Find Academic Supervisors

Sudhanshu SemwalView profile

Professor

• Computer Graphics
• Virtual Reality (VR)
• Wearable Computing
• +7 more

Dr. Sudhanshu Semwal is a tenured Professor of Computer Science at the University of Colorado Colorado Springs (UCCS), where he has served since 1987. He advanced through the ranks from Assistant Professor (1987) to Associate Professor (1994) and achieved full Professor status in 2000. He served as Department Chair in 2002. His research focuses on computer graphics, virtual reality (VR), wearable computing, medical visualization, and computational geometry. He pioneered UCCS's MS in Media Convergence, Games and Media Integration (GMI) program and co-founded the GMI Lab and CoView Data Labs™. His work spans academic collaborations at ATR Kyoto and Sandia National Labs, with over 60 peer-reviewed publications. Education: B.E. in Electronics & Communication Engineering from University of Roorkee (India), M.Sc. in Computing Science from University of Alberta (Canada), and Ph.D. in Computer Science from University of Central Florida. Research emphasizes VR applications for empathy training, medical imaging, and human animation. His contributions include innovations in ray tracing, volume rendering, and drone-based AR systems. He received the 2004 EAS Best Teacher Award Nomination and has presented globally across 8 countries. Advising & Innovation: Supervised 117 GMI program alumni, developed crossover user interface models for inclusive computing, and led projects like the Line-Storm ludic system and EEG-based game accessibility tools. Collaborations include agent-based modeling for urban systems and blockchain solutions for healthcare privacy. Labs & Partnerships: Director of GMI Lab, partner in UCCS's ICORE interdisciplinary initiative, and collaborator with the UCCS Honors Program through the AMP Program.

Zahra MontazeriView profile

Lecturer

• Computer Graphics
• Physics-based Rendering
• Material Modeling
• +3 more

Zahra Montazeri is a Lecturer (Assistant Professor) in the Department of Computer Science at the University of Manchester. Her research focuses on physics-based computer graphics, particularly photorealistic rendering and appearance modeling for complex materials like cloth, hair, and fur. She holds a PhD in Computer Science from the University of California, Irvine (UCI), and has industry experience at Disney Research, WetaDigital, Industrial Light & Magic (ILM), Pixar, and Luxion. **Education:** PhD in Computer Science (UCI, 2015–2021) M.Sc. in Computer Science (UCI, 2015–2017) B.Sc. in Computer Engineering (Sharif University of Technology, Iran, 2010–2014) **Research Interests:** Zahra’s work bridges academic and industrial applications, emphasizing practical and efficient rendering techniques. Her key areas include physics-based rendering, material modeling for fabrics, and virtual reality optimizations like foveated rendering. She collaborates with industry leaders such as WetaDigital and has contributed to movies like The Mandalorian and Avatar: The Way of Water . **Articles Trends:** Recent work focuses on texture-free cloth rendering, dynamic BTF synthesis, and neural-based material models. Her research often addresses computational efficiency while maintaining photorealism, with applications in film, gaming, and VR. **Awards:** Best Paper Award at EGSR (2023) Best Visuals Award at EGSR (2023) UCI Doctral Fellowship (2015) LightSpeed Venture Partners Summer Fellowship (2016) **Advising & Grants:** Advises four PhD students and has one alumni (David Petrescu). Her group actively collaborates with industry and explores applied research in rendering and virtual environments. She serves on program committees for PG, EGSR, and I3D. **Labs/Teams:** Leads a research group at Manchester focused on graphics and virtual environments, with interdisciplinary projects in computer vision, AI, and material science.

• Laser Plasma Physics
• High-Performance Computing (HPC)
• Computational Physics
• +3 more

René Widera is a researcher at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), specifically within the Laser Particle Acceleration department of the Institute of Radiation Physics. His work focuses on advancing high-performance computing (HPC) techniques for plasma simulations, particularly leveraging GPU architectures and exascale computing frameworks. He contributes to the development and optimization of the PIConGPU code, a leading particle-in-cell (PIC) simulation tool. His research integrates machine learning for real-time data analysis, parallel algorithms for HPC scalability, and cross-platform visualization strategies. Areas of expertise include laser plasma acceleration, high-energy-density physics, and the design of efficient numerical methods for large-scale simulations. He explores hardware-agnostic solutions for computational challenges, including memory access optimizations and DAG-based parallelism. Collaborations involve international HPC initiatives and open-source software projects like openPMD and alpaka . Key projects include the TWEAC initiative to overcome limitations in laser-wakefield acceleration and the development of in-situ visualization pipelines for real-time simulation insights. He also evaluates modern GPU architectures (e.g., AMD, ARM-based systems) for scientific workloads. His contributions bridge theoretical plasma physics with practical computational advancements, aiming to enable next-generation high-intensity laser experiments.

• Machine Learning
• Computer Vision
• Data Science
• +3 more

Xiaoxue Li is a computer science researcher with a robust publication record spanning 2008-2025. She contributes to diverse fields including Machine Learning , Computer Vision , and Data Science , with recent 2025 work on neural rendering (MoNeRF) and light field image quality assessment. 2024 publications focus on stress reduction databases , asymmetric distribution learning for museum applications, and LIDAR data integration for biomass estimation. Her 2023-2021 output includes fault identification via deep belief networks and micro-expression recognition systems. Earlier works (2008-2020) address polynomial discriminant systems , graph attention networks , and network embedding for heterogeneous systems. Her research trends show increasing specialization in generative AI and graph-based learning applied to both computer vision and physical systems .

• Cybersecurity
• Machine Learning
• Web Development
• +3 more

Nikola Savanović is a researcher and academic at Singidunum University, specializing in cybersecurity, machine learning, and web technologies. He holds a PhD in Advanced Security Systems (2024) from Singidunum University, following a Master's in Contemporary Information Technologies (2016) and a Bachelor's in Informatics and Computing (2013), both from the same institution. He also completed high school in Computer-Aided Design at Politehnika School for New Technologies (2003-2007). His research focuses on intrusion detection systems, machine learning optimization for cybersecurity applications, and adaptive web technologies. He has contributed to educational technology through virtual learning environments and game-based learning. His mathematical work includes fixed point theory in b-metric spaces. He has authored/co-authored multiple books on web design, multimedia systems, and digital marketing. Publications highlight interdisciplinary work: hybrid CNN-XGBoost models for medical diagnostics, metaheuristic algorithms for software defect detection, and cybersecurity innovations in healthcare IoT systems. His articles span computer science, mathematics, and data science, emphasizing practical applications in education and healthcare. Despite no listed awards, his extensive publication record and teaching roles reflect significant academic contributions. He actively collaborates on university projects and advises students in informatics and computing disciplines, though no formal student list is provided.

• Animation
• Collaborative Play
• Visual Storytelling
• +3 more

Kyoung Lee Swearingen is an Associate Professor and Graduate Studies Chair at The Ohio State University's Department of Art, Art & Technology. She holds an M.F.A. from OSU, B.F.A. from Savannah College of Art and Design, and B.S. in Chemistry from Sungshin Women’s University. Her expertise spans animation, collaborative play, and humane technology for social good. Her research focuses on creating inclusive games and animations, such as Wall Mounted Level (winner of 'Best Innovative Game' at Montreal 2017) and The Woods , an AR game addressing social isolation. Collaborations with Scott Swearingen produced award-winning projects like Sonder , exhibited globally, and Beacon , an art installation exploring human connection. A former Pixar Technical Director, her filmography includes Ratatouille , Wall-E , and Toy Story 3 , earning 4 Academy Awards. She actively presents at SIGGRAPH, HCI International, and GEM conferences, emphasizing interdisciplinary approaches to technology and storytelling. Education: M.F.A., Art & Technology, The Ohio State University (2004) B.F.A., Computer Art, Savannah College of Art and Design (2001) B.S., Chemistry, Sungshin Women’s University (1995) Awards: 4 Academy Awards for Best Animated Feature (Pixar) Montreal Independent Game Festival Awards (2017) Global film festival recognitions for Sonder Key Projects: Wall Mounted Level : Mixed-reality game promoting reconciliation The Woods : AR cooperative game addressing social isolation Sonder : Collaborative animated short with 144 contributors Grants & Collaborations: 45% effort in IFIP-ICEC 2021 publication Multi-institutional collaborations with Texas Women’s University, MSU, and Monmouth University Labs & Teams: Works at the intersection of art, technology, and social impact through Ohio State’s design programs and global partnerships.

• New Product Development
• Engineering Design Thinking
• Human-Machine Interaction
• +7 more

Martin Steinert is a Professor of Engineering Design and Innovation at the Norwegian University of Science and Technology (NTNU), affiliated with the Faculty of Engineering and the Department of Mechanical and Industrial Engineering. He leads the Design & Engineering research group and heads TrollLABS, a prototyping lab he founded in 2014. His research focuses on the fuzzy front end of product/service development, human-machine interactions in critical environments, and disruptive technology management. Education: Ph.D. in Engineering Design. Affiliations: Norwegian Academy of Technological Sciences (NTVA). Teaching: Courses include Innovation by Design Thinking, Fuzzy Front End Engineering, and Engineering Design Methodology for PhD students. Research Interests: 3D printing and additive manufacturing for medical and aerospace applications. Prototyping methodologies and open-source hardware paradigms. Human factors in remote operations and autonomous systems. Generative AI's role in design innovation and ethical challenges. Articles Trends: Recent work emphasizes blood glucose prediction algorithms, haptic surgical simulations, and material science in 3D printing. Themes include clinical relevance in AI-driven healthcare and low-cost space prototyping. Awards: Top 1% in Mechanical Engineering (Stanford, 2022). Grants: Over $15M from NSF, Swiss NSF, and Norwegian Research Council. Advising: Supervising 9 PhD students and leading international collaborations like the CERN Challenge-Based Innovation program. Labs/Teams: TrollLABS pioneers open-source prototyping tools and hosts hackathons (e.g., IDEA Challenge). Collaborations include Stanford University and CERN.

Renata RaidouView profile

Associate Professor

• Medical Visualization
• Visual Analytics
• Uncertainty Visualization
• +3 more

Renata Raidou is an Associate Professor in Biomedical Visualization and Visual Analytics at the Research Unit of Computer Graphics, Institute of Visual Computing & Human-Centered Technology, TU Wien, Austria. She previously held positions at the University of Groningen and TU Wien as a postdoc. Her research focuses on medical visualization, uncertainty visualization, and data physicalization for healthcare applications. Raidou has received prestigious awards including the Dirk Bartz Prize (2017) and EuroVis Young Researcher Award (2022). She coordinates TU Wien's BSc in Digital Health and MSc in Medical Informatics. Education: PhD in Medical Visualization (Eindhoven University of Technology, 2017), MSc in Biomedical Engineering (TU Delft), Diploma in Electrical and Computer Engineering (NTUA). Professional Roles: Editorial Board member of Computer & Graphics , Steering Committee member of EG VCBM, and member of EASAC's AI in Healthcare working group. Research Interests: Medical visualization strategies for P4 medicine, anatomical edutainment through physicalization, and uncertainty-aware visual analytics in radiotherapy. Her work bridges visual computing, machine learning, and medical applications, emphasizing clinical decision support and public health education. Awards: Over 10 awards including Best Paper recognitions at IEEE Vis and EuroVis, and the EuroVis Best PhD Award. Her contributions span visualizing anatomical variability, ensemble data exploration, and interactive medical training tools. Grants & Projects: Leads the Health Virtual Twins project (2024–2028) for personalized stroke management. Active in interdisciplinary collaborations, including the Shonan Meeting on Formalizing Biological Visualization. Labs/Teams: Head of the Visualization Group at TU Wien, developing tools like Vologram (holographic medical data physicalization) and Slice and Dice anatomical crafts. Collaborates on edutainment systems and AI-driven healthcare visualization.

Annalena UlschmidView profile

Researcher

• Physically-based Rendering and Simulation
• Statistics / User Studies
• Incremental Path Tracing for Scene Editing
• +4 more

Annalena Ulschmid is a PreDoc Researcher at the Vienna University of Technology , affiliated with the Faculty of Informatics and the Computer Graphics group. She holds an MSc and contributes to research in physically-based rendering , user studies , and real-time graphics algorithms . Research spans incremental path tracing , alternative rendering datastructures , and probabilistic models for participating media . Key projects include ACD (Automated Prioritization for Context-Aware Re-rendering) (2020–2028) and IVILPC (Single-Exemplar Lighting Style Transfer) (2023–2026). She teaches courses like Computer Graphics , Fundamentals of Computer Graphics , and Rendering . Publications focus on real-time rendering , VR accessibility , and lighting style transfer . Her work has been recognized with the Best Student Paper Award at VISIGRAPP 2025 . Notable collaborations include Michael Wimmer and Katharina Krösl . Further details are available via her ORCID profile and GitHub repository .

Adam CelarekView profile

Researcher

• Computer Graphics
• Physically Based Rendering
• Deep Learning for 3D Data
• +4 more

Adam Celarek is a PreDoc Researcher and University Assistant at the Computer Graphics department (E193-02) within the Faculty of Informatics at Vienna University of Technology. He holds the position of Scientist in the Rendering and Modeling workgroup and serves as a PhD student. Celarek teaches courses including Computer Graphics, Fundamentals of Computer Graphics, Seminar in Visual Computing, and Rendering. His research interests span Physically Based Rendering, Deep Learning for 3D data, Point Clouds, Gaussian Mixture Models, and Terrain Rendering. Celarek's work focuses on the intersection of computer graphics and machine learning, particularly in processing unstructured 3D data. He is currently working on deep learning applications for Gaussian mixture models and developing AlpineMaps, a navigation aid for alpinists in collaboration with Manuela Waldner. His publication record shows a consistent focus on rendering techniques and 3D data processing, with recent work emphasizing the application of deep learning to Gaussian mixture models and terrain visualization. The research demonstrates progression from foundational work on light transport algorithms to more recent applications in geospatial visualization and deep learning for 3D data. OCG-FÖRDERPREIS 2018 (with Christoph Weinzierl-Heigl) Celarek has supervised multiple student projects including Johannes Eschner's work on real-time avalanche risk visualization and Stefan Fraiss's research on Gaussian mixture models from point clouds. He is involved in the EVOCATION training network as a former Marie Skłodowska-Curie fellow and currently leads the High-performance triangle-mesh streaming for unbounded datasets project funded by netidee Projektförderung. As a member of the Rendering and Modeling workgroup, Celarek contributes to the department's research in physically based rendering, 3D data processing, and visualization techniques, with particular expertise in light transport algorithms and Gaussian mixture models.

David CazierView profile

Professor

• Virtual Reality
• Computer Graphics
• Computational Geometry
• +4 more

David Cazier is a **Professor at the University of Strasbourg** and a **Researcher at the ICube Laboratory**, specializing in geometric and graphical computing. He also teaches computer science at the **IUT of Haguenau**. His research focuses on three main axes: multiresolution geometric models, real-time interaction in virtual reality, and tools for adapting such models to simulations and visualization. His work bridges theoretical advancements in geometric modeling with practical applications in medical imaging, crowd simulation, and augmented reality. **Research Interests**: Cazier’s expertise includes virtual reality (VR) immersion, real-time interaction techniques, and the development of efficient geometric models for complex simulations. His projects often involve hierarchical meshes, topological changes during deformations, and applications in surgical AR. Key areas include multiresolution representations, collision detection in dynamic environments, and non-manifold geometry processing. **Publications**: His recent work emphasizes medical applications (e.g., surgical AR with topological changes) and foundational contributions to geometric data structures (e.g., CGoGN, CPH). He explores user interaction challenges in the digital divide era and develops tools for crowd simulation using deformable agents. **Collaborations and Projects**: Active in collaborations with the ICube Lab’s IGG team, Cazier contributes to platforms like CGoGN and InVirtuo. His research spans national and European projects, including IHU, ANR, and CNRS initiatives. He supervises internships on geometric models for VR applications and interdisciplinary projects combining geometry with medical and industrial challenges.

Richard ZemelView profile

Professor

• Machine Learning
• Artificial Intelligence
• Statistics
• +6 more

Richard Zemel is the Trianthe Dakolias Professor of Engineering and Applied Science in the Department of Computer Science at Columbia University. He leads the NSF AI Institute for ARtificial and Natural Intelligence (ARNI). His research focuses on machine learning, artificial intelligence, statistics, neuroscience, and cognitive science with recent emphasis on robust AI, few-shot learning, algorithmic fairness, and continual learning. Education details are not explicitly listed, but his career includes roles as director of an NSF institute and extensive academic contributions. His research group includes active and former students/postdocs now in academia and industry roles at institutions like Google, DeepMind, NVIDIA, and universities globally. Key Research Themes: Fairness in AI, causal inference, generative models, and neural network architectures. Labs/Teams: ARNI Institute (NSF-funded), Zemel Research Group at Columbia. Advising and grants include supervision of over 40 students/postdocs and leadership in multi-institutional AI initiatives. His work spans theoretical foundations to real-world applications in healthcare, ethics, and computational neuroscience.

Pradeep SenView profile

Professor

• Computer Graphics
• Image Synthesis
• Computational Photography
• +5 more

Pradeep Sen is a Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara, where he directs both the UCSB MIRAGE Lab and the UCSB Gaucho Game Lab. His research spans computer graphics, computational photography, and real-time rendering, with significant contributions to high dynamic range imaging and Monte Carlo rendering techniques. Sen has established himself as a leading researcher in computer graphics with numerous publications in top venues including SIGGRAPH and IEEE Transactions on Visualization and Computer Graphics. Ph.D. in Electrical Engineering, Stanford University (2006) M.S. in Electrical Engineering, Stanford University (1998) B.S. in Computer and Electrical Engineering, Purdue University (1996) Dr. Sen's research primarily focuses on novel rendering algorithms for accelerating global illumination and image-based techniques for capturing light transport. His work bridges theoretical advances in computer graphics with practical applications in video game development and immersive technologies. He has made significant contributions to patch-based high dynamic range video, computational zoom, and denoising Monte Carlo renderings using machine learning approaches. His research has important applications in virtual reality, augmented reality, and medical imaging. Analysis of Sen's recent publications reveals a strong trend toward integrating machine learning techniques with traditional computer graphics algorithms. His work has evolved from fundamental rendering techniques to more complex applications involving neural networks for image synthesis, 3D reconstruction, and content creation. There's a clear progression from his early work on dual photography and HDR imaging to more recent work on virtual try-on systems, diffusion models for image editing, and cosmic ray detection frameworks. Symposium on Computer Animation (SCA) Best Paper Award (2016) High Performance Graphics (HPG) Best Paper Finalist (2015) CVPR 2015 Outstanding Reviewer Award (2015) National Science Foundation CAREER award (2009) SIGGRAPH/Eurographics Graphics Hardware Conference Best Paper Award (2004) Dr. Sen has successfully mentored numerous PhD and Master's students who have gone on to prominent positions at companies like Adobe, Facebook Reality Labs, and Pinterest. His research has been generously funded through multiple NSF grants totaling over $1.6 million, including a prestigious CAREER award. He has also secured funding from NVIDIA, Sandia National Laboratories, and other sources to support his innovative work in computer graphics and visualization. As Director of both the UCSB MIRAGE Lab and the UCSB Gaucho Game Lab, Sen leads research teams focused on advancing computer graphics, imaging, visualization, and computer vision technologies. The MIRAGE Lab conducts fundamental research in rendering algorithms and computational photography, while the Gaucho Game Lab focuses on video game development and immersive experiences. These labs foster interdisciplinary collaboration between computer science, electrical engineering, and media arts students and faculty.

Joseph McKayView profile

Associate Professor

• Interactive Art-Games
• VR/AR Development
• Computer History
• +3 more

Joseph McKay is an Associate Professor of New Media at Purchase College (SUNY), specializing in interactive art-games and digital media. He holds a BFA from Nova Scotia College of Art & Design (1993) and an MFA from UC Berkeley (2007), with additional studies at the Whitney Independent Study Program (2000-2001). His work bridges fine art and playful interactivity, focusing on video games as modern storytelling mediums. He teaches courses like Experimental Game Lab, Programming for Visual Artists, and Physical Computing. Key research areas include VR/AR development, computational art, and the intersection of technology with everyday life. Notable projects include Awwful Tree Farmer (2024), Peckish (2023), and Zamboni Simulator . He has exhibited widely, including at MoMA, Berkeley Art Museum, and The Wrong Biennale. Awards include the Juanita & Joseph Leff Distinguished Professorship (2016–17) and the Eisner Award (2006). As an educator, he emphasizes hands-on technical skills and conceptual innovation. His exhibitions often explore themes like environmental interaction, surveillance, and playful critique of technology. He previously taught at UC Berkeley, Stanford, and Diablo Valley College, and directed the Woodstock Digital Media Festival (2011–2012).

Feng LiuView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +11 more

Feng Liu is an Assistant Professor in the Department of Computer Science at Drexel University's College of Computing & Informatics (CCI). He previously served as a Postdoctoral Researcher at Michigan State University's Department of Computer Science and Engineering. His research spans computer vision, machine learning, and biometric recognition, with a focus on 3D scene understanding, generative AI, and human-AI interaction. Research Interests: 3D Computer Vision: 3D object/scene understanding, 3D generation, VR/AR, 3D vision+language understanding 3D Human Digitization: Modeling, reconstruction, rendering, biomechanics Generative AI: Explainability, generalization, controllability in generative models, DeepFake detection Biometric Recognition: Face and gait recognition, person re-identification AI + X: Applications in Education and Healthcare Publication Trends: Dr. Liu's recent publications demonstrate a strong focus on advancing biometric recognition systems, particularly in open-set scenarios and video-based person re-identification. His work integrates 3D vision, diffusion models, and large-scale benchmarking, with increasing emphasis on real-world challenges such as aerial-ground integration, long-range recognition, and controllable synthetic data generation for training robust models. Scientific Recognition: Area Chair for BMVC 2025, ACM MM 2025, FG 2025, IJCNN 2025 Area Chair for FG 2024 Advising and Engagement: Dr. Liu is actively recruiting PhD students and interns, indicating an expanding research group. He regularly presents at major conferences including CVPR, NeurIPS, and WACV, and participates in workshops such as ELFA, demonstrating active engagement with the research community. His collaborations span multiple institutions, including Michigan State University, Queensland University of Technology, and others. Labs and Teams: While specific lab names are not mentioned in the provided texts, Dr. Liu leads a research group focused on computer vision and AI, with projects involving 3D reconstruction, biometrics, and generative models. His work on AG-VPReID and HAMoBE suggests leadership in developing large-scale benchmarks and hierarchical recognition systems.