Dimitris Tzionas is an Assistant Professor for 3D Computer Vision at the University of Amsterdam (UvA), leading research in the intersection of Computer Vision, Computer Graphics, and Machine Learning. His work focuses on modeling human-object interactions, 3D/4D perception, and synthesis for applications in Ambient Intelligence, Virtual Assistants, and the Metaverse. He holds an ERC Starting Grant (€1.5M) and ELLIS Amsterdam affiliations. Previously, he was a Research Scientist at Max Planck Institute for Intelligent Systems (MPI-IS), contributing to projects like the GRAB dataset and MANO/SMPL body models. He earned his PhD from the University of Bonn on hand-object interaction, advised by Jürgen Gall, and completed his MSc at Aristotle University of Thessaloniki in Electrical & Computer Engineering. His research has produced impactful datasets (e.g., GRAB, InterCap, DAMON) and methods like InteractVLM and PICO, advancing human-centric AI. He actively serves on CVPR/ICCV/ECCV committees and teaches 'Introduction to Computer Vision' at UvA. Notable awards include NVIDIA grants, Google Research Gifts, and multiple Outstanding Reviewer recognitions. His lab collaborates widely, advising over 10 PhD/MSc students and postdocs, with projects funded by ERC, ELLIS, and industry partners like NVIDIA and Google. Key themes include 3D reconstruction, interaction modeling, and generative AI for realistic avatar creation.
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.
Farnam Jahanian is President and Professor of Computer Science and Robotics at Carnegie Mellon University. His research develops algorithms for controlling dynamic physical systems in robotics and animation, including human motion synthesis, robotic manipulation, and simulated clothing/fluid dynamics. Current work explores motion planning for humanoid robots using motion capture data and physical simulations. Recent publications (2024-2025) focus on kinematic motion retargeting, volumetric hairstyle capture, synthetic data for action recognition, and facial expression translation for robots. His lab integrates computer graphics with robotics to create realistic virtual characters and adaptive control systems.
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
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.
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.
Carol Luckhardt Redfield is a Professor of Computer Science at St. Mary's University with industry experience at Southwest Research Institute and Mei Technology Corporation. She directs educational initiatives in computer gaming and technology camps, and developed the Graduate Certificate in Educational Computer Gaming program. She holds a Ph.D. (1989) and two M.S. degrees (1982) from the University of Michigan. Her research integrates computer gaming, intelligent tutoring systems, and AI in education, with applications in K-12 outreach and space education. Awards: San Antonio Women's Hall of Fame (1992) Multiple Partner-of-the-Year awards for STEM outreach National Space Society education awards She chairs major conferences including Artificial Intelligence in Education (2001) and organized the university's Ultimate Frisbee program.
César Blecua Udías is a Professor and Subdirector at the Escuela Superior de Enseñanzas Técnicas (Architecture) at Universidad CEU Cardenal Herrera in Valencia. He holds a PhD in Architecture (2017) and teaches courses such as Structural Mechanics, Steel Structures, and New Technologies in Dentistry. His research focuses on computational methods for physical process modeling, including software development for architectural structures, CFD simulations, and GPU-accelerated graphics. He coordinates university choirs and chamber orchestras, reflecting his interdisciplinary engagement. Education: Bachelor of Architecture: Escuela Técnica Superior de Arquitectura, Universidad Politécnica de Valencia (2004) PhD in Architecture: Universidad CEU Cardenal Herrera (2017, Summa Cum Laude) Research Interests: His work bridges architecture and computing, developing tools for structural analysis, thermal simulations in Mediterranean courtyards, radiosity lighting algorithms, and hardware-accelerated image compositing. He is part of the 'Métodos computacionales para la modelización de procesos físicos' research group, focusing on quadrilateral meshing and finite element method implementations. Grants/Advising: Supervised the doctoral thesis 'Análisis computacional de mallados cuadrangulares en geometrías complejas para implementación en el método de los elementos finitos.' Labs/Teams: Leads the 'Putthephysicsinthecomputer' computational methods group and coordinates the university's Orfeón and Camerata (choir and chamber orchestra).
Dr. Chris Child is a Senior Lecturer in the Department of Computer Science at City, University of London, and currently serves as the Associate Dean for Employability and Engagement since 2020. He leads initiatives such as virtual internships, client-based projects, and the Last Mile training program in collaboration with Accenture. As a researcher, he focuses on AI-driven game agents, employing techniques like reinforcement learning and approximate dynamic programming. Additionally, he founded Childish Things Ltd., a computer game company, and pioneered City’s first Data Science apprenticeship program. His academic journey includes a PhD in Approximate Dynamic Programming from City, University of London (2011), alongside leadership in game development and industry-academia partnerships. His educational background encompasses a BSc in Computer Science and Software Engineering (University of Birmingham, 1993), MSc in Cognitive Science (University of Birmingham, 1994), and a PGDip in Academic Practice (City, University of London, 2004). Professional memberships include the British Computing Society and IEEE. Research interests center on intelligent agents for games, robotics, and healthcare applications. Notable projects include the Cricket Captain game series, virtual laparoscopic training tools, and emotion-based reward systems for AI agents. His work bridges academic research with industry, emphasizing practical applications of AI in gaming and education. Advising and grants are not explicitly detailed, but his role in apprenticeship development highlights his commitment to student employability. His company Childish Things Ltd. exemplifies full-stack game development expertise, from design to marketing. Future research aims to integrate agent research into commercial games and improve software engineering practices in gaming.
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.
Ifigeneia Mavridou is a Researcher at Bournemouth University's Faculty of Media and Communication , affiliated with the Centre of Digital Entertainment and collaborating with Emteq Ltd. Her work focuses on Virtual Reality and Affective Human-Computer Interaction (HCI) , leveraging physiological signals like EEG, EMG, and PPG for emotion detection. Education : MA in Art, Virtual Reality and Multi-user Systems (University Paris-8 & Athens School of Fine Arts, 2014); PhD in Affective State Recognition in Virtual Reality (Bournemouth University, 2021) Her research explores the intersection of New Media Art and VR to identify emotional features that enhance immersive experiences and VR content re-playability . Current projects involve developing OCOsense™ smart glasses for facial expression recognition and AVEL (Affective Virtual Environment Library) for emotion analysis. Recent publications highlight trends in VR-based emotion detection , wearable sensor integration (optomyography, EMG, PPG), and applications in mental health and clinical research . She is supported by an EPSRC grant for her work on affective VR systems. Collaborative efforts include supervision by Dr. Emili Balaguer-Ballester, Dr. Alain Renaud, Dr. Anna Troisi, Dr. Ellen Seiss, and Dr. Charles Nduka. She has participated in over 20 new media art exhibitions across Europe since 2005.
