Philip Dutré is a full professor at the Department of Computer Science , Faculty of Engineering Science , KU Leuven. He leads the Computer Graphics Research Group and chairs the Human-Computer Interaction division . His teaching portfolio includes courses on algorithms, data structures, and computer graphics fundamentals. Research Focus : Rendering algorithms, photo-realistic and image-based rendering, perceptual-based rendering, material models, and intuitive controls for computer animation. He explores deep learning applications in global illumination and uses quantum field theory for efficient light transport in participating media. Publications : Recent work includes advancements in temporal coherence for light transport (2017–2023), functional integrals for scattering models (2025), and optimization of spatial data structures (2019). Teaching Innovations : Advocate for ungrading (feedback-only assignments), flipped classroom techniques, and interactive learning. His approach emphasizes conceptual understanding over rote memorization, with structured, self-contained lessons and active student engagement. Leadership : Serves on multiple academic councils and committees including the Commission on Research Integrity and Student Services Council .
Vanessa Wood is a Professor at ETH Zürich in the Department of Mechanical and Process Engineering. She specializes in understanding structure-performance relationships in complex, heterogeneous systems, particularly lithium ion batteries, using advanced imaging techniques like electron and x-ray microscopy to address performance limitations and guide material improvements. Research Interests: Investigating nanoscale structure and surface chemistry in battery materials Studying electrolyte infilling and lithium transport dynamics Developing computational methods for multiscale material analysis Integrating machine learning to overcome experimental challenges Designing volumetric imaging approaches for energy storage systems Research Affiliations: Affiliated with the Microstructure Physics and Alloy Design group and Interdepartmental & Partner Research Groups at ETH Zürich. Her work bridges experimental and computational disciplines to improve energy technologies.
Glaucio H. Paulino holds the Margareta Engman Augustine Professorship in Civil and Environmental Engineering at Princeton University, where he also serves as a Professor at the Princeton Institute for the Science and Technology of Materials (PRISM). His work bridges computational mechanics, topology optimization, and materials science. Paulino leads a research group focused on advancing structural design methodologies, fracture mechanics, and functionally graded materials. His team has pioneered polygonal finite elements and multiresolution topology optimization techniques, addressing challenges in mesh bias and computational efficiency. He has published over 240 peer-reviewed articles and mentored 19 PhD and 11 MS students. Notable contributions include the PPR cohesive model for fracture analysis and adaptive mesh refinement for dynamic simulations. Paulino's research extends to practical applications such as high-rise building design and sustainable construction materials. Awards include election to the European Academy of Sciences and Arts and ASME’s Melville Medal. Current projects involve functionally graded cement-based materials, extrusion processing, and digital image correlation for material characterization. His lab collaborates with industry partners like Skidmore, Owings & Merrill LLP to translate topology optimization into real-world engineering solutions. Paulino’s interdisciplinary approach integrates computational modeling with experimental validation, fostering innovations in civil infrastructure resilience.
Dr. Gary Glover is a Professor of Radiology (Radiological Sciences Lab) at Stanford University , with courtesy appointments in Psychology and Electrical Engineering. His work focuses on the physics and mathematics of MRI, particularly rapid scanning methods using spiral k-space trajectories for functional brain imaging and multimodal neuroimaging (fMRI/EEG/fPET/fNIRS) combined with neuromodulation techniques like TMS and transcranial ultrasound. Academic Appointments: Radiology, Psychology, Electrical Engineering Professional Affiliations: Bio-X, Stanford Cancer Institute, Wu Tsai Neurosciences Institute Research Interests include: Development of blood oxygen level-dependent (BOLD) and viscoelastic contrast in MRI Functional MR Elastography for brain activation mapping Optimization of MR-ARFI for transcranial ultrasound guidance Automated spinal cord segmentation (EPISeg) using machine learning Scientific Awards : National Academy of Engineering (2013) Gold Medal, ISMRM (2000) Steinmetz Award, General Electric (1985) Lauterbur Lecture, ISMRM (2018) Recent Publications analyze: Fast fMRI sampling and spurious signal correction Dissociated patterns in default mode network anti-correlations Neural correlates of collaborative behavior in triadic fMRI Salience network contributions to depression pathophysiology
Vita Goei is an Associate Professor at the Medical College of Georgia within Augusta University , specializing in Pediatrics with a focus on Pediatric Gastroenterology . Holding an MD from Albert Einstein College of Medicine (1986) and a BA in Biology from Yeshiva University (1979) , she has practiced pediatric gastroenterology since 1996. Education: MD, Albert Einstein College of Medicine (1986) BA, Yeshiva University (1979) Her research career began in molecular biology with seminal work on the GABA(B) receptor gene and MHC class I transcription . She now seeks clinical studies in pediatric GI, particularly liver disease, Cystic Fibrosis , Inflammatory Bowel Disease , and Eosinophilic Esophagitis . Recent publications span antimicrobial therapy, genetic variants, and diagnostic case studies. Certifications: Basic Life Support (AHA, 2023) Georgia Composite Medical Board (2000) Professional service includes continuous affiliation with the Department of Pediatrics (Gastroenterology) since 2007, previously serving in the same department from 2000-2007.
Professor David Taubman is a distinguished academic serving as Professor and Deputy Head of School (Research) at the School of Electrical Engineering and Telecommunications (EE&T) at the University of New South Wales (UNSW) in Sydney, Australia. He is also co-director of Kakadu Software Pty. Ltd. and its affiliates Kakadu R&D and Kakadu GPU. With a career spanning over three decades, Professor Taubman has made significant contributions to the field of image and video compression, most notably as the author of the EBCOT coding algorithm adopted in the JPEG2000 international standard. Professor Taubman earned his B.Sc. in Mathematics and Computer Science (1986) and B.E. (Medal) in Electrical Engineering (1988) from the University of Sydney, followed by an M.Sc. (1992) and Ph.D. (1994) in Electrical Engineering from the University of California at Berkeley. His professional journey includes engineering work at the Electricity Commission of N.S.W. (1988-1990), research positions at Hewlett-Packard Laboratories in Palo Alto (1994-1998), and an academic career at UNSW where he progressed from Senior Lecturer (1998-2003) to Associate Professor (2004-2009) and finally to Professor (2009-present). He has held various leadership roles including Head of the EE&T Telecommunications Research Group (2003-2014), Head of the EE&T Signal Processing Research Group (2014-present), Director of Research for the School of EE&T (2011-2016), and Deputy Head of School (Research) since 2017. Professor Taubman's research interests center on image and video compression, with particular expertise in JPEG2000 standards and implementations. His work spans signal processing, wavelet transforms, scalable video coding, motion modeling, and multimedia systems. He has pioneered numerous compression algorithms and frameworks, including the EBCOT coding algorithm that became central to the JPEG2000 standard. His recent research focuses on efficient motion modeling with cuboidal partitioning, learned lifting-based transform structures, and high-throughput implementations of JPEG2000 for video applications. His work bridges theoretical foundations with practical implementations, as evidenced by the commercially successful Kakadu Software tools that have garnered around 500 commercial licensees. Analysis of Professor Taubman's recent publications reveals a consistent focus on advancing compression technologies with particular emphasis on scalability, efficiency, and adaptability. His work spans traditional image compression (JPEG2000 extensions), video coding (cuboid-based partitioning for UHD/360-degree video), and emerging applications (nanopore sequencing data compression). A notable trend is the integration of machine learning techniques with traditional compression frameworks, as seen in his work on learned lifting-based transform structures. His research maintains strong connections to real-world applications across diverse domains including medical imaging, astronomical data processing, and genomic sequencing. IEEE Fellow Engineers Australia Fellow (by invitation) Professor Taubman has served as Associate Editor for the IEEE Transactions on Image Processing for two four-year appointments (2003-2005 and 2010-2013). He has been actively involved in numerous research grants focused on image and video compression technologies, particularly those related to the JPEG2000 standard and its extensions. His work has received significant industry support, reflected in his consultancy with various U.S., Japanese, and Australian corporations. He has also contributed to international standards development as a member of Standards Australia Technical Committee MS-065 (mirroring ISO TC42 on Digital Photography) and as a constitutional member of Standards Australia Technical Committee IT-029 (Coded Representation of Picture, Audio and Multimedia/Hypermedia Information). Professor Taubman co-directs Kakadu Software Pty. Ltd. and its research affiliates Kakadu R&D and Kakadu GPU, which have developed the commercially successful Kakadu Software tools for JPEG2000. His research group at UNSW focuses on advanced image and video compression techniques, with particular expertise in wavelet-based methods, scalable coding, and motion modeling. The group maintains strong industry connections and has contributed significantly to the development and standardization of image compression technologies worldwide.
Dr. Nicholas Brake is an Associate Professor at Lamar University's Department of Civil and Environmental Engineering, focusing on reclaimed materials, wireless power transfer applications in concrete, and fatigue fracture modeling for pavements. His research spans recycled concrete aggregate, coal ash utilization, and electromagnetic cementitious composites. Education: Ph.D., M.S., B.S. in Civil Engineering from Michigan State University Awards: Anita Riddle Fellowship (2018), Lamar Merit Award (2018), Presidential Faculty Fellowship (2015), and multiple scholarships during his studies. His research emphasizes three key areas: 1) Material reclamation using recycled concrete aggregate, coal combustion residuals, and EAF slag. 2) Electromagnetic transport properties for wireless vehicle charging applications. 3) Fatigue damage modeling in concrete pavements. Through 3D printing integration and design-build-test pedagogy, he enhances student learning outcomes. Recent publications focus on international engineering education (2020), magnetic concrete composites (2019), and advanced testing methodologies for civil infrastructure (2018). His teaching innovation includes developing nine Lamar University courses with active learning strategies that improved student design confidence (p Scientific Awards: Anita Riddle Excellence in Teaching Fellowship (2018) Presidential Faculty Fellowship for Teaching Innovation (2015) Outstanding Teaching Assistant Award at Michigan State (2011) Dr. Brake mentors undergraduate and graduate researchers, including doctoral candidates Mahdi Feizbahr and Hossein Hariri Asli (2023-2024). His lab (LUMS) houses advanced testing systems like Instron 5965/8803, MTS Insight 100SL, and thermal analyzers for material characterization.
Ethan A. Scott is a Research Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of Virginia. He holds a B.S. (2015) and Ph.D. (2021) in Mechanical and Aerospace Engineering from UVA, followed by a postdoctoral research associate position at Sandia National Laboratories. His research focuses on experimental techniques for analyzing heat and energy transfer in extreme material conditions, including micro- and nanoscale phenomena. He serves as Deputy Director of the EXSiTE Lab led by Professor Patrick Hopkins. Education: B.S., Mechanical Engineering, University of Virginia (2015) Ph.D., Mechanical and Aerospace Engineering, University of Virginia (2021) Postdoctoral Research Associate, Sandia National Laboratories (2021–2023) Research Interests: Ethan explores advanced thermal transport phenomena using electro- and optothermal methods. Key areas include micro/nanoscale heat transfer, microfabrication, and infrared thermal detection. His work addresses challenges in material size extremes (e.g., nanoscale thin films) and environmental extremes (e.g., high-energy ion irradiation effects). Publications: His recent work emphasizes thermal conductivity manipulation through ion irradiation, optothermal sensor development, and novel material characterization. Themes include defect engineering in crystalline systems and optimizing thin-film thermometry for high sensitivity. Awards: Editor’s Pick, Applied Physics Letters (2021) Nuclear Regulatory Commission Fellowship (2017) Labs & Teams: Deputy Director of the EXSiTE Lab, focusing on experimental studies of thermal and mechanical properties of materials under extreme conditions.
Martin Berzins is a Professor of Computer Science at the University of Utah, affiliated with the School of Computing and the Scientific Computing and Imaging (SCI) Institute. His research focuses on parallel scientific computing, numerical methods for partial differential equations, and high-performance computing frameworks. He is a leading developer of the Uintah framework, a scalable simulation tool used for large-scale engineering and scientific problems. Research Interests : Parallel algorithms, adaptive mesh refinement, material point method (MPM), exascale computing, computational fluid dynamics, and performance portability. His work emphasizes scalable software solutions for complex multiscale and multiphysics simulations, with applications in environmental modeling, explosive detonation analysis, and computational mechanics. Recent articles highlight advancements in Uintah's portability to exascale systems, error estimation in MPM, and high-order numerical methods. Berzins has contributed significantly to the development of task-based parallelism strategies and heterogeneous computing optimizations. His research bridges theoretical numerical analysis with practical large-scale computational challenges. Collaborations include DOE projects on hazard analysis and exascale computing. He has pioneered the integration of runtime systems like Hedgehog with Uintah to enhance scalability on modern architectures. His work ensures computational frameworks remain viable for emerging hardware trends, emphasizing both algorithmic innovation and software engineering rigor.
Eduardo Alonso Pérez de Agreda is a faculty member at the Universitat Politècnica de Catalunya in the Departament d'Enginyeria del Terreny, Cartogràfica i Geofísica . He leads research in geotechnical engineering and rock mechanics, particularly focusing on landslides, tunneling in expansive rocks, and multiphase soil interactions. Research Highlights Analyzing soil saturation dynamics using digital imaging Modeling tunnel lining in anhydritic claystones Studying mineral precipitation impacts on infrastructure Recent Article Trends Over 15 articles (2021–2025) on landslides, tunneling, soil liquefaction, and multiphase interactions Keywords span geotechnical engineering, computational methods, rock mechanics, and material science Subfields include stress-dilatancy, material heterogeneity, swelling rocks, and landslide triggering mechanisms Awards Baker Medal (2017) Telford Gold Medal (2019) Advising Advised PhD students: G. Di Carluccio (2020), C. Alvarado (2017), M. Alvarado (2021) Co-advised: L. Tapias, Y. Salami, R. Fuentes Labs & Collaborations Active in the MSR - Mecànica del Sòls i de les Roques and GGMM - Grup de Geotècnia i Mecànica de Materials research groups Collaborated with institutions in Spain, Italy, and China
Nicolas Riviere is a Professor at INSA Lyon in the Department of Mechanical Engineering, working within the Laboratory of Fluid Mechanics and Acoustics (LMFA - UMR 5509). He is part of the "Fluides complexes et transferts" (Complex Fluids and Transfers) group and the Environment team. His teaching activities primarily focus on fluid mechanics at the Mechanical Engineering Department of INSA Lyon, covering: General balances (mass, momentum, energy) Aerodynamics Compressible flows Numerical simulation of flows Free surface hydraulics Prof. Riviere's research centers on free surface hydrodynamics, with applications to natural and industrial risks. His work takes an experimental approach, utilizing the laboratory's channel facilities, particularly the channel intersection installation. His research spans river floods with compound beds, urban flooding, sanitation networks, torrential flows, and flow-obstacle interactions. He has developed a strong interdisciplinary focus, co-leading the "Baignades en Rivières Urbaines" studio with Oldrich Navratil from University Lyon 2 and the EVS Laboratory. His publication record demonstrates consistent contributions to the fields of fluid mechanics and environmental hydraulics, with recent work focusing on open-channel flows, urban flooding phenomena, vegetation-flow interactions, and experimental techniques for studying complex hydraulic phenomena. His research often bridges theoretical fluid mechanics with practical environmental applications. Prof. Riviere has received recognition for his work in environmental fluid mechanics, with numerous publications in high-impact journals in hydraulic engineering and fluid mechanics. He has supervised multiple PhD students and research projects related to environmental fluid mechanics and has collaborated with various institutions on interdisciplinary research projects addressing water-related challenges. The laboratory where he works, LMFA, provides extensive experimental facilities including wind tunnels, hydrodynamic channels, and advanced measurement techniques such as PIV (Particle Image Velocimetry), LDV (Laser Doppler Velocimetry), and other state-of-the-art instrumentation for fluid flow analysis.
Aurélie Labbe is a Full Professor in the Department of Decision Sciences at HEC Montréal, holding the prestigious FRQ-IVADO Chair in Data Science. Appointed as Co-Scientific Director – Academic Partnerships at IVADO in October 2023, she plays a key leadership role in establishing connections between IVADO and partner universities. Her academic journey includes a PhD in Statistics from the University of Waterloo, a Master's degree in Statistics from the University of Montreal, and dual Bachelor's degrees in Applied Mathematics and Social Sciences from Paris-Dauphine University and Pure Mathematics from Versailles-St Quentin University. Her research spans multiple interdisciplinary domains with a focus on developing advanced statistical and machine learning methodologies for big data analysis. Labbe's work bridges theoretical statistics with practical applications across diverse fields including genomics, neuroscience, transportation systems, and health informatics. She has made significant contributions to kernel methods, matrix factorization techniques, random forest applications, and spatiotemporal data analysis, with publications appearing in top journals across multiple disciplines. Analyzing her recent publications reveals a clear trend toward methodological innovation applied to complex real-world problems. Her work demonstrates expertise in handling high-dimensional data from diverse sources including neuroimaging, transportation networks, and genomic studies. The interdisciplinary nature of her research connects statistical theory with applications in healthcare, transportation safety, and biological sciences, reflecting her ability to develop methods that address domain-specific challenges while advancing statistical methodology. Holder of the FRQ-IVADO Chair in Data Science Member of the Center for Mathematical Research Training Professor Labbe actively mentors the next generation of data scientists, supervising numerous doctoral and master's students. Her supervision portfolio includes 1 doctoral thesis (2023), 4 master's theses (2022-2024), and 32 supervised projects spanning 2019-2025. Her students' work covers diverse applications including transportation safety, healthcare analytics, financial modeling, and environmental analysis. Through her leadership of the FRQ-IVADO Chair in Data Science, she coordinates research activities that integrate mathematical, statistical, and computer science expertise with domain knowledge from various data-generating fields. As Co-Scientific Director at IVADO, Professor Labbe leads efforts to establish connections with faculties and departments across five partner universities, integrating them into IVADO's research and knowledge transfer activities. Her leadership role positions her at the forefront of advancing data science research and applications in Quebec's academic ecosystem.
Elizabeth J. Marsh is a Professor of Psychology and Neuroscience at Duke University and a Faculty Network Member of the Duke Institute for Brain Sciences . Her work bridges cognitive psychology, neuroscience, and education, with a focus on memory accuracy, misinformation, and aging. Education: Ph.D., Stanford University (1999) B.A., Drew University (1994) Research Interests: Marsh investigates how memory can be both accurate and erroneous, exploring questions like why people misremember facts, how fiction influences memory, and how aging affects decision-making and belief formation. Her work intersects with social psychology , developmental psychology , and educational psychology . Scientific Awards: Langford Lecture Award (2010) Grants & Funding: Aging and Finding Information: Using Google vs. Relying on Other People (2015–2025) Effects of Aging on Episodic Memory-Dependent Decision Making (2018–2025) When are pictures worth a thousand words? Debunking misinformation with images (2022–2023) Advancing Artificial Intelligence for the Naval Domain (2018–2023) Leveraging Older Adults' Social Goals to Improve Memory and Strategy Use (2018–2020) Exploring the potential of essay testing for improving memory and learning (2013–2019) Courses Taught: PSY 990: Special Readings in Psychology PSY 765S: Psychology and Neuroscience Grant Writing PSY 755: Research Practicum PSY 724S: Survey of Current Topics in Psychology and Neuroscience II PSY 723S: Survey of Current Topics in Psychology and Neuroscience I PSY 102: Cognitive Psychology: Introduction and Survey NEUROSCI 755: Interdisciplinary Program in Cognitive Neuroscience (IPCN) Independent Research Rotation
Brenda Schulman is a Professor and Director of the Molecular Machines and Signaling Pathways department at the Max Planck Institute of Biochemistry in Martinsried, Germany. She also holds an honorary professorship at the Technical University of Munich's Department of Chemistry and serves as Adjunct Faculty at St. Jude Children's Research Hospital in Memphis, TN, USA. Her research focuses on understanding how ubiquitin and ubiquitin-like proteins regulate cellular processes through protein modification. Dr. Schulman's research interests center on structural biology of the ubiquitin-proteasome system and ubiquitin-like proteins. Her work has shown that hundreds of dynamic multiprotein complexes are transiently converted into different conformations by specialized regulatory factors that control ubiquitin and ubiquitin-like proteins, thereby monitoring virtually all processes in cell biology. She combines biochemical reconstitution, structural analysis, enzymology, protein design, cell biology, and genetics to understand how these molecular machines function. Her research has significant implications for understanding diseases such as cancer, neurodegenerative disorders, and viral infections where defects in ubiquitin pathways are implicated. Her extensive publication record demonstrates expertise in ubiquitin signaling, protein degradation mechanisms, structural biology of E3 ligases, and molecular machines. Her work spans from fundamental mechanisms of ubiquitin chain formation to therapeutic applications in targeted protein degradation. Among her numerous scientific accolades are the Feldberg Prize for Anglo-German Scientific Exchange (2025), ERC Advanced Grant (2023), Louis-Jeantet Prize for Medicine (2023), Gottfried Wilhelm Leibniz Prize (2019), and election to the National Academy of Sciences (2014). She has also received the Dorothy Crowfoot Hodgkin Award from The Protein Society and has been an Investigator of the Howard Hughes Medical Institute. Dr. Schulman leads an active research group that has produced numerous high-impact publications in top journals including Nature, Cell, and Nature Structural & Molecular Biology. Her team has made significant contributions to understanding the structural mechanisms of ubiquitin transfer, E3 ligase specificity, and the role of ubiquitin in cellular quality control pathways. Current research in her lab focuses on deciphering the ubiquitin code and developing novel approaches for targeted protein degradation.
Professor Stephen Croft is a faculty member at Lancaster University , affiliated with the School of Engineering . His research focuses on Nuclear Materials Measurement Science , with expertise in radiation detection, neutron interrogation, and X-ray/gamma-ray spectroscopy. Current projects include cosmic ray neutron monitoring , active neutron interrogation of nuclear materials , and radiation damage assessment . His recent publications emphasize semi-empirical modeling of atomic interactions and advanced detection techniques for nuclear applications. He has contributed to understanding vacancy transfer probabilities , X-ray fluorescence cross-sections , and water detection in nuclear environments . His work supports nuclear security, power plant safety, and space weather monitoring. Scientific awards : None explicitly mentioned in the text. Research groups : Involved in Nuclear Space Weather initiatives.
