Prof. Olga Sorkine Hornung is a Full Professor of Computer Science at ETH Zürich, leading the Interactive Geometry Lab. She holds a BSc and PhD from Tel Aviv University (2000 and 2006) and conducted postdoctoral research at Technical University Berlin. Her research focuses on computer graphics, geometric modeling, and geometry processing, with applications in shape editing, digital fabrication, and animation. She has received numerous accolades, including the ACM Fellowship (2020), ERC Consolidator Grant (2020), and the Golden Owl Teaching Award (2021). Her work bridges theoretical foundations and practical algorithms, addressing challenges in parameterization, surface compression, and interactive design tools. Her research interests span: Computer Graphics & Visualization Geometric Modeling & Processing 3D Content Creation & Digital Fabrication Garment Design & Simulation Human Motion Analysis & Animation Awards and grants include: 2024: Best Paper Honorable Mention (EUROGRAPHICS) 2023: Member of Swiss Academy of Engineering Sciences (SATW) 2020: ERC Consolidator Grant 2017: Rössler Prize (ETH Zurich) Her lab focuses on developing novel methods for interactive geometry processing, with recent advancements in garment modeling (e.g., AIpparel, Rags2Riches) and motion retargeting systems like WalkTheDog. She actively collaborates on interdisciplinary projects, including biomedical applications and sustainable fashion technology.
Marc Olano is an Associate Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC), and serves as the Associate Dean of Academic Programs and Learning in the College of Engineering and Information Technology. He leads the Computer Science Game Development Track and co-directs the VANGOGH lab. His research focuses on interactive 3D computer graphics, programmable shading, graphics hardware, and surface appearance modeling, with contributions to foundational graphics technologies like procedural shading and normal mapping. Research Interests: Olano’s work spans real-time rendering, GPU algorithms, texture compression, and procedural shading. He has pioneered techniques such as LEAN mapping and variable bitrate texture compression, significantly impacting game development and real-time graphics. His research often explores the intersection of hardware capabilities and algorithmic innovation, with applications in medical visualization, visualization of scientific data, and haptic interaction. Key Contributions: Olano’s accomplishments include pioneering procedural shading on graphics hardware, developing homogeneous rendering techniques, and advancing normal mapping. His work on GPU-based curvature estimation and BT volumes for volume rendering exemplifies his focus on leveraging GPU parallelism for real-time visualization challenges. He has also contributed to standards in shading languages and GPU programming. Teaching & Mentorship: Olano teaches courses in computer graphics, game development, and advanced computer architecture. He mentors students in independent studies and has advised numerous MS theses exploring topics like GPU random number generation, volume rendering, and soft shadow algorithms. His students’ work often bridges theoretical research and practical GPU implementations. Labs & Projects: The VANGOGH lab under his co-direction focuses on advanced visualization and graphics research, including real-time rendering techniques, GPU algorithms, and interactive data visualization. His research collaborations span industry partners like Firaxis Games, contributing to titles such as Civilization V through texture compression innovations.
Ian J. Rhile is a Professor of Chemistry and Biochemistry and currently serves as the Department Chair at Albright College. He holds a B.S. from Ursinus College and an M.S. and Ph.D. from Cornell University. His postdoctoral work at the University of Washington preceded his appointment at Albright in 2005. Dr. Rhile’s research focuses on physical and mechanistic organic chemistry, particularly atomic orbitals and proton-coupled electron transfer. His lab investigates base-appended radical cations and their role in hydrogen abstraction from phenols, exploring how molecular structural variations influence reaction kinetics and thermodynamics. He is also dedicated to improving organic chemistry laboratory education through innovative techniques like parametric equations for orbital visualization. Dr. Rhile has received notable recognition, including the 2011 Dr. Henry P. and M. Paige Laughlin Annual Distinguished Faculty Award for Teaching and the 2013 Albright PRIDE Award. He has contributed to institutional committees such as the Middle States Reaccreditation Steering Committee and chaired the Educational Policy Council and Advisory Committee on Rank and Tenure. His service roles include faculty advisor to the Student Government Association and Pride+, underscoring his commitment to both academic excellence and campus community building. Dr. Rhile teaches a range of courses, including CHE102 (Science of Food and Cooking), CHE105/106 (General Analytical Chemistry), and CHE411/470 (Advanced Organic Chemistry and Chemical Education). He has also been involved in grant-funded research through the American Chemical Society-Petroleum Research Fund (2009-2012). His work in the Rhile lab emphasizes experimental and theoretical studies of molecular systems, with a focus on understanding fundamental chemical processes. This aligns with Albright’s mission to provide hands-on research opportunities for students, which he actively fosters through his teaching and mentorship.
Joe D. Warren is a Professor of Computer Science at Rice University, where he has served since 1986. His research focuses on computer graphics, geometric modeling, and computational geometry, with notable contributions to subdivision surfaces, as detailed in his book Subdivision Methods for Geometric Design . He also explores bioinformatics applications, including 3D modeling of mouse brain gene expression and lung motion analysis from 4D CT scans. Additionally, Warren teaches courses in computer game design and introductory programming, co-developing award-winning Coursera specializations. He earned his Ph.D. from Cornell University and previously served as Department Chair (2008-2013). Education: B.Sc. (Rice University, 1983), Ph.D. (Cornell University, 1986) Research Collaborators: Baylor College of Medicine, MD Anderson Cancer Center, Texas A&M Teaching: COMP460 (Game Design), COMP110 (Introductory Computing) His work on the GRACE tool (Graphical Ruler and Compass Editor) won the 1998 Quest for Java award. He has advised PhD students now at Washington University and Texas A&M. Current projects include game prototyping with Pi Studios and lung motion modeling for medical diagnostics.
Rook Bridson is an Adjunct Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Imager and SCL labs. He holds a PhD from Stanford University (2003) and degrees from the University of Waterloo (MMATH '99, BMATH '98). His research focuses on fluid simulation, physical effects in computer graphics, and computational physics, with applications in visual effects and animation. Bridson has contributed to industry through co-founding Exotic Matter AB, creators of the Naiad fluid simulation software acquired by Autodesk. He has been recognized with an Oscar Technical Achievement Award and multiple teaching awards at UBC. Education: PhD in Computer Science, Stanford University, 2003 Master of Mathematics (MMATH), University of Waterloo, 1999 Bachelor of Mathematics (BMATH), University of Waterloo, 1998 Research Interests: Bridson’s work spans fluid dynamics, computational physics, and their applications in film and animation. His research emphasizes realistic simulation techniques, including fluid animation with explicit surface meshes, particle-based methods, and numerical algorithms for handling complex physical phenomena. He has developed influential tools like Naiad, used in major films such as Avatar and Harry Potter . Industry Contributions: Co-founder of Exotic Matter AB (developer of Naiad) Senior Principal Research Scientist at Autodesk Contributions to studios like Weta Digital and Double Negative VFX Grants & Awards: Oscar Technical Achievement Award (Academy of Motion Picture Arts and Sciences) 2012 and 2008 CS Department Teaching Awards (UBC) Best Technical Paper Award (ACM SIGGRAPH/Eurographics Symposium on Computer Animation) Labs & Teams: Active in UBC’s Imager Lab and SCL Lab, focusing on fluid simulation, geometric modeling, and real-time animation techniques. Collaborates with industry partners on advancing visual effects technology.
Sidharth Kumar is an Associate Professor in the Department of Computer Science at the University of Illinois at Chicago (UIC), where he leads research in high-performance computing and data visualization. He joined UIC in August 2023 after previously working at the University of Alabama at Birmingham. His research focuses on developing scalable algorithms and data structures for data-intensive applications, intersecting HPC, visualization, databases, and machine learning. Education: Ph.D. in Computing (2016) from the University of Utah's Scientific Computing and Imaging Institute, advised by Valerio Pascucci. Bachelor of Technology in Information and Communication Technology (2009) from DAIICT, Gandhinagar, India. Research Interests: Dr. Kumar's work centers on parallel I/O, GPU acceleration, big data processing, and scientific visualization. His projects include: 1) Exascale data management systems, 2) GPU-accelerated web visualization, 3) Declarative analytics frameworks, and 4) Topology-driven analysis for neuroscience and virology. He develops solutions for memory-constrained environments and heterogeneous systems. Publication Trends: Recent works (2023-2025) demonstrate strong focus on GPU-accelerated databases (Datalog optimizations), parallel communication algorithms (all-to-all collectives), memory-efficient visualization techniques (speculative raycasting), and applied topological analysis (brain networks, virus taxonomy). His publications consistently appear in top-tier HPC and visualization venues. Awards & Honors: Best Paper Awards: IEEE HiPC (2019), ISC Hans Meuer (2020), LDAV (2023) Honorable Mention: PacificVis (2025) Poster Awards: SC23 Finalist, HiPC SRS (2021) NSF EPSCoR Research Fellow (2022) Grants & Advising: NSF PPoSS Large: Declarative Analytics ($960K PI) NSF SHF: Scalable I/O Runtime ($300K PI) NSF EPSCoR: Relational Algebra ($265K PI) Advises 6 PhD students in HPC and visualization research Lab & Service: Leads a research team working on exascale computing challenges. Serves on technical committees for SC, ISC, IPDPS, and HiPC conferences. Teaches courses in Database Systems, Algorithms, and Data Visualization.
Mengyu (Rachel) Chu is a tenure-track Assistant Professor at the School of Intelligence Science and Technology, Peking University, affiliated with the Visual Computing and Learning Lab. Previously, she was a Lise Meitner Postdoctoral Research Fellow at the Max Planck Institute for Informatics (2020–2022), and completed her Ph.D. in Computer Science at Technical University of Munich (2014–2020). She holds a B.Eng. in Software Engineering from Southeast University (2007–2011) and an M.Eng. in Computer Science from Zhejiang University (2011–2014). Her research focuses on Physics-Enhanced Deep Learning , combining deep learning with physical simulations to enhance fluid dynamics modeling, video synthesis, and neural network training. Key areas include fluid reconstruction, manipulation, synthesis, and temporally coherent video generation. Her work bridges physics-based principles with modern AI techniques for realistic simulations and generative models. Notable contributions include Physics Informed Neural Fields for sparse data reconstruction (SIGGRAPH 2022), Learning Meaningful Controls for Fluids (SIGGRAPH 2021), and TempoGAN for fluid flow super-resolution (SIGGRAPH 2018). Her research emphasizes real-world applications in graphics, visualization, and computational physics. She has been recognized with the Lise Meitner Postdoctoral Fellowship (2020) and Summa Cum Laude distinction for her Ph.D. (2020). Her work spans academic publications, patents, and open-source projects, with collaborations across institutions like TU Munich and Max Planck Institute.
Alexandre Shvartsburg is a Professor at Wichita State University, specializing in advancing ion mobility spectrometry (IMS) technologies, particularly field asymmetric waveform ion mobility spectrometry (FAIMS). His research focuses on novel nonlinear approaches for separating ions in gases, enabling unprecedented analyses of modified peptides, protein conformers, and lipid isomers. Collaborations with instrument companies drive hardware improvements, while computational methods like the Scattering on Electron Density Isosurfaces (SEDI) paradigm enhance ion mobility calculations. His lab utilizes custom planar FAIMS systems achieving record resolution (~500 for multiply charged ions), enabling separations once deemed impossible. Research also emphasizes optimizing IMS methods and extracting structural insights from ion cross-section data. Contact: alexandre.shvartsburg@wichita.edu | Office: MC 318
Adriano Lopes is an Invited Assistant Professor at Iscte - Instituto Universitário de Lisboa, affiliated with the Department of Information Science and Technology within the School of Technologies and Architecture. He is also an Associate Researcher at ISTAR-IUL, the university's research center in Information Sciences, Technologies, and Architecture. His academic work spans software systems engineering, visual analytics, and big data technologies. PhD in Computer Science – University of Leeds, UK (1999) Master’s in Computer Science – University of Coimbra (1993) Bachelor’s in Electrical Engineering (Computer Science branch) – University of Coimbra (1986) Postgraduate studies in Financial Analysis – Technical University of Lisbon, ISEG (2013) Adriano Lopes’ research focuses on visual analytics, big data, software engineering, and computer graphics, with a strong emphasis on data visualization and its applications in domains such as smart tourism and urban planning. His work integrates human-centric design with advanced computational techniques to support decision-making in complex systems. His recent publications highlight a shift toward applied research in digital transformation for sustainable tourism, particularly through spatiotemporal visualization of tourism crowding and carrying capacity modeling. These works demonstrate a consistent trend in leveraging data-driven platforms for real-world societal challenges, especially in the context of post-pandemic recovery and sustainable development. Adriano has supervised numerous Master’s students at both Iscte and Universidade Nova de Lisboa, with thesis topics covering sentiment analysis, GPU-based rendering, anomaly detection, and tourism flow forecasting. He has participated in EU-funded research projects such as RESETTING, which aims to relaunch sustainable tourism models through digitalization. His academic service includes organizing roles in major visualization conferences like EUROVIS 2006 and the Eurographics UK Conference. He has been actively involved in research labs and teams including ISTAR-IUL and CITI (research center at FCT/UNL), contributing to interdisciplinary projects that bridge computer science with architecture, telecommunications, and tourism. His work reflects a strong commitment to collaborative, applied research with societal impact.
Vincent Danjean is an associate professor at Grenoble Alpes University , specializing in parallel computing, high-performance computing, and bioinformatics. He earned his PhD in 2004 from École Normale Supérieure de Lyon under the supervision of Raymond Namyst. Research Interests: Vincent's work spans several critical areas in computational science: Parallel and Distributed Systems: Focus on task-based parallelism and hybrid cluster architectures. Performance Analysis: Development of visual frameworks for analyzing parallel applications. Bioinformatics: Application of computational methods to genetic and genomic data analysis. GPU Computing: Efficient scheduling and work stealing strategies for multi-GPU systems. Reproducible Research: Workflows using Git and Org-mode for scientific transparency. Publication Trends: His publications demonstrate a consistent focus on advancing parallel computing techniques, with significant contributions to GPU scheduling, cache-efficient algorithms, and visualization tools. Recent work includes interdisciplinary applications in genomics and cybersecurity protocols. Contact: vincent.danjean@imag.fr
Antonio Chica is an Associate Professor at the Department of Computer Science, Universitat Politècnica de Catalunya (UPC), specializing in geometry processing, real-time rendering, and virtual reality applications. His research focuses on 3D reconstruction, procedural landscape generation, and LiDAR data optimization. Teaching at Terrassa School of Engineering and Barcelona School of Informatics Member of the Modeling, Visualization, Interaction and Virtual Reality Group Key research areas include: Geometry processing techniques for signed distance fields Procedural generation of 3D landscapes and vegetation Game development frameworks and VR training systems Efficient algorithms for massive point cloud rendering His recent publications emphasize Bayesian reconstruction methods, adaptive SDF approximations, and optimized VR training tools. He actively collaborates on LiDAR data calibration, terrain modeling, and cultural heritage visualization projects. Antonio Chica's work integrates advanced graphics algorithms with practical applications in urban modeling, medical training, and historical preservation. He develops open-source tools like MeshPipe to simplify geometry processing workflows.
Joshua A. Levine is a researcher in the Department of Computer Science at the University of Arizona, focusing on topological data analysis, scientific visualization, and computational geometry. His work bridges computer graphics, data science, and mathematical methods. Key Research Areas: Topological data analysis, visualization of scientific simulations, mesh processing algorithms, and computational methods for scalar fields. Recent Trends: 2025 publications highlight discrete vector field construction and topological simplification solvers, building on 2024 work in open-access repositories. Earlier work includes particle system simulations (2022), neural representations for volumetric data (2021), and foundational contributions to Delaunay meshing (2008–2012). Collaborations: Regularly works with Julien Tierny, Matthew Berger, Robert M. Kirby, and Valerio Pascucci.
Pere Brunet is a Full Professor in Computer Science at the Polytechnic University of Catalonia (UPC) in Barcelona, Spain, where he heads the UPC Research Group in Modeling, Visualization and Computer Graphics. He served as Vice President for Research at UPC between 1988 and 1992 and currently serves as Vice President of the Royal Academy of Engineering in Spain. He pioneered Computer Graphics research in Spain starting in 1979 and promoted the creation of the Virtual Reality Center in Barcelona, where he serves as scientific head. Industrial Engineer (1971) from Barcelona School of Engineers (UPC) Doctor in Industrial Engineering (1976) from UPC with special outstanding recognition Professor Brunet's research focuses on geometric computer-assisted design, hierarchical geometric representations, and virtual reality. His group works on complex research projects involving Virtual Reality and very complex models across diverse fields including geo-modeling, industrial design, cultural heritage, and medical applications. His work emphasizes multi-resolution geometric models, real-time navigation through complex virtual environments, and implicit interaction in VR systems. The group maintains strong international cooperation and industry-based research engagement. His publication record spans several decades with significant contributions to Computer-Aided Geometric Design, volume visualization, and octree representations. His recent work focuses on massive data processing, urban modeling, cultural heritage visualization, and efficient rendering techniques for complex environments. Member of the Royal Academy of Engineering in Spain (currently Vice President) Corresponding member of the Academy of Engineering of Portugal Member of the CAETS Council and EuroCASE Executive Committee Recipient of the Distinguished Career Award of the Eurographics Association (2008) Recipient of the XI Catalan Foundation Prize for research (2001) Recipient of the Narcís Monturiol medal from the Catalonia Government Recipient of the Silver medal from the Polytechnic University of Catalonia Professor Brunet has served on editorial boards of prestigious journals including Computer-Aided Design, Computer-Aided Geometric Design, IEEE Transactions on Visualization and Computer Graphics, and Computers & Graphics. He was Chairman of the Eurographics Association (2001-2002) and has been actively involved in international scientific organizations like Eurographics, IFIP, and Siggraph. He has contributed to numerous edited books and special journal issues in his field and has served as scientific consultant for universities, international associations, and research funding agencies. He leads the UPC Research Group in Modeling, Visualization and Computer Graphics, which has been instrumental in developing Spain's computer graphics research landscape. The group maintains strong connections with industry and international research communities, focusing on practical applications of their theoretical work across multiple domains.
Laura J. Juszczak is an Associate Professor in the Department of Chemistry and Biochemistry at Brooklyn College, CUNY. She specializes in protein photophysics , particularly focusing on tryptophan fluorescence , UV resonance Raman spectroscopy , and cation-π interactions . Her work bridges biochemistry , physical chemistry , and molecular modeling to elucidate noncovalent interactions in proteins. Education: B.A. in Art History, Wellesley College (1976) M.S. in Art Conservation, University of Delaware (1979) M.S. in Chemistry, New York University (1986) Ph.D. in Physical Chemistry, New York University (1993) Postdoc in Laser Spectroscopy of Proteins, Albert Einstein College of Medicine (1999) Her research interests center on: Understanding tryptophan's variable fluorescence quantum yield in proteins via dipeptide models Linking electron density isosurfaces to aromaticity and photophysical properties Characterizing higher-order cation-π interactions in biological systems (e.g., antimicrobial peptides, epigenetic binding) Recent publications highlight her lab's work on tryptophan dipeptides , aromatic boxes , and visible spectroscopy in non-metallic systems. Grants include NIH and NSF funding for instrumentation and interdisciplinary research . She mentors undergraduate and international graduate students , and has been active in pedagogical innovation , notably revising CHEM 1007 to focus on food chemistry and sustainability . Awards: NSF Instrumentation Award (2021) NIH SC3 Grant (2013-2017) PSC-CUNY Research Awards (2013, 2008)
Frederic Cordier is an Associate Professor (HDR) at the University of Haute-Alsace, affiliated with the LMIA department within the Faculty of Science and Technology (FST). His research focuses on computer graphics, 3D modeling, and geometric algorithms. He holds a PhD in Computer Science from the University of Geneva (2004) and advanced degrees from the University of Lyon. His work spans sketch-based interfaces, cloth simulation, medical modeling, and texture mapping. Key projects include inferring mirror symmetry from sketches, compressing 3D mesh sequences, and reconstructing organ models from medical data. His contributions to real-time cloth simulation and dressed virtual humans have been influential in interactive systems and virtual garment design. Publications emphasize geometric algorithms for shape reconstruction, symmetry detection, and medical applications. He has held visiting roles at KAIST (South Korea) and conducted postdoctoral research in computational geometry. Teaching includes graduate-level computer science courses in Geneva and Haute-Alsace.
