a group with 2 postdocs, 3 graduate students, and 4 undergraduates developing novel detector systems for RHIC and EIC. Current grants support instrumentation development for streaming readout in particle physics experiments.

John GuttagView profile

Professor

• AI for Healthcare and Life Sciences
• Biological and Medical Devices and Systems
• Graphics and Vision
• +3 more

John Guttag is the Dugald C. Jackson Professor in Electrical Engineering and Computer Science at MIT. His work focuses on AI-driven healthcare solutions, biomedical systems, and advanced computer vision applications. He leads research in medical image analysis, machine learning reliability, and healthcare equity. Guttag's contributions include innovative frameworks like MultiMorph and Scale-Space Hypernetworks, addressing challenges in medical imaging and clinical decision-making. Affiliations: MIT Electrical Engineering & Computer Science Department (EECS) Research emphasizes AI for healthcare, particularly in segmentation, predictive analytics, and ethical algorithm design. Notable projects include real-time fraud detection systems and studies on racial disparities in clinical risk scores. His work bridges computer science with clinical practice through tools like Voxelmorph for medical image registration and ScribblePrompt for interactive biomedical segmentation. Recent publications highlight advancements in uncertainty-aware AI, contrastive learning, and scalable medical data processing. Guttag’s methodologies prioritize practical clinical applications, aiming to improve diagnostics and healthcare workflows. His lab develops open-source tools and frameworks that enhance accessibility to advanced medical imaging technologies.

Leow Wee KhengView profile

Associate Professor

• Medical Image Analysis
• Computer Vision
• 3D Modeling
• +5 more

Associate Professor Leow Wee Kheng is affiliated with the Department of Computer Science at the School of Computing, National University of Singapore . His career spans over three decades with expertise in medical image analysis , computer vision , and surgical simulation . Ph.D. in Computer Science, University of Texas at Austin (1994) M.Sc. in Computer Science, National University of Singapore (1989) B.Sc. in Computer Science, National University of Singapore (1985) His research focuses on medical image analysis for craniofacial surgery and stroke diagnosis, 3D modeling of anatomical structures, and computer vision techniques like robust PCA and texture analysis . Recent work includes knee joint motion modeling and forearm rotation simulation for clinical applications. Key trends in his 2017-2025 publications involve skull reconstruction algorithms , multi-objective optimization for digital media, subject-specific biomechanical modeling , and low-rank decomposition techniques in visual computing. Collaborations include institutions like Singapore General Hospital and National Taiwan University Hospital . Scientific Awards : CAIP 2017 Best Paper Award 2007 Andrew P. Sage Best Transactions Paper Award Faculty Teaching Excellence Award (AY2015/16) Annual Teaching Excellence Award (AY2015/16) He has mentored numerous students in medical imaging , computer vision , and biomedical modeling . Current and former advisees include Chen Ying , Vineta Lum Lai Fun , and Long Huizhong (Ph.D.).

Catherine De WolfView profile

Assistant Professor

• Circular Engineering
• Sustainable Construction
• Digital Innovation
• +3 more

Prof. Catherine De Wolf is an Assistant Professor at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering and Deputy Head of the Institute of Construction and Infrastructure Management. She leads the Chair of Circular Engineering for Architecture (CEA), an interdisciplinary lab focused on automating building material reuse through digital innovation. Her work bridges academia, government, and industry, exemplified by partnerships with institutions like the Centre Pompidou and initiatives like Anku and the Digital Circular Economy (DiCE) Lab. She is also a faculty member at ETH Zurich's AI Center and collaborates with EMPA's Urban Energy Systems Lab. Her roles include Chair of the Design++ Advisory Board and PI in the National Centre of Competence in Research on Digital Fabrication (DFAB). Education: Catherine holds a PhD in Building Technology from MIT, with prior studies in Civil Engineering and Architecture at VUB and ULB. She has additional training in documentary filmmaking and postdoctoral research at the University of Cambridge and EPFL's Structural Xploration Lab, funded by Marie Sklodowska-Curie and Swiss Excellence scholarships. Research Interests: Her work centers on digital tools for circular construction, including blockchain-based material passports, AI-driven design, and automated deconstruction planning. Key areas include: Material reuse and lifecycle analysis Building Information Modeling (BIM) applications Decentralized data networks in construction Carbon reduction in structural systems Interdisciplinary collaboration across engineering, architecture, and computer science Awards: Marie Sklodowska-Curie Postdoctoral Fellowship (European Commission) Swiss Excellence Scholarship Advising & Grants: Catherine has overseen projects funded by EU initiatives and industry partnerships. Her research group actively collaborates with firms like Arup and Thornton Tomasetti through initiatives such as the Structural Engineers 2050 Commitment. She advises on policy frameworks like the EU's Level(s) sustainability standard. Labs & Teams: Her CEA lab operates with 20+ researchers and has pioneered tools like the '5D Digital Circular Workflow.' The lab's work is showcased in real-world projects such as the Centre Pompidou material reuse case study.