Prof. Dr. Alexander Marbach is a Professor in the Creative Content Design department at the Faculty of Media, Mittweida University of Applied Sciences. He teaches courses in game development, virtual production, and interactive media design, and has led "beta," Germany's largest game development project in higher education, since 2013. His research focuses on the intersection of creative technologies and artificial intelligence. Key areas include: Realtime Graphics & Interaction : motion capture, virtual production, and game development. Applied AI in Computer Graphics : procedural content generation, image/video synthesis, and automated 3D environment creation. Assessment and Media Didactics : automated assessment methods and intelligent tutoring systems for digital education. VFX Production : leveraging AI techniques (e.g., Video2Video, NeRFs, Gaussian Splatting) for visual effects. Prof. Marbach is a founding member of "Games&XR Mitteldeutschland eV" and the "RAL Gütegemeinschaft Serious Games". He serves on expert committees for the German Computer Game Award and the R42 Mentoring Program, and provides academic advisory services to external universities.
Li Kunyi is a researcher at the Chair of Computer Science Applications in Medicine at the Technical University of Munich . Their work bridges computer science and medical imaging, focusing on advanced 3D reconstruction and scene understanding techniques. Research Interests: Computer Vision 3D Reconstruction Medical Imaging SLAM (Simultaneous Localization and Mapping) Deep Learning for Graphics Optical Engineering Article Trends: Recent publications emphasize Gaussian splatting for open-vocabulary 3D modeling, 4D SLAM for dynamic environments, and implicit surface reconstruction using monocular cues. Applications span both robotics and medical imaging, with a focus on real-time systems and semantic scene understanding.
Prof. Marielle Stoelinga is a Professor at the University of Twente, Netherlands, working within the Electrical Engineering, Mathematics and Computer Science faculty in the Formal Methods and Tools department. She leads significant research initiatives in formal methods with applications to safety, security, and reliability engineering. Her research spans predictive maintenance , fault tree analysis , attack tree modeling , and the integration of safety and security through formal methods. She focuses on applying big data analytics to predict system failures, with particular emphasis on critical infrastructure including railway systems, satellite missions, and nuclear reactors. Her work bridges theoretical formal methods with practical applications in asset management. Analysis of her recent publications reveals a strong trend toward integrating safety and security analysis through attack-fault-defense trees, developing formal frameworks for risk assessment, and applying model checking techniques to real-world maintenance problems. Her research increasingly addresses the human and organizational aspects of predictive maintenance systems while maintaining rigorous formal foundations. 5 million euros research grant from Dutch National Organization for Scientific Research (NWO) for PrimaVera project Prof. Stoelinga leads the PrimaVera research project ( Predictive maintenance for Very effective asset management ), which takes a holistic approach to predictive maintenance spanning sensor systems, data science, maintenance optimization, and human factors. Her research group actively contributes to formal methods applications in critical infrastructure sectors including energy, transportation, and aerospace.
Mojtaba Bemana is a researcher in the Computer Graphics department at the Max Planck Institute for Informatics, Saarbrücken, Germany, specializing in neural rendering, virtual reality displays, and computational photography. His work bridges computer graphics and vision with deep learning applications. His academic background includes: Ph.D. in Computer Science from Universität des Saarlandes and Max Planck Institute for Informatics (2018-2023) M.Sc. in Electrical Engineering from Sharif University of Technology, Iran (2014-2016), thesis: 'Novel view synthesis using the Light Field camera' supervised by Dr. Arash Amini B.Sc. in Electrical Engineering from Shiraz University, Iran (2010-2014) Dr. Bemana's research focuses on high dynamic range imaging , neural radiance fields , and perception-aware image processing . He develops novel techniques combining classical computer graphics with deep learning for real-time rendering, image quality assessment, and video enhancement. His methodology emphasizes perceptual accuracy and computational efficiency in virtual reality applications. Analysis of his 12 publications (2019-2025) reveals a strong trajectory toward diffusion-based HDR generation , real-time radiance field rendering , and self-supervised video processing . Key trends include the integration of physics-based models with neural networks for refractive effects, dual-exposure sensor optimization, and perceptual quality metrics that eliminate reference image dependencies. He actively contributes to the Saarbrücken Research Center for Visual Computing, Interaction and Artificial Intelligence (VIA) and the European Laboratory for Learning and Intelligent Systems (ELLIS Unit SAM), collaborating on cutting-edge visual computing projects within the Saarland Informatics Campus ecosystem.
Dr. Yi Mei is an Associate Professor and Associate Dean (Research) at the Faculty of Engineering, Victoria University of Wellington, New Zealand. He serves as Programme Director for Computer Science & Computer Graphics within the School of Engineering and Computer Science and is affiliated with the Centre for Data Science and Artificial Intelligence (CDSAI). Dr. Mei's research focuses on evolutionary computation for combinatorial optimisation , with specific expertise in genetic programming , automatic algorithm design , explainable AI , and multi-objective optimisation . His work bridges theoretical foundations with practical applications in transportation, healthcare, manufacturing, and aquaculture. His publication portfolio shows a clear trajectory toward increasingly complex real-world applications of evolutionary computation, with recent work focusing on emergency medical dispatch optimization , dynamic transportation systems , and explainable AI for routing problems . The research demonstrates strong interdisciplinary connections between evolutionary computation, machine learning, and domain-specific optimization challenges. Victoria University of Wellington Ki te Pae - Research Excellence Award 2024 Multiple Best Paper Awards at ACM Genetic and Evolutionary Computation Conference (GECCO) from 2022-2024 HUMIES Silver Award at GECCO 2023 IEEE Transactions on Evolutionary Computation Outstanding Associate Editor (2024, 2025) Fellow of Engineering New Zealand and IEEE Senior Member Dr. Mei has successfully supervised numerous PhD and Master's students whose research has received recognition, including the ACM SIGEVO Dissertation Award. He leads significant research projects funded by MBIE Endeavour Smart Idea Fund ($1M NZD), New Zealand Royal Society Catalyst Leaders Fund ($150K NZD), and industry partners like Honda Research Institute Europe. His service contributions include editorial roles for top journals including IEEE Transactions on Evolutionary Computation and leadership positions in IEEE Computational Intelligence Society. Dr. Mei leads the Evolutionary Computation for Combinatorial Optimisation Group (ECCO) and the Evolutionary Computation and Machine Learning Research Group (ECRG) at Victoria University of Wellington. He also chairs the IEEE Taskforce on Evolutionary Scheduling and Combinatorial Optimisation (TESCO), fostering international collaboration in evolutionary computation applications.
Kirsten Hermes serves as Senior Lecturer in Music Performance Technology at the University of Westminster since 2016, merging academic research with professional practice as electronica artist Nyokee. Her work bridges psychoacoustic engineering, electronic music performance, and creative technology development. Her educational foundation includes an EPSRC-funded PhD in Sound Recording and Psychoacoustic Engineering from the University of Surrey, where her thesis focused on spectral clarity predictors in music mixes. Research centers on automatic music mixing tools and spectral clarity modeling , expanding into AI's impact on creativity, virtual artist identities, and chiptune culture. Recent work examines pandemic adaptations in online music communities and audiovisual integration in live electronic performance, emphasizing practical applications for musicians. Analysis of her 15 most recent publications (2021-2025) reveals an evolution from core psychoacoustic research toward interdisciplinary exploration of AI, virtual performance, and cultural adaptation in electronic music. Key trends include human-AI collaboration frameworks, chiptune's digital resilience, and the role of 3D avatars in artist identity construction. She currently supervises doctoral researcher Clara Colotti, whose thesis investigates audiovisual expansion of orchestral cultural scope. While specific grant details aren't provided, her EPSRC-funded PhD demonstrates research funding capability. Affiliated with the university's Music Research Group, she actively engages the electronic music community through Nyokee performances at MAGfest, Comic Con, and Hyper Japan, blending academic inquiry with stage practice.
Niko Sünderhauf is a Professor in the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT), specializing in robotics, computer vision, and autonomous systems. His research spans visual place recognition, simultaneous localization and mapping (SLAM), neural radiance fields, and out-of-distribution detection for robotics applications. His research interests focus on enabling robots to understand and navigate complex environments through advanced computer vision techniques. He has made significant contributions to visual place recognition, particularly for handling viewpoint and environmental changes. His work on switchable constraints has improved robustness in SLAM systems, while his more recent research explores neural radiance fields, Gaussian splatting, and integrating large language models with robotic perception. Prof. Sünderhauf's publication record demonstrates consistent research productivity with 115 publications spanning from 2005 to 2025. His recent work shows a clear progression from traditional SLAM techniques toward more advanced neural scene representations and integration with large language models. His research has been published in top venues including IEEE ICRA, CVPR, IROS, and the International Journal of Robotics Research. Among his scientific contributions are novel approaches to visual place recognition that work across seasons and viewpoints, robust SLAM techniques that handle outliers and non-linearities, and recent innovations in neural scene representations for robotics. His work on switchable constraints has been particularly influential in the robotics community. Prof. Sünderhauf actively supervises PhD students including Dimity Miller, Krishan Rana, and Jad Abou-Chakra, who frequently appear as first authors on publications. His collaborative network includes researchers from QUT and international institutions, demonstrating strong research leadership in the robotics community.
Dr. Jaehong Kim has been appointed as an Assistant Professor in the Department of Artificial Intelligence Engineering at the College of Software Convergence, Inha University, effective September 1, 2025. He is currently transitioning from a postdoctoral position at Carnegie Mellon University's Department of Computer Science. His educational background includes: Ph.D. from KAIST (August 2024) Dr. Kim's research focuses on Artificial Intelligence applications in video streaming, immersive media, and network systems. His work includes neural network-based video quality enhancement, 3D live streaming, 5G network optimization, and 3D Gaussian Splatting compression. He has made significant contributions to AI-driven media delivery systems, with particular emphasis on real-time transmission protocols and neural rendering techniques for immersive experiences. His notable scientific awards include: Gold Prize (1st place in Communications and Networks) at 2022 Samsung HumanTech Paper Awards KAIST Breakthrough of the Year in 2021 Dr. Kim's research has been supported by the National Research Foundation of Korea's Overseas Outstanding Young Researcher Program during his postdoctoral fellowship at CMU. His work has been presented at premier conferences including SIGCOMM, CoNEXT (Best Paper Finalist), OSDI, and EuroSys, establishing him as a rising expert in AI-enhanced networked media systems.
Jun-Yan Zhu is the Michael B. Donohue Assistant Professor of Computer Science and Robotics at Carnegie Mellon University's School of Computer Science. He holds affiliated faculty roles in the Computer Science Department and Machine Learning Department. His research focuses on generative models, computer vision, graphics, and computational photography. Education: Ph.D., UC Berkeley (2017), advised by Alexei A. Efros B.E., Tsinghua University (2012), advised by Zhuowen Tu, Shi-Min Hu, and Eric Chang Postdoc, MIT CSAIL (2017–2018), with William T. Freeman, Josh Tenenbaum, and Antonio Torralba Research Interests: Zhu's work explores the synergy between human creators and generative models. Key areas include: - Controllable Visual Synthesis : Developing algorithms for precise image/video editing and generation. - Model Customization : Enabling users to adapt models for new tasks/concepts with minimal input. - Data Attribution : Addressing ethical challenges in synthetic data usage. - 3D/Neural Rendering : Advancing techniques for 3D object synthesis and tactile integration. His lab, Generative Intelligence Lab , emphasizes human-AI collaboration and practical applications like NVIDIA Canvas and Adobe Firefly. Articles Trends: Recent work spans 3D object generation (LEGO designs), efficient diffusion models (SVDQuant), tactile-aware 3D synthesis, and ethical data attribution systems. His research balances technical innovation with user-centric design, often bridging theory and industry applications. Awards: ACM SIGGRAPH Outstanding Doctoral Dissertation (2017) CVPR Best Paper Finalist (2022), ICRA Best Paper (2024) NVIDIA GTC Best in Show (2019) for GauGAN Advising & Grants: Supervises 10+ PhD students across CMU Robotics (RI), Machine Learning (MLD), and Computer Science (CSD). Active in NSF grants and industry collaborations (Adobe, NVIDIA). His lab hosts the Generative Intelligence Lab , part of CMU Graphics Lab and Computer Vision Group.
James Tompkin is an Associate Professor in the Department of Computer Science at Brown University, specializing in visual computing. His research focuses on computer graphics, computer vision, and human-computer interaction, with an emphasis on techniques for image/video creation, editing, analysis, and interaction. His lab develops methods for scene reconstruction (especially from multi-camera systems), dynamic scene modeling, and applications in 2D, multi-view, and VR/AR displays. Research interests include neural radiance fields (NeRFs), Gaussian splatting, time-of-flight sensing, and generative adversarial networks (GANs). He has collaborated extensively with industry partners (Adobe, Amazon, Meta) and received funding from NSF, DARPA, NASA, and UK/EPSRC. His work is disseminated via top-tier venues like CVPR, SIGGRAPH, and ECCV. Teaching includes visual computing topics, and his lab maintains active projects on GitHub and project webpages. Office hours are held weekly, with scheduling via Google Calendar integration.
Professor Kenny Mitchell is a faculty member at the School of Computing Engineering and the Built Environment at Edinburgh Napier University. With over 60 research outputs listed, he specializes in Interactive Graphics, Virtual Reality, and Augmented Reality technologies. Research Interests Mitchell's work focuses on real-time systems, motion prediction, and human-computer interaction in immersive environments. His research spans generative AI environments , 3D facial reconstruction , and light field rendering . Key themes include AI-driven animation , networked VR experiences , and haptic-visual integration . Article Trends Recent publications emphasize Transformer-based motion prediction (NeFT-Net), speech-to-VR systems (HoloJig), and low-latency avatar synchronization . His work integrates machine learning with computer graphics for applications in telepresence dance and emotionally intelligent avatars . Projects CAROUSEL+ : £929,077 funded by European Commission (2021-2024) for telepresent dance systems DISTRO : £243,804 European Commission grant for 3D graphics training (2015-2018)
Becky Lake is an Adjunct Professor of Graphic and Media Design at Marymount University and Producer of Volumetric Content at the Institute for IDEAS. She holds a BA in Graphic Design with minors in History and Illustration from an unspecified institution and will complete her MFA in Film and Media Arts at American University in May 2024. Her research explores the intersection of traditional and emerging media forms: Documentary storytelling through film photography and immersive formats Development of volumetric content creation techniques Interactive narrative structures in virtual reality environments Cross-disciplinary approaches to visual storytelling Her recent publications focus on experimental applications of immersive technologies in sports training, theatrical performance, and narrative experiences, demonstrating consistent innovation in mixed-reality applications.
Sebastian Wohner is a researcher at the Chair of Computer Graphics and Visualization (Prof. Westermann) at the Technical University of Munich. His work focuses on advanced visualization techniques, machine learning applications in graphics, and GPU-accelerated algorithms for 3D design and simulation. He actively contributes to projects such as the NVIDIA CUDA Research Center and ERC-funded initiatives like SaferVis and realFlow, emphasizing real-time liquids and safer visualization systems. His research interests span 3D Gaussian splatting, topology optimization, neural fields for statistical dependencies, and spatio-temporal flow visualization. He has pioneered methods for compressing meteorological ensembles and accelerating novel view synthesis in consumer devices. Wohner also explores GPU-based linear algebra optimizations and efficient rendering techniques for ribbons and twisted lines. In teaching, he leads courses on game physics, visual data analytics, deep learning in computer graphics, and topology optimization. Notable contributions include the development of the Particle Engine and Bunny Demo applications, as well as advancements in differentiable rendering and robotic perception systems. His work bridges theoretical foundations with practical implementations in both academia and industry.
Monika Roznere is an upcoming Assistant Professor of Computer Science at Binghamton University, starting Fall 2024. Currently, she is completing her Ph.D. in Computer Science at Dartmouth College where she is a member of the Reality and Robotics Lab (RLab) under the supervision of Alberto Quattrini Li. Her academic journey began with a B.S. in Computer Science and a minor in Graphic Design at Binghamton University. Upcoming Assistant Professor, Binghamton University (Fall 2024) Ph.D. Candidate, Dartmouth College Member, Reality and Robotics Lab (RLab) Head, Marine Robotics Lab (upcoming) Monika's research focuses on enabling accessible robots to explore unmapped and poorly understood environments, particularly underwater ecosystems. Her work bridges the gap between theoretical robotics and practical environmental applications, with emphasis on perception systems that can operate in challenging aquatic conditions where traditional sensors fail. She develops novel methods for 3D reconstruction, sensor fusion, and navigation that specifically address the unique challenges of underwater environments including light absorption, scattering, and limited localization capabilities. Analysis of her publication record reveals a consistent research trajectory focused on underwater perception systems. Her work shows progression from foundational techniques like image color correction (2019) to more complex multi-sensor integration (2020) and sophisticated 3D reconstruction frameworks (2023). The publications demonstrate her ability to tackle real-world challenges in underwater robotics with practical, field-tested solutions using low-cost sensor configurations. Her research consistently emphasizes deployable systems that can operate in real ocean environments rather than controlled laboratory settings. While no formal scientific awards are mentioned in the available information, her publications in top-tier robotics conferences (ICRA, IROS, ISER) indicate recognition by the robotics research community. Her GitHub profile shows active contributions to open-source robotics projects, particularly related to Blue Robotics sonar systems, suggesting strong community engagement. As an upcoming faculty member, Monika will establish the Marine Robotics Lab at Binghamton University, focusing on accessible underwater exploration technologies. Her interdisciplinary approach combines computer science, robotics, and environmental monitoring, with potential applications for ocean conservation and scientific discovery. The lab will likely continue her work on multi-sensor integration for underwater robots, with emphasis on practical, deployable systems that can operate in challenging real-world conditions.
Jean Botev is a Research Scientist and co-head of the Collaborative and Socio-Technical Systems (COaST) group at the University of Luxembourg's Faculty of Science, Technology and Medicine. He directs the VR/AR Lab, focusing on immersive technologies and human-centered design. His work bridges physical and digital realities through mediated reality approaches, emphasizing collaborative virtual environments and interaction techniques. Dr. Botev holds a PhD in Computer Science (2011, University of Luxembourg) and master's/bachelor's degrees from the University of Trier (Germany). He teaches courses in Virtual/Augmented Reality, Immersive Media, and programming disciplines across multiple university programs. His research spans 85+ peer-reviewed publications, with notable contributions to IEEE VR, ACM IVA, and TVCG. He leads €5M+ in grants, including the EU H2020 FET Open ChronoPilot project (€3M) exploring time perception modulation. Awards include the 2024 EuroXR Best Demonstration Award and multiple best paper recognitions. Botev actively engages in public outreach, organizing events like ACM SIGGRAPH Asia Demo Scene and promoting ethical design principles. His work integrates socio-technical systems, human factors, and interdisciplinary collaboration to advance immersive technology applications in education, cultural heritage, and healthcare.
