Daniel Webster is a Senior Lecturer in Games and Visual Effects at Staffordshire University's School of Digital, Tech, Innovation & Business. With a background spanning the games industry and academia, he specializes in 3D art, animation, and game design pipelines. His expertise includes 3D sculpting, character modeling, environment design, and Unreal Engine 4 implementation. Education: MSc (Hons) 3D Computer Games Design, Staffordshire University Postgraduate Certificate in Higher and Professional Education, Staffordshire University BSc (Hons) Computer Games Design, Staffordshire University Research & Teaching Focus: Daniel teaches modules like 'Advanced Vehicles and Weapons Prototyping' and 'Realtime Character Art and Production,' emphasizing 3D modeling pipelines, motion capture integration, and physially based rendering. His work bridges academic theory with industry practices, including collaborations on indie and AAA game titles. He holds a Fellowship of the Higher Education Academy (FHEA) and has contributed to Staffordshire University's recognition for research impact ('Outstanding/Very Considerable' per The Times 2023) and teaching quality. Though no personal awards are listed, his institution has received accolades for facilities and social inclusion (Whatuni 2023). Additional Roles: Daniel combines teaching with freelance 3D artistry and event management for games development, leveraging international experiences from China and Africa to inform his pedagogy.
Andreas Paul is a Researcher affiliated with the Department of Computer Science (Informatik V) at the Technische Universität München (TUM), part of the TUM School of Computation, Information and Technology. His research focuses on real-time visualization, computational geometry, and flight simulation systems. He contributed to the FORTWIHR project, developing synthetic vision systems for aircraft, demonstrating expertise in adaptive algorithms and terrain triangulation. Collaborations include work with the TU Braunschweig and ESG, highlighting interdisciplinary engagement. His academic background includes a Master's thesis (1995) and a PhD dissertation (2000) on hierarchical data structures and terrain modeling. Professional activities include conference participation and contributions to visualization technology for aviation applications. Education: PhD in Computer Science, TU Munich, 2000 Master's Thesis: 'Compression of image sequences with hierarchical bases', 1995 Research interests emphasize practical applications of computational methods in aviation and geospatial systems, with a strong focus on real-time performance and algorithmic efficiency. His work bridges computer graphics, geographic information systems, and aerospace engineering, addressing challenges in synthetic vision and terrain data representation.
Olga Gutan is a doctoral student at Carnegie Mellon University 's Computer Science Department , affiliated with the Geometry Collective and advised by Keenan Crane . Her work focuses on computer graphics and geometry processing , with a primary research interest in vectorization and surface algorithm development. Current role: Doctoral Research Assistant Past work: Nonmanifold Minimal Surfaces with mentors Etienne Vouga, Nicholas Sharp, Josh Vekhter Her research bridges theoretical geometry and practical implementation, with publications on singularity-free frame fields for vectorization and exploratory work on gravitational surface rendering in Houdini. She received an Honorable Mention for Best Paper at Symposium on Geometry Processing 2023. Olga contributes to algorithm development and visualization techniques, including triply-periodic nonmanifold surfaces. Scientific Awards : Best Paper (Honorable Mention), Symposium on Geometry Processing 2023 Key Collaborations : Mentored by Etienne Vouga, Nicholas Sharp, and Josh Vekhter during summer 2021. Affiliated with the Geometry Collective at Carnegie Mellon.
Robert Krueger is an Assistant Professor in the Department of Computer Science & Engineering at NYU Tandon School of Engineering, and a member of the Visualization Imaging and Data Analysis Center (VIDA) at NYU. Previously, he held a joint postdoctoral appointment as a Senior Research Scientist and Subgroup Lead at Harvard University's Visual Computing Group (VCG) and Laboratory of Systems Pharmacology (LSP). His research focuses on scalable visualization and visual analytics for spatial and multivariate data, particularly in biomedical and geographical applications like smart cities and cancer tissue analysis. Education: Ph.D. in Computer Science (Dr. rer. nat.), University of Stuttgart, 2017 M.S. in Computer Science and Media, Stuttgart Media University, 2012 B.S. in Media and Communication Informatics, Reutlingen University, 2008 Research Interests: Krueger specializes in integrating machine learning with interactive visual interfaces to enable human-in-the-loop analysis of large biomedical and spatial datasets. He designs tools for multiplexed imaging data exploration, spatial biology, and geospatial dynamics. His work emphasizes interdisciplinary collaboration to address challenges in smart cities, immuno-oncology, and data standardization (e.g., MITI guidelines). Organization Committees: He actively contributes to the VIM (Visualization and Image Data Management) monthly meetings and the Spatial Biology Association (SBA), advancing data interoperability and spatial biology applications. His teaching accolades include multiple Harvard Excellence in Teaching Awards. Grants and Advising: As a subgroup leader since 2021, he manages research collaborations between VCG and LSP. He has supervised 14 student trainees/researchers on projects like CIMPLEX and HTAN. His team develops open-source tools like Minerva and Scope2Screen. Labs/Teams: Affiliated with VIDA at NYU and VCG/Harvard Medical School. He leads visualization efforts in the Human Tumor Atlas Network (HTAN), funded under the NCI Cancer Moonshot Initiative.
Dr. Miaomiao Liu is a Research Fellow at the School of Computing, The Australian National University. Her research focuses on computer vision, 3D reconstruction, and neural rendering, with applications in robotics, autonomous systems, and renewable energy forecasting. She leads multiple projects including Next-Generation Aviation Safety Net Air Traffic Management, Machine Vision Techniques for Solar Power Forecasting, and 3D Vision Geometric Optimization in Deep Learning. Her work integrates cutting-edge techniques such as neural radiance fields, depth estimation, and self-supervised learning to address challenges in dynamic scene reconstruction, motion forecasting, and image deblurring. She has pioneered methods for mining supervision signals in dynamic regions and developing language-driven deblurring networks. Key Projects: Aviation safety systems, solar irradiance prediction, and geometric optimization in deep learning Research Themes: 3D scene understanding, human motion prediction, and neural rendering Technical Expertise: Neural networks, multi-view stereo, and physics-based modeling Dr. Liu's research has been published in top-tier venues like CVPR and IEEE conferences, with over 2,450 citations. While not explicitly listed as part of a lab, her work demonstrates strong collaboration with industry partners such as CSIRO and aerospace stakeholders. She actively supervises research students in areas like 3D vision and energy systems.
Corey Toler-Franklin is an Assistant Professor in the Computer Science Department at Barnard College, Columbia University, directing the Graphics, Imaging & Light Measurement Lab (GILMLab). Her research focuses on computer graphics, vision, and machine learning applications in biomedical research, oncology, and archaeology. She holds a Ph.D. in Computer Science from Princeton University and has held positions at UC Davis, Adobe, and Google. Education: Ph.D., Computer Science, Princeton University (2011) M.S., Architecture & Computer Graphics, Cornell University (2000) B.Arch., Cornell University (1999) Research Interests: Developing algorithms for capturing and analyzing complex materials' shape/appearance through optics principles. Applications include diagnosing metastatic cancers, studying neurological disorders, and restoring cultural heritage artifacts. Expertise spans machine learning, multispectral imaging, and non-photorealistic rendering. Awards: 2009 Google Anita Borg Award NSF iDigBio Visiting Scholar (2013) First African American Ph.D. in Computer Science at Princeton Grants & Labs: Leads GILMLab, collaborating with oncology/pathology experts. Former UC President’s Postdoctoral Fellow. Active in 3D digitization projects for STEM education and museum conservation. Labs/Teams: Graphics, Imaging & Light Measurement Lab (GILM Lab) at Barnard, previously affiliated with UC Berkeley CITRIS Banatao Institute.
Dr Anthony Bukowski is a Senior Lecturer and Programme Leader for the BSc Computer Animation & Visual Effects at Manchester Metropolitan University's Computing and Mathematics Department. He specializes in FX rendering, procedural systems, and VFX integration, with industry collaborations through Knowledge Transfer Partnerships (KTP). His academic roles include external examining at Leeds Beckett University and Nord University. Education: PhD, BSc, Fellow of the Higher Education Academy (FHEA) Notable Achievements: Multiple teaching award nominations, 'Outstanding' KTP completions (2013, 2018) Research interests focus on dynamic systems in VFX and applied technologies for creative industries. He leads undergraduate programs producing graduates for top studios like Framestore and DNEG. Current supervision includes a doctoral project on predictive models for elderly mobility impairments. Awards: Highlighted teaching excellence and industry-linked research impact
Chris Risher is an Associate Professor in the Department of Biomedical Sciences at Marshall University. His research investigates astrocyte-mediated regulation of synaptic development and its implications for neurodevelopmental disorders. The lab employs transgenic mouse models, in vitro systems, and high-resolution 3D reconstructions to study synaptic maturation. Research focuses on identifying molecular pathways linking astrocytes to synaptic structures disrupted in autism, schizophrenia, and addiction. Recent publications (2021-2025) examine synaptic quantification methods, astrocyte morphology changes following opioid exposure, and mesolimbic pathway alterations. Laboratory personnel include PhD candidates and undergraduate researchers. Current projects investigate thrombospondin signaling, dendritic spine analysis, and developing novel therapeutic strategies for synaptic disorders.
Elena Molina Lopez is a researcher at the Department of Computer Science within the Barcelona School of Informatics at Universitat Politècnica de Catalunya · BarcelonaTech (UPC), actively contributing to the ViRVIG research group focused on visualization, virtual reality, and graphical interaction. Her work develops immersive analytics systems for molecular visualization and 3D interaction techniques. Her academic background includes: PhD in Computer Science (thesis: 'Advanced Interaction in Immersive Analytics Systems for Molecular Visualizations') Her research spans virtual reality, molecular visualization, 3D interaction, data visualization, human-computer interaction, and computer graphics. She investigates user perception in visualization techniques, with recent work addressing molecular atom selection accuracy, heatmap color palette effects, and statistical visualization design guidelines. Her publications demonstrate technical innovation through user studies and system development. Analysis of her 2020-2024 publications reveals consistent contributions to top venues like Computers & Graphics and EuroGraphics, with emphasis on VR interaction techniques for molecular structures and perceptual studies in data visualization. Key trends include improving selection accuracy in immersive environments and establishing evidence-based design principles. She collaborates extensively on research projects including 'Entornos 3D de alta fidelidad para Realidad Virtual y Computación Visual', working with prominent researchers such as Pere Pau Vazquez (8 collaborations), Nuria Pelechano, and Alejandro Rios across health, architecture, and urban applications. As a core member of the ViRVIG research group, she participates in a dynamic team advancing visualization technologies through interdisciplinary approaches and industry partnerships.
Xiaoyi Jiang is a Professor at the Institute of Computer Science at the University of Münster, leading the Jiang Lab focused on Pattern Recognition and Image Analysis. He holds roles in the CiM-IMPRS Graduate Programme Management Board and participates in projects like the Multiscale Imaging Centre. His research emphasizes biomedical image analysis, machine learning, and medical applications such as tumor segmentation, vessel network extraction, and automated tracking systems for small organisms. Key contributions include FIMTrack software for locomotion analysis, the Voreen visualization framework, and complex-valued neural network architectures. He has authored over 200 papers and holds patents in imaging and segmentation technologies. His work bridges computer science with medical and biological applications, aiming to solve challenges in automated analysis and interpretation of biomedical data.
Dr. Saad Ali Amin serves as the Post-graduate Programme Manager and Principal Lecturer in Network Computing within Coventry University's Faculty of Engineering and Computing. With extensive experience in academic leadership and research, he directs postgraduate programs while maintaining an active research portfolio focused on health informatics and computing technologies. His work bridges theoretical computer science with practical healthcare applications, particularly in biomedical image processing and distributed computing systems. Education: Pg.Cert., Learning and Teaching in Higher Education, Coventry University Ph.D., Computer Science, Loughborough University M.Phil., Computer and Control Systems, Brunel University Dr. Amin's research spans multiple interconnected domains within health informatics and computing. His primary focus centers on the design of biomedical image processing algorithms and multimedia applications for parallel and distributed computing environments, with implementation on Clusters of Workstations (CoW). He has made significant contributions to context-aware multimedia information systems for e-health decision support, creating technological solutions that adapt to user and environmental contexts. His work in parallel processing, particularly with systolic arrays and VLSI implementations, demonstrates a strong foundation in hardware-aware algorithm design. The integration of neural networks with biomedical applications represents another key thread in his research portfolio, showing how advanced computational models can enhance healthcare delivery systems. Analysis of Dr. Amin's publication record reveals a consistent trajectory from foundational work in parallel computing and image processing toward increasingly healthcare-focused applications. His early work (2004-2006) established technical capabilities in medical visualization and knowledge management, while his middle period (2010) demonstrated the application of context-aware systems to e-health decision support. The most recent publications (2011-2013) show expansion into performance evaluation systems, steganography applications, and comprehensive surveys of pervasive healthcare systems. This progression illustrates a researcher who has successfully adapted core computing expertise to address evolving healthcare technology challenges, with particular emphasis on culturally sensitive implementations as evidenced by his work in UAE and Arab contexts. Dr. Amin has secured multiple competitive research grants that reflect the practical impact of his work: Breast cancer detection research funded by BUiD Research Funding (UAE) Parallel computing and medical imaging collaboration with Midlands region hospitals (UK) European Community funding for collaboration with European institutes UNESCO funding as Project Manager for Computerised Documentation Bank Prime Minister Initiative 2 (UK) for Context-Aware Multimedia Information System for e-Health Decision Support Knowledge Exchange and Enterprise Network (KEEN UK) for Reliable and Energy Cognitive Radio Multichannel MAC Protocol development As an academic leader, Dr. Amin has supervised 4 completed PhD students with 3 currently under supervision. His professional service includes membership on the IEEE Committee for Signal Processing Chapter for the UK and Ireland, Vice-Chairmanship of the British Computer Society/Middle East section, and roles on the Executive Council of Dubai Government Excellence Projects. He has organized major international conferences including the 4th International Conference on Developments in e-Systems Engineering (DeSE'11) and served on program committees for numerous biomedical engineering and signal processing conferences.
David López Vilariño is a Lecturer at the University of Santiago de Compostela, affiliated with the Department of Electronics. His research focuses on LiDAR data processing, FPGA acceleration for high-performance computing (HPC), and embedded systems. He teaches courses such as Fundaments of Electronic Instrumentation , Heterogenous Programming , and The Physics of Computing , contributing to bachelor’s and master’s programs in Physics, Informatics Engineering, and High Performance Computing. His research interests span LiDAR-based applications in urban planning, infrastructure monitoring, and medical imaging. He has developed algorithms for LiDAR data analysis, FPGA-based motion estimation, and GPU-accelerated medical image processing. Notable contributions include tools like the Open Lidar Visualizer and Analyser for 3D point cloud visualization. Dr. Vilariño’s work bridges computer architecture, signal processing, and geomatics. His recent publications emphasize optimizing HPC workloads using FPGAs and Intel OneAPI, as well as automated LiDAR-based detection of power lines, road points, and pedestrian zones. He collaborates on interdisciplinary projects involving parallel computing, embedded vision systems, and real-time surveillance applications. Teaching responsibilities include coordinating courses for the Máster Universitario en Computación de Altas Prestaciones, a joint program with the University of A Coruña. No academic awards are listed, but his active role in teaching and research grants underscores his contributions to the field.
Vladimir Todorovic is an Associate Professor and Chair of Fine Arts at the School of Design, University of Western Australia (UWA), and a Visiting Professor at the University of Arts Belgrade. His work bridges art, technology, and environmental discourse through immersive storytelling, AI-driven generative art, and experimental film. He has exhibited globally at festivals like Annecy, IFFR, and Ars Electronica, winning over a dozen awards for his innovative projects. Research interests include generative art systems, artificial intelligence aesthetics, virtual reality narratives, and the ethical implications of technology in creative practices. He has organized major events such as ISEA2008 and the Environmental Visions conference (2014), emphasizing interdisciplinary collaboration between artists, scientists, and technologists. Current projects explore AI ethics, Indigenous storytelling through extended reality, and procedural modeling in digital media. Grants: 2023: 'Illustrating Nyangumarta' (AUD 57k) from WA's Department of Local Government 2022: 'Cabinet of Algodreams' (AUD 15k) Awards: 1st Prize Experimental, 19th Athens Animfest (2024) Philip K. Dick Science Fiction Festival Award (2024) Early-Career Research Award, UWA (2022) Labs/Teams: Leads the UWA Fine Arts Lab focusing on experimental digital media and collaborates with Indigenous communities on XR storytelling initiatives.
Dr. Adam Kortylewski leads an Emmy Noether research group at the University of Freiburg's Department of Computer Science. His work focuses on developing robust computer vision systems that reliably understand images under challenging conditions including occlusion, novel viewpoints, and adverse weather. The research combines deep learning with computer graphics to create 3D-aware neural network architectures. Research interests include: Robustness to out-of-distribution scenarios 3D object understanding from 2D images Neural analysis-by-synthesis approaches Occlusion handling in visual recognition Compositional network architectures Adversarial robustness Recent publications demonstrate advancements in self-supervised 3D learning, semantic correspondence, and neural rendering. Articles show consistent focus on improving model robustness through 3D-aware architectures and compositionality. Dr. Kortylewski received prestigious Emmy Noether funding from the German Research Foundation (DFG) to support his work on reliable computer vision. His research has applications in autonomous vehicles, industrial robotics, and safety-critical vision systems.
Dr. Zhidong Xiao serves as Principal Academic (Associate Professor) at Bournemouth University's National Centre for Computer Animation within the Faculty of Media and Communication. With over ten years of leadership experience including roles as Programme Leader, Head of Education, and Deputy Head of Department, he drives academic strategy and research innovation in computer animation and digital media. His work bridges technical excellence with creative industry applications through extensive collaborations across the UK and China. Dr. Xiao's educational foundation includes a PhD in Computer Graphics (2010) and postgraduate certificates in Education Practice (2010) and Research Degree Supervision (2011) from Bournemouth University, complemented by a BEng (Hons) in Thermodynamics from Taiyuan University of Technology, China (1994). PhD in Computer Graphics, Bournemouth University (2010) PGCE in Education Practice, Bournemouth University (2010) PGCE in Research Degree Supervision, Bournemouth University (2011) BEng (Hons) in Thermodynamics, Taiyuan University of Technology (1994) His research spans Computer Graphics, Motion Capture, Artificial Intelligence, and Virtual Reality with focus on physics-based simulation, sign language recognition, and motion synthesis. Recent work integrates partial differential equations with machine learning to solve animation challenges in facial realism, deformation simulation, and 3D reconstruction. His interdisciplinary approach connects computer science with creative industries, healthcare applications, and educational technology while advancing core techniques in neural rendering and motion analysis. Analysis of his 15 most recent publications reveals consistent innovation in physics-based animation techniques (40%), motion capture processing (25%), and neural approaches to 3D reconstruction (35%). Key trends include the fusion of analytical physics models with deep learning architectures, development of efficient real-time simulation methods, and expansion into accessibility applications through sign language recognition systems. Scientific recognitions include: Fellow of British Computer Society (2023) Fellow of Higher Education Academy (2011) Best Poster Award at Pacific Graphics 2014 He maintains active peer review roles for EPSRC, ESRC, IEEE Transactions on Multimedia, and ACM SIGGRAPH conferences. Dr. Xiao has supervised seven PhD students to completion while currently guiding Alexandra Sergeeva Alexdottir's research on Phantom Touch phenomena. His grant portfolio demonstrates strong industry-academia collaboration: Principal Investigator Capturing and representing sign language (British Council, 2025) VE Communication Programme (Erasmus+, 2020) Co-Investigator Rehabilitation Enhancement via Motion Capture (BU Fusion Fund, 2013) Cross-Channel Film Lab (Interreg, 2012) Digital Beijing Opera Project (2010) As a core member of Bournemouth's Computer Graphics and Visualisation Research Group and Centre for Digital Entertainment, he leads initiatives in motion capture technology through AccessMocap Studio. His international outreach includes invited lectures across China on computer animation education and visual effects techniques, strengthening global partnerships in creative technology development.
