Toni Susin is an Associate Professor of Applied Mathematics at UPC-BarcelonaTech. He leads the Dynamic Simulation Lab, part of the ViRVIG research group in Barcelona. His research focuses on numerical methods, physically-based simulation, and applications in computer graphics and biomechanics. Key research areas include Physically-Based Animation Surgical Simulation Biomechanical Applications Image-Based Modeling Fluid Animation Techniques His recent work spans microbiome data analysis, sports performance tracking, and biomedical simulations. While no scientific awards are listed, his career includes founding three tech companies and mentoring numerous PhD/Master's students in computational methods and simulation technologies.
Ricardo J. Machado is a Full Professor of Information Systems Engineering at the University of Minho, where he founded this disciplinary area. He currently serves as President of the CCG/ZGDV Institute and has held strategic roles including Vice-Rector of UMinho. He is a member of the Board of GraphicsVision.AI, the leading academic network in Europe in computer graphics and vision. DEng in Electrical and Computer Engineering (U.Porto) MSc and PhD in Computer Science and Engineering Dr. Habil in Information Systems Engineering (UMinho) Certified Software Product Manager (ISPMA) Cybersecurity and Crisis Management programme from Portuguese National Defence Institute Professor Machado's research focuses on modeling and requirements engineering, systems architecture, process and project management, information semantics, ontologies, and cognitive computing. He has developed several methods and tools including the 4SRS method and the shobi-PN meta-model for requirements analysis, software architecture, ontology computation, and project portfolio management. His work bridges theoretical frameworks with practical industrial applications across various sectors. His recent publications demonstrate a strong trend toward digital transformation across multiple domains including smart cities, healthcare systems, industry 4.0, and higher education. The research shows increasing integration of semantic interoperability, logical architecture design, and data management frameworks. His work consistently addresses the challenges of aligning business processes with technical implementations while focusing on practical applications in real-world settings. IEEE MGA Achievement Award APLOG Excellence Award TAA Textbook Award nomination by Springer Professor Machado has supervised nearly one hundred PhD and MSc students, many of whom now hold leadership roles in academia and industry. He has led over 50 R&I projects funded by FCT, ANI, IAPMEI, and the European Union, partnering with institutions including Carnegie Mellon University, MIT, Fraunhofer, and Bosch. His project portfolio spans requirements engineering, systems architecture, and digital transformation initiatives across multiple sectors including healthcare, manufacturing, and smart cities. He founded the SEMAG research group at ALGORITMI and the EPMQ department on Software Engineering and Intelligent Data at CCG/ZGDV. As Director of the ALGORITMI Research Centre, he coordinated UMinho's participation in strategic initiatives such as CEDT, CMU | Portugal, EIT Digital, EUHubs4Data, and Gaia-X Portugal. He also co-founded DTx and ProChild CoLabs, and TICE.pt and CSCP Clusters.
Aleksandr Zagarskikh is an Associate Professor at the Game Development School of ITMO University, specializing in virtual reality, scientific visualization, and high-performance computing. He has led projects in quantum chemistry visualization, flight simulators, and urban simulation technologies. Developed real-time graphics systems for ultra-realistic image synthesis Created high-performance network protocols for distributed visualization Current research focuses on big data decision-making in finance and multiscale urban modeling His work spans predictive modeling, GPU optimization, and cloud-based infrastructure visualization, with publications in Procedia Computer Science. He teaches courses in game technologies, VR, and scientific computer graphics.
Alastair F. Donaldson is a Professor in the Department of Computing at Imperial College London's Faculty of Engineering, where he leads the Multicore Programming Group. He also works as a Software Engineer at Google in the Android Graphics Team. Previously, he served as Director of GraphicsFuzz, an Imperial College spinout company acquired by Google in 2018. His research spans programming languages, compilers, verification, and testing, with a particular focus on randomized and fuzz testing techniques for compilers and program analyzers. Donaldson has developed several influential testing frameworks including GraphicsFuzz, RustSmith, and GrayC, which have significantly advanced compiler testing methodologies. Analysis of his recent publications reveals a strong trend toward practical applications of compiler testing techniques across diverse domains including GPU programming, verification-aware languages, and memory models. His work increasingly incorporates continuous integration practices and focuses on addressing real-world challenges in compiler development and verification. Donaldson maintains active involvement in the programming languages research community, serving on program committees for major conferences including PLDI, POPL, ASPLOS, and SPLASH. He has contributed significantly to advancing compiler testing methodologies and has mentored numerous researchers through PLMW (Programming Languages Mentoring Workshop). He leads the Multicore Programming Group at Imperial College London, which focuses on challenges in parallel and concurrent programming. His work bridges theoretical computer science with practical software engineering challenges, particularly in the areas of compiler correctness and verification.
Dr. Bob Mahmoodi serves as a Lecturer in the Department of Electrical and Computer Engineering at the University of St. Thomas School of Engineering, where he has taught for 10 years since 2012. Concurrently, he holds an adjunct instructor position at the University of Minnesota's Electrical and Computer Engineering department for 35 years. His industry background includes over 30 years at 3M in R&D focused on wireless RFID and biometric sensors, plus three years at Honeywell developing airborne radar systems. His educational qualifications include: PhD in Electrical Engineering and Control Sciences from the University of Minnesota MS in Electrical Engineering from the University of Minnesota BS in Electrical Engineering from the University of Minnesota Dr. Mahmoodi's research spans wireless communication, digital signal processing, control systems, medical instrumentation sensors, and FPGA/IC design. His work integrates analog/digital systems with applications in biometric security and image compression. Current teaching focuses on Electronics I laboratories, Engineering Design Clinic II, and graduate-level Digital Signal Processing coursework emphasizing machine learning applications. His publication history from 1981-2013 reveals consistent innovation in image enhancement algorithms and radar signal processing, with increasing specialization in medical imaging after 1984. Key thematic developments include the transition from military radar applications to medical/biometric systems and the evolution of real-time processing techniques for commercial printing technologies. Dr. Mahmoodi holds seven U.S. patents covering image enhancement (1986, 1994), projection displays (2006), and oil quality monitoring systems (2012-2013). His professional service includes IEEE Twin Cities Chapter chairmanship (1989-1990), IS&T Conference chairmanship (1991), and ACR-NEMA standards committee membership for image compression. As an active design clinic instructor, he mentors student teams in industrial problem-solving through the Senior Design Clinic program. His industry experience directly informs classroom instruction, particularly in sensor integration and system modeling applications. Laboratory development for electronics courses leverages his 3M/Honeywell background in practical circuit design.
Megan Hofmann is an Assistant Professor holding dual roles at Northeastern University's Khoury College of Computer Sciences and the Department of Mechanical and Industrial Engineering (College of Engineering). She earned her PhD in Human-Computer Interaction from Carnegie Mellon University in 2022. Her research focuses on accessibility and digital fabrication, particularly in healthcare contexts, including automated machine knitting and medical making. She leads the Accessible Creative Technologies (ACT) Lab, which develops tools like Maptimizer (custom tactile maps), OPTIMISM (collaborative optimization frameworks), and KnitGIST (generative knitting design). Her work addresses challenges in assistive technology fabrication, such as creating accessible medical devices and optimizing rapid prototyping in healthcare. Recent projects include NSF-funded research on interactive smart textiles and studies on distributed manufacturing during the COVID-19 pandemic. Hofmann’s contributions span interdisciplinary domains, blending computer science, mechanical engineering, and healthcare innovation. Grants & Awards: Recipient of a $550,000 NSF grant for smart textile tools (2024). Labs: ACT Lab focuses on inclusive digital fabrication systems.
Rahmatullah Roche serves as an Assistant Professor in the Department of Computer Science at Columbus State University's TSYS School of Computer Science, joining the tenure-track faculty in Fall 2024. His academic credentials include: Ph.D. in Computer Science and Applications from Virginia Tech (2024) M.S. in Computer Science and Software Engineering from Auburn University (2021) B.S. in Computer Science and Engineering from Bangladesh University of Engineering and Technology (2016) Dr. Roche's research spans Computational Biology , Applied Machine Learning , Data Science , and Human-Computer Interaction , with primary focus on macromolecular predictive modeling for intra- and inter-molecular interactions using cutting-edge AI techniques. His work bridges computer science and biology to solve complex structural bioinformatics challenges. Analysis of his 14 publications (2020-2025) reveals a consistent trajectory in applying deep learning—particularly transformer networks, equivariant graph neural networks, and biological language models—to protein-RNA complex prediction, protein-nucleic acid binding, and protein-protein interaction site identification, published in high-impact journals including Cell Systems and Nucleic Acids Research. Key scientific recognitions include: Pratt Fellowship Award (2023-2024) Turner College Research Award (2025) Professional Development Award for Core Course redesign (2025) Core Course Design Institute Professional Development Award (2024) 3rd place Flash Talk award at VT GPSS Symposium (2024) Best Poster Award at ACM-BCB 2020 YSEA Finalist Travel Award at MCBIOS 2024 Dr. Roche actively recruits undergraduate and graduate students for his research lab while securing resources through NSF ACCESS grants. His teaching portfolio includes Computer Science I, Computer Organization, and Graphical User Interface Development, complemented by service as Discipline Coordinator for Web Development and reviewer for top bioinformatics journals. His research group collaborates with Virginia Tech on advancing biomolecular modeling through interdisciplinary AI applications.
Eduard Gröller is a Full Professor of Visualization at the Vienna University of Technology (TU Wien), leading the Research Unit of Computer Graphics and the Visualization Group within the Institute of Visual Computing & Human-Centered Technology (VC&HCT). He holds adjunct professorships at the University of Bergen, Norway, and chairs several academic committees. His academic journey began with a PhD in 1993 from TU Wien, followed by extensive contributions to visualization research. His research focuses on visual computing, scientific visualization, and medical imaging, with applications in energy modeling, climate analysis, and molecular biology. Gröller has pioneered methods like BEMTrace for BIM-based energy models and HORA 3D for flood risk visualization. He co-authored over 300 publications, including foundational work in IEEE Transactions on Visualization and Computer Graphics and Computer Graphics Forum . Gröller's awards include the IEEE VGTC Technical Achievement Award (2019), Eurographics 2015 Outstanding Technical Contributions Award, and Fellow of the Eurographics Association (2009). He actively contributes to conferences like EuroVis and IEEE Visualization as program chair and reviewer. His educational efforts span courses in visual computing, graphics, and data analysis, with a focus on immersive tools like ImNDT for material data exploration. Current projects include Climate-Sensitive Adaptive Planning for Resilient Cities, Visual Analytics in Radiation Therapy, and scalable web-based visualization techniques. He leads teams in VRVis, a research center for applied visualization, and collaborates internationally on medical imaging and environmental data challenges.
Dr. Denis Kalkofen serves as an Associate Professor at the Institute of Computer Graphics and Vision (ICG) at Graz University of Technology, Austria. His academic journey began with a Dipl.-Ing. (2004) from the University of Magdeburg, followed by a Dr. techn. (2009) from Graz University of Technology. University of Magdeburg - Dipl.-Ing. (2004) Graz University of Technology - Dr. techn. (2009) University of Michigan, Ann Arbor - Virtual Reality Laboratory member Stanford University - Visiting Assistant Professor at Computational Imaging Laboratory (2019) University of South Australia - Visiting Researcher at Wearable Computer Laboratory (2019) Dr. Kalkofen's research centers on developing visualization, interaction, authoring, and display technologies for Virtual and Mixed Reality environments, with particular emphasis on combining computer graphics and computer vision techniques to create comprehensible and accessible VR/MR experiences. His work spans situated visualization (addressing label placement and X-ray visualization), photometric rendering (recovering lighting properties for realistic AR), and content creation automation (leveraging existing data sources for AR content). His publication trends over the past 15+ years demonstrate consistent leadership in AR/MR research, evolving from foundational work on visualization techniques to current cutting-edge research in neural rendering, neuroadaptive systems, and industrial AR applications. Recent work shows increased focus on practical industrial implementations, error management in AR assembly, and multimodal learning applications. Best paper award for 'enRoute: Dynamic path extraction from biological pathway maps' (2012) Best short paper for 'TutAR: Augmented Reality Tutorials for Hands-only Procedures' (2018) Best paper for 'Tools for Teaching Mining Students in Virtual Reality' (2020) Honorable Mention for Best Paper for 'Adaptive User-Perspective Rendering' (2017) Dr. Kalkofen leads Team Kalkofen at ICG, supervising researchers including Peter Mohr, Shohei Mori, David Mandl, and Ana Stanescu. His team has secured significant funding for projects related to AR/VR content creation, visualization techniques, and industrial applications. They maintain strong collaborations with institutions including Stanford University, University of South Australia, and University of Michigan. Team Kalkofen operates within the Institute of Computer Graphics and Vision at TU Graz, focusing on three main research thrusts: situated visualization for AR, photometric rendering for realistic MR, and automated content creation for professional AR applications. The team maintains active partnerships with industry and academic institutions worldwide, contributing to the advancement of practical AR/MR technologies.
Chris Barker is a Senior Lecturer at RMIT University's School of Design, specializing in animation, computer graphics, and interactive media. As part of the Centre for Animation and Interactive Media (AIM), he focuses on augmented architecture, virtual heritage, and creative entrepreneurship. His work bridges art, technology, and industry, with notable roles as Creative Director and Production Designer for urbanskinning, creating immersive environments for stage and events. Industry Experience: Member of Melbourne ACM SIGGRAPH Professional Chapter Member of CG Society Research Interests: Barker explores animation studies, human-computer interaction, heritage preservation, and new media art. His projects include installations like Urban Skinning (2007) and collaborations with institutions like ACMI and QUT. Exhibitions & Awards: Final Notice (1999): Winner of the Planet X Award for Best Use of Digital Media Featured in international exhibitions, including ACMI’s Eyes, Lies and Illusions (2006–2007) Teaching & Projects: Barker supervises projects like New Tricks: Illusionary Experiences with 3D Animation (2025) and Crafting Vietnamese Digital Heritage (2024). His work emphasizes interdisciplinary innovation and community engagement through digital media.
Atanas Gotchev is a Professor of Signal Processing at Tampere University, Finland, where he leads the 3D Media Group and directs the Centre for Immersive Visual Technologies (CIVIT). He also serves as Chair of the Erasmus Mundus Joint Master Programme in Imaging and Deputy Director of the TAU Imaging Research Platform. Gotchev holds degrees from Technical University Sofia (M.Sc. in Electronics and Automation Engineering and M.Sc. in Applied Mathematics), the Bulgarian Academy of Sciences (PhD in Information Technologies), and Tampere University of Technology (D. Tech.). His research focuses on immersive imaging, 3D/light field imaging, computational optics, and image quality assessment. He has coordinated three Marie Sklodowska-Curie networks in light field imaging and serves as Senior Editor for IEEE Transactions on Image Processing and the Journal of Electronic Imaging. Gotchev has organized major conferences like the IEEE International Conference on Image Processing (2026) and chaired workshops on multimedia signal processing. Recent research emphasizes computational cameras, diffractive optics, and end-to-end design for metaoptics. He has a visiting professorship at the University of Utah (2023-2024) supported by Fulbright and Nokia Foundation grants. His work spans datasets like CIVIT and contributions to safety-critical applications in robotics and ITER projects.
Ms. Stephanie Andrews is a Lecturer and Program Manager for the Masters of Animation, Games, and Interactivity (MAGI) at RMIT University's School of Design. She holds a PhD in Virtual Reality (VR) and has a career spanning art, technology, and academia. Previously, she was a Technical Director at Pixar, led curriculum innovation at the University of Washington's DXARTS program, and served as Creative Director at Liminal, a VR and neuroscience company. Her research focuses on stereoscopic spatial hacking in VR, 3D graphics, and user experience design. She has received over $300,000 in grants for stereoscopic research and exhibited internationally in Australia, Iceland, the UK, and the USA. Education: PhD in VR creation, Technical Director experience at Pixar, and leadership roles in academic programs. Her work blends art and tech through interactive installations, digital media, and educational initiatives. Research interests include immersive VR experiences, spatial perception, and experimental art forms. She co-founded companies for the metaverse and 3D printing sectors, showcasing her entrepreneurial spirit. Recent projects include Existential Crisis (2024), an interactive VR artwork exploring embodiment, and Citizen Tree , presented at ISEA2024. Awards/Grants: Secured $300k+ USD in stereoscopic research grants and established a groundbreaking audio-video suite at the University of Washington. Service: Jury member for ISEA2024's art exhibition selection. Labs/Teams: Center for Digital Art and Experimental Media (DXARTS), Liminal VR.
Dr. Gamal ELGHAZALY is a Research scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), affiliated with the Ubiquitous and Intelligent Systems department. His work focuses on autonomous driving technologies, V2X communication systems, robotics, and control systems. Key research areas include 5G-enabled teleoperated driving, high-definition map construction, and 3D perception for autonomous vehicles. He has developed platforms like RoboCar and contributed to frameworks like FastCycle for modular automated systems. Research interests span robotics kinematics (planar parallel manipulators), adaptive control methodologies (sliding mode control, fuzzy logic), and hybrid systems (cable-driven robots). His publications emphasize real-time motion planning, sensor fusion, and safety-critical systems. Recent works (2023-2025) highlight advancements in 4D perception, cloud-assisted 3D reconstruction, and V2X-enabled collaborative systems. Publications from 2017-2018 reflect early contributions on parallel manipulator modeling and control, while recent efforts focus on integrating cutting-edge technologies like 5G and edge computing into autonomous systems. His work bridges theoretical robotics with practical implementations, addressing challenges in both dynamic environments and industrial applications.
Jing Zhao is a Professor at Beijing Institute of Technology's School of Automation, Department of Computer Science, with an extensive publication record spanning artificial intelligence, computer vision, medical imaging, and robotics. Their interdisciplinary research bridges theoretical computer science with practical applications in healthcare, agriculture, and engineering. Research interests focus on cutting-edge AI methodologies including deep learning architectures, neural rendering techniques, and multimodal systems. Notable work includes advancements in 3D reconstruction (Gaussian Splatting), medical image analysis for cancer diagnosis, and novel approaches to EEG-based emotion recognition. The research demonstrates strong interdisciplinary connections between computer science and domain-specific applications. Recent publications reveal a consistent trend toward practical AI implementations across diverse fields. Jing Zhao's work shows expertise in adapting theoretical machine learning concepts to solve real-world problems in medical diagnostics, agricultural monitoring, and robotics. The research portfolio demonstrates particular strength in developing novel neural network architectures for specialized applications. As a corresponding author on numerous high-impact publications, Jing Zhao appears to lead a productive research group with collaborations spanning multiple institutions and disciplines. The publication record indicates significant contributions to both theoretical computer science and applied AI solutions across various domains.
Al Bovik is a Visiting Professor at the University of Texas at Austin's Department of Electrical and Computer Engineering, part of the College of Engineering. His research focuses on digital video, visual neuroscience, and deep learning, with an emphasis on developing perceptual theories for high-quality streaming video and virtual/augmented reality systems. He has pioneered advancements in video quality assessment, compression, and AI-generated media evaluation. He has received prestigious awards including the IEEE Edison Medal, Primetime Emmy, and membership in multiple national academies. Bovik co-founded the IEEE Transactions on Image Processing and established the IEEE International Conference on Image Processing in 1994, which he chaired. His influential books include The Essential Guides to Image and Video Processing . Key Research Contributions: HDR/SDR video quality metrics, perceptual artifact detection, and AI-driven quality assessment frameworks. Labs/Teams: Leadership in IEEE initiatives and collaborations in media quality and signal processing. His work bridges theoretical research with practical applications in video streaming, medical diagnostics, and user-generated content analysis.
