جست‌وجوی استاد و پژوهشگر

• Data Visualization
• Human-Computer Interaction
• Big Data Analytics
• +۱۳ مورد دیگر

Huamin Qu is a Chair Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology (HKUST). He serves as the Founding Dean of the Academy of Interdisciplinary Studies (AIS), Founding Head of the Division of Emerging Interdisciplinary Areas (EMIA), and was the Founding Acting Head of Computational Media and Arts (CMA) at HKUST(GZ). Qu directs the VisLab and coordinates the Human-Computer Interaction (HCI) group. He obtained his BS in Mathematics from Xi'an Jiaotong University and MS/PhD in Computer Science from Stony Brook University. Qu's research integrates Data Visualization , Human-Computer Interaction , and Human-Centered AI , with applications in urban informatics, social networks, and explainable AI. His work focuses on developing interactive systems for big data analytics, visual storytelling, and AI-driven decision support. Research extends to multimodal communication, fintech, and augmented reality applications. His publications emphasize visual analytics for complex datasets (mobility, social media, financial), interaction techniques for immersive environments, and AI-enhanced visualization tools. Recent works explore explainable AI interfaces and large-scale data communication frameworks. IEEE Visualization Academy (2020) IEEE VGTC Technical Achievement Award AI 2000 Most Influential Scholar (2019, 2023, 2024) 21 Best Paper/Honorable Mention awards IBM Faculty Award (2009) APICTA Merit Award (2015) Yelp Dataset Grand Prize (2018) Qu has advised 48 PhD graduates (21 now faculty at institutions like UC Davis, University of Minnesota, Texas A&M) and 30 MPhil students. He secured major grants including RGC theme-based projects (digital citizenship, air pollution), UGC AoE (slope safety), and China's 973 Program. As VisLab director, he leads 20+ researchers in visualization/HCI projects adopted by Microsoft, IBM, Huawei, and Tencent.

Wolfgang Kunzمشاهده پروفایل

استاد

• Hardware Safety and Security
• Formal Hardware Verification
• Embedded Computing Systems
• +۵ مورد دیگر

Wolfgang Kunz is a Full Professor (C4, W3) and Chair of Electronic Design Automation at the Technische Universität Kaiserslautern since 2001. His academic career spans multiple prestigious institutions, including Goethe-University Frankfurt/Main and the University of Massachusetts, Amherst. He has held leadership roles such as Dean (2005-2007) and Vice-Dean (2007-2009) at TU Kaiserslautern. Habilitation (Dr. rer. nat. habil.), Computer Science, University of Potsdam (1996) Doctoral degree (Dr.-Ing.), Electrical Engineering, University of Hannover (1992) Dipl.-Ing. degree, Karlsruhe Institute of Technology (1989) His research focuses on hardware verification, security, and optimization, particularly in embedded systems and processors. His work on formal verification methods has been commercialized by companies like Synopsys, Mentor Graphics, and Siemens EDA. His 2016-2021 publications address critical security issues such as Spectre/Meltdown and introduce innovative verification frameworks adopted by industry leaders like Infineon and OneSpin Solutions. Scientific awards include the IEEE Fellow (2006), German IT Society Award (2005), and TU Kaiserslautern Distinguished Teaching Award (2016). He has served on editorial boards of major journals and coordinated the Erasmus Mundus European Master Program in Embedded Computing Systems since 2010. Key students: Jörg Bormann, Raik Brinkmann, Tobias Ludwig Collaborations: Siemens EDA, Infineon, AbsInt, Intel SCAP Spin-offs: LUBIS EDA, OneSpin Solutions

• Data Visualization
• Visual Data Analysis
• Data Science
• +۳ مورد دیگر

Univ.-Prof. Torsten Möller, PhD is a Professor at the University of Vienna and serves as Head of the Research Group Visualization and Data Analysis and Head of the Research Network Data Science. His work spans data visualization, visual analytics, and human-computer interaction, with a focus on biomedical, environmental, and societal data applications. Academic rank: Professor Research group: Visualization and Data Analysis Network: Data Science Email: torsten.moeller@univie.ac.at Research interests include: Visual data analysis for complex systems Interdisciplinary applications in climate science and medicine Human-computer interaction in data exploration Image processing and computer graphics Recent publication trends show expertise in: Visualizing climate change and pandemic data Multi-volumetric and network analysis Algorithmic transparency and user-centered design Interdisciplinary collaborations (e.g., astrophysics, medical imaging) Statistical and uncertainty visualization Design frameworks for visualization recommendation Teaching includes courses in: Computer graphics and visualization Image processing and analysis Human-computer interaction Data analysis projects Doctoral research seminars

• Computer Vision
• Autonomous Driving
• Robotics
• +۷ مورد دیگر

Dominik Schörkhuber is a PreDoc Researcher at the Vienna University of Technology (TU Wien) in the Computer Vision department. With a background in Informatics (BSc, Dipl.-Ing.), he focuses on computer vision applications for autonomous driving, robotics, and human-machine interaction. His work spans driver action recognition, pedestrian prediction, and adaptive lighting systems. Current projects: Empathic Vehicle (2024–2026), SyntheticCabin (2021–2025), SmartProtect (2020–2025) Research themes: Video transformers, synthetic data transfer learning, multi-task learning, and sensor-lighting integration Specializes in 3D sensing, nighttime driving analysis, and mobile video creation tools

• Image Science
• Digital and Media Art Research
• Art History and its Media
• +۶ مورد دیگر

Oliver Grau is a Chair Professor for Image Science and a leading figure in Media Art research, affiliated with Hong Kong Baptist University (Academy of Visual Arts, Distinguished Fellow since 2023) and Danube University Krems (Chair Professor for Image Science from 2005–2022). He founded the Archive for Digital Art (ADA) and the international MediaArtHistories Conference Series , with key roles at institutions across Germany, Austria, and Australia. His work bridges art, science, and technology, focusing on immersive images, digital heritage, and emotion research. Key Positions: Director of ADA (since 2000), Founding Director of MediaArtHistories Conference Series (since 2005), PI for high-resolution digitization of the Goettweig Graphic Print Collection (2005–2017). Research Grants: Funded by DFG, Austrian Science Fund, Australian Research Council, VW Foundation (total 8.3 Mio EUR), and Erasmus+ Joint Master program (5.4 Mio EUR). Research Interests: Grau’s scholarship spans the history of media art, telepresence, artificial life, emotion research, and digital humanities. His work emphasizes the evolution of immersive visual experiences from historical art forms to digital media, integrating theoretical and practical approaches. Article Trends: His recent publications focus on digital art’s sociopolitical dimensions, archiving challenges in the digital era, and cross-disciplinary methodologies. Themes include media art conservation, web-based tools for digital humanities, and the intersection of artistic expression with contemporary global issues like climate change and surveillance. Scientific Awards: Distinguished Fellow at Hong Kong Baptist University (2023) Science Award of Lower Austria (2019) Honorary Doctorate from University of Oradea (2014) Invitations to G-20 summit, Olympic Games, and international symposia Labs & Teams: He leads the Archive for Digital Art, managing a global team of 28 staff, and co-founded the Erasmus+ Joint Master in Media Arts Cultures. His projects emphasize collaborative archiving tools (e.g., Web 2.0/3.0 archives) and large-scale digitization initiatives.

Alan Bovikمشاهده پروفایل

استاد

• Image quality
• Video compression
• Streaming video
• +۷ مورد دیگر

Alan Bovik is the Cockrell Family Regents Endowed Chair Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin's Cockrell School of Engineering. He also holds positions at The Institute for Neurosciences and serves as Director of the Laboratory for Image and Video Engineering (LIVE). With a career spanning over three decades at UT Austin, he has progressed from Assistant Professor (1984-1988) to Associate Professor (1988-1994) to his current position as Full Professor (1994-present). Dr. Bovik received his Ph.D. in Electrical and Computer Engineering in 1984 from the University of Illinois, Urbana-Champaign. Professor Bovik's research focuses on image and video quality assessment, visual perception, and digital media processing. He is renowned for developing groundbreaking algorithms including the Structural Similarity (SSIM) index, Visual Information Fidelity (VIF), and various blind quality assessment models like BRISQUE and NIQE. His work bridges engineering and neuroscience, creating perception-based models that optimize visual media delivery while reducing bandwidth consumption. These innovations have had profound industry impact, with his algorithms processing a significant proportion of global internet video traffic. His recent publications demonstrate continued leadership in perceptual quality assessment, with increasing focus on AI-generated content, high dynamic range (HDR) video, and novel applications in medical imaging. The research shows a clear trajectory toward more sophisticated, neural network-based quality metrics that better align with human visual perception across diverse content types. Professor Bovik has received numerous prestigious awards recognizing his contributions to the field: John Fritz Medal (2024) IEEE Edison Medal (2022) IAMB BaM Award (2022) Elected to the United States National Academy of Engineering (2022) Technology and Engineering Emmy Award (2021) IEEE Fourier Award for Signal Processing (2019) Progress Medal from The Royal Photographic Society (2019) Named Honorary Fellow of The Royal Photographic Society (2019) Primetime Emmy Award (2015) Edwin H. Land Medal from The Optical Society (2017) As Director of the Laboratory for Image and Video Engineering (LIVE), Professor Bovik has secured substantial research funding from organizations including the National Science Foundation and the National Institute for Standards and Technologies. His lab has produced numerous influential datasets including the LIVE Image and Video Quality Databases. He has mentored many successful students who have gone on to make significant contributions in academia and industry, though specific student names are not provided in the source materials. The Laboratory for Image and Video Engineering (LIVE) under Professor Bovik's direction has become a world-renowned center for research in perceptual image and video quality. The lab maintains close collaborations with major technology companies including Netflix, Amazon, and YouTube, ensuring that research has direct practical applications. LIVE has developed numerous influential tools and databases that are widely used in both academic research and industrial applications worldwide.

Moncef Gabboujمشاهده پروفایل

استاد

• Machine learning
• Artificial intelligence
• Signal processing
• +۹ مورد دیگر

Professor Moncef Gabbouj is a distinguished academic and researcher currently serving as Professor of Signal Processing at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University, Finland. Previously, he held the same position at Tampere University of Technology before the merger in 2019. He has also held visiting professorships at prestigious institutions including Hong Kong University of Technology and Science, University of Southern California, and Purdue University. Ph.D. and MSc. in Electrical Engineering from Purdue University, USA (1989 and 1986) B.Sc. in Electrical Engineering from Oklahoma State University, USA (1985) Prof. Gabbouj's research spans multiple domains within signal and image processing, with a strong focus on machine learning applications. His primary research interests include artificial intelligence, machine learning, Big Data analytics, multimedia content-based analysis, indexing and retrieval, nonlinear signal and image processing, voice conversion, and video processing and coding. His work bridges theoretical advancements with practical applications across various industries, particularly in multimedia communications and biomedical applications. His extensive publication record demonstrates a clear evolution from traditional signal processing techniques toward more sophisticated machine learning and deep learning approaches. Recent work shows increasing focus on convolutional neural networks for various applications including ECG classification, video processing, financial time-series analysis, and image recognition tasks, reflecting the broader trend in the field toward deep learning methodologies while maintaining strong foundations in signal processing theory. IEEE Fellow (2011) Member, Finnish Academy of Science and Letters (2014) Knight, First Class, of the Order of the White Rose of Finland (2006) Nokia Foundation Recognition Award (2005) Nokia Foundation Visiting Professor Award (2012) Finnish Cultural Foundation for Art and Science Award (2017) TUT Foundation Grand Award (2015) Prof. Gabbouj has supervised 64 doctoral and 72 Master's theses, demonstrating his significant contribution to academic mentoring. His research has been supported by substantial funding, including research grants totaling 8.5 million Euro (2001-2015). He has served as Academy of Finland Professor during 2011-2015 and has been involved in numerous EU research projects including Horizon, ESPRIT, HCM, IST, COST, Tempus and Erasmus programs. As Editor, Guest Editor or member of the Editorial Board of 6 international scientific journals, he has significantly influenced the academic discourse in his field. He leads the Signal Analysis and Machine Intelligence (SAMI) research group at Tampere University and serves as the Finland Site Director of the NSF IUCRC funded Center for Visual and Decision Informatics. His research unit focuses on applying advanced machine learning techniques to solve complex problems in signal processing, computer vision, and multimedia analytics, with applications ranging from healthcare to multimedia communications and financial analysis.

Marc Pollefeysمشاهده پروفایل

استاد

• 3D Computer Vision
• Robotics
• Machine Learning
• +۵ مورد دیگر

Marc Pollefeys is a Full Professor of Computer Science at ETH Zurich and Director of the Microsoft Mixed Reality and AI Zurich Lab. He has held roles such as Visiting Professor at Stanford University (2007) and Assistant/Associate Professor at UNC-Chapel Hill (2002–2009). His research focuses on 3D computer vision, robotics, machine learning, and augmented reality. Education: PhD in Computer Science from KU Leuven (1999), followed by postdoctoral research there until 2002. He transitioned to academic roles at UNC-Chapel Hill before joining ETH Zurich in 2007. Research interests include 3D reconstruction, visual localization, SLAM, and applications in archaeology, urban modeling, and robotics. Notable projects include real-time 3D scanning, city-scale reconstruction, and autonomous vision-based drones. Key awards include ACM Fellow (2022), IEEE Fellow (2012), and ERC Starting Grant (2008). He advises numerous PhD students and collaborates with institutions like Google and Microsoft. Labs and teams: Leads the Computer Vision and Geometry (CVG) lab at ETH Zurich and directs the Microsoft Mixed Reality and AI Lab. His work bridges academia and industry, focusing on perception for mixed reality and autonomous systems.

Johannes Brandstetterمشاهده پروفایل

دانشیار

• Machine Learning
• Deep Learning
• Geometric Deep Learning
• +۵ مورد دیگر

Johannes Brandstetter is an Associate Professor at the Institute for Machine Learning at Johannes Kepler University Linz (JKU) where he leads the "AI for data-driven simulations" research group. He is also Co-founder and Chief Scientist at Emmi AI, bridging academic research with industrial applications in AI-driven physics simulation. Brandstetter earned his PhD after working at CERN's CMS experiment on Higgs boson physics. In 2018, he transitioned to machine learning, joining Sepp Hochreiter's research group in Linz. From 2021-2023, he worked at the Amsterdam Machine Learning Lab under Max Welling and Microsoft Research, developing expertise in Geometric Deep Learning and neural surrogates for partial differential equations. He returned to JKU in October 2023 to establish his own research group. His research spans Machine Learning, Deep Learning, and Physics-Informed Machine Learning with focus areas including Neural PDE solvers, Computational Fluid Dynamics, and Climate Modeling. Brandstetter believes AI is poised to revolutionize industrial-scale simulations, potentially saving thousands of compute hours across engineering domains. His work integrates computer vision, numerical simulation, and engineering components to advance data-driven approaches. Recent publications reveal a strong trend toward foundation models for scientific applications, particularly in atmospheric modeling (Aurora), geometric deep learning, and neural surrogates for complex physical systems. His interdisciplinary work spans computer vision, climate science, computational physics, and engineering, demonstrating the versatility of his research approach. Principal Investigator for "AlKa-DL: Alpine karst spring discharge prediction" (FWF-funded, 2024-2027) Principal Investigator for Cluster of Excellence "Bilateral Artificial Intelligence" (FWF-funded, 2024-2029) Co-PI for "Fast, efficient and flexible CFD simulation through generative AI" (FFG-funded, 2025-2026) As an educator and researcher, Brandstetter actively engages with the scientific community through invited talks at major conferences including presentations on "Closing the Gap Between Scientific Foundation Models and Real-World Applications" (March 2025) and "Scientific Machine Learning for Science and Engineering" (February 2025).

Sylvain Lefebvreمشاهده پروفایل

پژوهشگر

• Computer Graphics
• Texture Synthesis
• Additive Manufacturing
• +۴ مورد دیگر

Sylvain Lefebvre is a permanent researcher at INRIA (Institut National de Recherche en Informatique et en Automatique) in France, where he leads the MFX research team since 2018. Previously, he was part of the ALICE group at INRIA Nancy (2009-2018) and the REVES team in Sophia Antipolis (2006-2009). His career includes a postdoctoral position at Microsoft Research Seattle (2005) following his PhD at INRIA Rhones-Alpes under Fabrice Neyret. His educational background includes a PhD in Computer Graphics from Université Joseph Fourier (Grenoble) in 2005, preceded by a Master in Computer Graphics from INP Grenoble in 2001. His habilitation thesis focused on Runtime Texture Synthesis. Lefebvre's research centers on simplifying content creation for highly detailed patterns, structures, and shapes with applications spanning Computer Graphics to additive manufacturing. He develops fast, controllable by-example synthesis approaches that generate content while enforcing user-specified constraints. His work addresses computational challenges through novel data structures and algorithms optimized for GPUs and FPGAs, including his Silice programming language. The ERC-funded ShapeForge project (2012-2017) advanced shape generation for 3D printing, leading to the IceSL software for digital modeling and fabrication. Analysis of his 15 most recent publications reveals a strong focus on additive manufacturing optimization, with recurring themes in structural integrity, material efficiency, and geometric algorithms. His work bridges computer graphics theory with practical fabrication constraints, particularly in microstructure design, slicing techniques, and mechanical metamaterials. The interdisciplinary nature spans computer science, materials engineering, and robotics. EUROGRAPHICS Young Researcher Award (2010) ERC Starting Grant for ShapeForge project (2012) Lefebvre has advised over 25 PhD students and interns including Marco Freire, Thibault Tricard, and Jimmy Etienne. His ShapeForge project received significant ERC funding, supporting research in computational fabrication. He serves on numerous program committees including SIGGRAPH, Eurographics, and SIGGRAPH Asia, reflecting his leadership in the computer graphics community. As leader of the MFX team since 2018, Lefebvre directs research in computational fabrication, focusing on IceSL software development for 3D printing workflows. The team integrates computer graphics techniques with manufacturing constraints, developing tools that simplify complex object design and fabrication while addressing real-world challenges in material usage and structural integrity.

Ivan Violaمشاهده پروفایل

دانشیار

• Visualization
• Computer Graphics
• Biological Visualization
• +۳ مورد دیگر

Ivan Viola is an Associate Professor at the Institute of Computer Graphics and Algorithms, part of the Faculty of Informatics at TU Wien, Austria. He holds a leave of absence until December 2024 while also being affiliated with King Abdullah University of Science and Technology (KAUST) as an Associate Professor funded by the Vienna Research Groups program. His research focuses on visualization techniques in medicine, biological sciences, and earth sciences, with a specialty in illustrative visualization and DNA-nanotechnology applications. Viola has contributed over 100 scientific works and serves as a reviewer and panelist for major conferences in computer graphics and visualization. Education: M.Sc. (2002) and Ph.D. (2005) in Computer Graphics from TU Wien. Postdoctoral research at the University of Bergen (2006-2011), where he became Full Professor before returning to TU Wien. Research Interests: Whole-cell visualization Molecular modeling Interactive 3D environments Biomedical visualization Data-driven colormap techniques Awards: IEEE VIS 2017 Best Paper Honorable Mention, 'Best Overall Concept' for CellView, and multiple visualization awards. Active in EuroVis and IEEE VIS organizing roles. Grants & Supervision: Leads the Visualization Group at TU Wien, supervising student projects and master’s theses. Involved in grants like the Vienna Research Groups program. Labs/Teams: Visualization Group at TU Wien, collaborating on projects like CellView and Molecumentary.

• Augmented Reality
• Computer Vision
• Human-Computer Interaction
• +۴ مورد دیگر

Dr. Alexander Plopski is an Assistant Professor at the Institute of Visual Computing, Technische Universität Graz. His research focuses on advancing augmented reality (AR) technologies, human-computer interaction (HCI), and optical display systems. He holds a PhD, M.Sc., and BSc in relevant fields. His work emphasizes perceptual optimization in AR displays, eye tracking integration, and accessibility solutions for color vision deficiencies. Key research areas include gaze-contingent AR interfaces, light field manipulation for extended reality, and multimodal interaction techniques. Notable contributions include the development of the 'guitARhero' interactive AR guitar tutorial system and studies on focal distance effects in optical see-through displays. His publications span topics from AR display calibration to gesture recognition using radar sensing. He has explored applications in industrial training, medical AR, and robotic telemanipulation. His work often bridges theoretical perceptual studies with practical system implementations, aiming to enhance user experience and accessibility in AR/VR environments.

Bruce Brownمشاهده پروفایل

استاد

• Visual language
• Visual memory
• Research management
• +۳ مورد دیگر

Bruce Brown is Pro-Vice-Chancellor for Research at the University of Brighton , overseeing research across life, physical, social sciences, and arts and humanities. He previously served as Dean of the Faculty of Arts and Architecture (1989–2006) and Head of the Department of Design (1984–1989). Administrative Leadership : REF2014/RAE2008 Chair, International Governor at Shenkar College, and advisor to academic bodies in Hong Kong, Portugal, and Italy. Research Interests : Visual memory, arts education, and research leadership, with publications spanning design history, spatial design, and cultural policy. Scientific Awards : 2007 WHO’s WHO (A&C Black) 2005 Honorary Fellow (University for the Creative Arts) 2004 Honorary Fellow (Royal College of Art) 1985 Elected Member (Designers and Art Directors Association) 1978 Sanderson and Herbert Read Awards (Royal College of Art) 1970 Elected Fellow (Royal Society of Arts) Articles focus on visual communication, design policy, and cultural memory, reflecting his expertise in design research and higher education leadership . He is currently an Editor of Design Issues: Research Journal (MIT Press).

Marie Fargeمشاهده پروفایل

استاد

• Wavelets
• Turbulence
• Computational Fluid Dynamics
• +۴ مورد دیگر

Marie Farge is a distinguished French mathematician and physicist currently serving as Directrice de Recherche 1ère classe at the French National Center for Scientific Research (CNRS) since 2008. She maintains strong affiliations with École Normale Supérieure in Paris where she has been based since 1981, and teaches at multiple institutions including Institut des Etudes Politiques (IEP) in Paris since 2011. Her extensive academic career includes visiting positions at prestigious institutions worldwide including Cambridge University, Harvard University, and the Max Planck Institute. Dr. Farge's research focuses on the intersection of mathematics and physics, with particular emphasis on wavelets , turbulence , and computational fluid dynamics . Her pioneering work has established wavelet analysis as a fundamental tool for studying turbulent flows and extracting coherent structures. She has developed the Coherent Vortex Simulation (CVS) method, which has become influential in turbulence modeling. Her research spans theoretical mathematics, numerical methods, and practical applications in fluid dynamics and plasma physics. Analysis of her publication record reveals a consistent focus on applying wavelet transforms to fluid dynamics problems, with increasing sophistication in handling three-dimensional turbulence and plasma phenomena. Her work demonstrates a progression from theoretical foundations of wavelet analysis to practical computational methods for complex fluid systems. The interdisciplinary nature of her research bridges mathematics, physics, and engineering applications. Prix Poncelet from the French Academy of Sciences (1993) American Physical Society Gallery of Fluid Motion award (1990) Seymour Cray Award for Scientific Computing (1988) Ministry of Foreign Affairs of Japan Award (1985) Fulbright Fellowship at Harvard University (1981) ESRO Award (1971) Elected member of Academia Europaea (2005) Grand Prix du CNRS 'La Recherche en Action' (1989) As an educator, Dr. Farge has taught extensively across France and internationally at institutions including Stanford University, Cambridge University, and numerous European and Asian universities. She has served on the editorial boards of major journals including the Journal of Applied and Computational Harmonic Analysis since 1993 and has been active in the Ethics Committee of CNRS since 2007. Her teaching spans wavelet theory, computational physics, turbulence, and signal processing, reflecting the breadth of her expertise. Dr. Farge maintains active research collaborations worldwide, evidenced by her numerous visiting positions at leading research centers including the Center for Turbulence Research at Stanford University, the Newton Institute in Cambridge, and the Institute for Advanced Study in Princeton. Her work continues to influence both theoretical developments in wavelet analysis and practical applications in fluid dynamics and related fields.

Craig Gotsmanمشاهده پروفایل

استاد

• Computer Graphics
• Computational Geometry
• 3D Animation
• +۵ مورد دیگر

Craig Gotsman is a Professor and Dean at the Ying Wu College of Computing, New Jersey Institute of Technology. He previously held roles at Cornell Tech, Technion, ETH Zurich, and MIT. His research focuses on computational geometry, computer graphics, and 3D animation. Ph.D. in Computer Science, Hebrew University of Jerusalem (1991) His work spans geometric modeling, mesh processing, and applications in animation and visualization. Recent research trends include gaze correction in video conferencing, mesh parameterization, and spectral compression techniques. Notable awards include Fellowships in the US National Academy of Inventors and the Academy of Europe, multiple best paper awards, and the Technion's Hewlett Packard Chair in Computer Engineering. Gotsman has mentored over 50 postgraduate students and holds ten US patents. He co-founded three companies: Virtue 3D Inc. (acquired by NVIDIA), Estimotion Inc. (now ITIS Israel Ltd.), and CatchEye.