Glenn Van Wallendael is an Associate Professor at Ghent University's Faculty of Engineering and Architecture , affiliated with the Department of Electronics and Information Systems . He leads research in video coding, digital watermarking, and immersive media technologies. Academic Focus: Video compression standards (HEVC, H.266), AI for multimedia, virtual reality Key Collaborations: iMinds, imec, European research consortia Research Interests include: Video compression algorithms (HEVC, SVC, MV-HEVC) Digital watermarking for copyright protection Machine learning applications in image/video analysis Quality of Experience (QoE) in immersive environments Recent Publications (2024-2025) show expertise in: Deepfake detection using vision transformers Medical image landmarking tools Lightweight geometric approximation methods AI-driven video quality assessment Doctoral Mentorship includes supervising: 2021: Hannes Mareen (video forensics) 2020: Vasileios Avramelos (light field coding) 2017: Johan De Praeter (adaptive video encoding)
Peter Kery serves as Assistant Professor of Graphic Design in the College of Arts and Sciences at the University of the District of Columbia (UDC), teaching core courses including Typography, Web Design, and Digital Design Applications. He concurrently holds an Adjunct Instructor position at George Mason University while maintaining an active independent design practice. His academic foundation includes: Master Fine Arts in Graphic Design from Vermont College of Fine Arts Bachelor Fine Arts in Graphic Design from The University of the Arts Kery's research investigates visual perception mechanisms through experimental design projects. His "Ambiguous Grey" exhibit demonstrates how contextual framing alters color perception, while the "Colors and Textures" photography project examines sensory interpretation of visual stimuli. These works integrate cognitive psychology principles with graphic design practice, particularly exploring optical illusions, gestalt theory, and perceptual phenomena in digital environments. His YouTube motion narratives further investigate storytelling through temporal visual sequences. Analysis of his recent publications reveals consistent thematic focus on perception mechanics. The 2021 blog series ("Illusion and Perception," "Viewing 2D form 3D") establishes foundational research on visual processing, while newer works like "On lost" and "Visual principles of perception" develop theoretical frameworks. His technical experiments ("Horizontal Scrolling Test," "Javascript Test") bridge perceptual theory with interactive implementation, creating a cohesive research trajectory examining how design choices influence cognitive interpretation. With extensive teaching experience across institutions including University of Minnesota Duluth (2021-23) and Boston University Center for Digital Imaging Arts (2008-14), Kery's professional practice at Harriman Architects (2016-20) informs his applied teaching methodology. His course portfolio spans foundational subjects like Color Theory and Design Principles through advanced topics in Emerging Media, reflecting his commitment to connecting theoretical knowledge with professional design practice.
Chuang Gan is a distinguished researcher holding dual positions as a Principal Research Staff Member at the MIT-IBM Watson AI Lab and an Assistant Professor at the University of Massachusetts Amherst. His work bridges academic research and industrial applications in artificial intelligence, with particular focus on advancing the frontiers of computer vision and multimodal learning systems. Dr. Gan's research interests span multiple interconnected domains within artificial intelligence. He specializes in video understanding, with deep expertise in representation learning, neural-symbolic visual reasoning, audio-visual scene analysis, and embodied intelligence. His work frequently integrates graph deep learning techniques with neuro-symbolic approaches to create more interpretable and robust AI systems. The recurring themes across his research portfolio include developing models that can understand physical dynamics from visual inputs, creating systems capable of embodied reasoning, and building bridges between symbolic and neural approaches to artificial intelligence. His publications reveal a strong trend toward increasingly sophisticated multimodal systems that integrate visual, auditory, and linguistic information. Over time, his work has evolved from basic video understanding tasks to complex embodied reasoning systems capable of physical simulation, 3D scene understanding, and multi-agent collaboration. A notable pattern is the progression from analyzing static scenes to understanding dynamic physical interactions and embodied agent behaviors in increasingly complex environments. Microsoft Fellowship Baidu Fellowship Dr. Gan's research has received significant recognition from major technology companies through prestigious fellowships and has been widely covered by leading media outlets including CNN, BBC, The New York Times, WIRED, Forbes, and MIT Tech Review. His work at the MIT-IBM Watson AI Lab provides him with access to substantial resources for cutting-edge AI research, while his academic position enables him to train the next generation of AI researchers. His collaborations with prominent researchers like Antonio Torralba demonstrate his integration within the top echelons of the computer vision and AI research community. At the MIT-IBM Watson AI Lab, Dr. Gan leads research initiatives focused on advancing video understanding and embodied intelligence. His work contributes to the lab's mission of developing AI systems that can perceive, reason about, and interact with the physical world in more human-like ways. His research group likely focuses on developing novel architectures for multimodal learning, creating benchmarks for physical reasoning, and building systems that can transfer knowledge between simulation and real-world environments.
Konstantin Nikolaevich Kasyan serves as Associate Professor at the Department of Computer Systems and Networks within the Faculty of Computer Science and Technologies at Zaporizhzhia National Technical University, where he has maintained academic activity since 1998. He graduated with honors from Zaporizhzhia Machine-Building Institute's Faculty of Electronic Engineering in 1993, specializing in Radio Engineering with qualification as Radio Engineer. His Candidate of Sciences degree (defended 1998/1999) established his expertise in diagnostic methodologies for electronic systems. His research spans three core domains: automating design and diagnosis of information systems, computer graphics methodologies, and web technologies. This interdisciplinary focus manifests in practical applications ranging from hardware diagnostics to smart home systems. His work demonstrates consistent evolution from foundational electronics reliability research in the 1990s toward contemporary IoT and computer vision applications. His publication trajectory reveals distinct chronological phases: 1990s-2000s concentrated on electro-radio diagnostics and reliability engineering; 2000s-2010s expanded into computer graphics and text recognition; while 2010s-2021 shifted toward IoT integration, smart home technologies, and machine learning applications. This progression reflects both technological advancements and his adaptability across computing subfields. Kasyan teaches modern Internet technologies, computer graphics, computer systems design, and computational methods in scientific research, directly translating his research into pedagogical practice. His academic presence is maintained through Scopus, Web of Science, Google Scholar, and ORCID profiles, indicating active scholarly engagement despite the absence of formal awards or documented grants in available records.
Prof. Dr. Alexander Ecker is Professor of Data Science at the Institute of Computer Science, University of Göttingen, and concurrently holds the prestigious Max Planck Fellow position at the Max Planck Institute for Dynamics and Self-Organization. Since 2020 he also serves on the Executive Board of the Campus Institute Data Science in Göttingen. He leads the Neural Data Science research group, comprising 14 PhD students and 2 postdoctoral researchers, focusing on the interface of machine learning and computational neuroscience. His educational background includes a Dr. rer. nat. in Neuroscience (2014) from the Graduate School of Neural and Behavioral Sciences/IMPRS, University of Tübingen, followed by post-doctoral and group-leader positions at the University of Tübingen and the Max Planck Institute for Biological Cybernetics. Research Interests Machine Learning & Deep Learning: developing novel algorithms for representation learning and generative modeling. Computational Neuroscience: large-scale data-driven modeling of visual cortical circuits. Visual Perception: bridging biological vision and computer vision via biologically inspired architectures. His work has produced a steady stream of influential publications (2019-2025) in leading journals such as Nature Communications , Nature , Nature Methods , PLOS Computational Biology , ICLR , NeurIPS , and CVPR . The publications trend toward integrating high-resolution neural recordings with state-of-the-art machine-learning models to uncover principles of sensory processing, neuron-type classification, and behavior. Scientific Awards & Honors Max Planck Fellow, Max Planck Institute for Dynamics and Self-Organization (ongoing) Executive Board Member, Campus Institute Data Science, Göttingen (since 2020) Teaching, Advising & Grants Regularly teaches advanced courses: “Deep Learning for Image Synthesis”, “Current Topics in Deep Learning”, and “Graph Machine Learning”. Supervises 14 current PhD students and 2 postdocs within the Neural Data Science Group. Offers numerous Bachelor’s and Master’s thesis projects, with topics ranging from neuronal morphology clustering to primate vocalization analysis. Leads or co-leads large collaborative consortia with labs in Göttingen, Tübingen, Baylor College of Medicine, and other institutions across the US and Germany. Labs & Teams The Neural Data Science Group operates at the Institute of Computer Science, University of Göttingen, and is tightly integrated with the Max Planck Institute for Dynamics and Self-Organization. The group maintains active collaborations with over a dozen partner laboratories, including groups led by Fabian Sinz, Andreas Tolias, Thomas Euler, Tim Gollisch, and Viola Priesemann, fostering an interdisciplinary environment that spans computer science, physics, biology, and psychology.
Francois Xavier COUDOUX is a Professor in the Digital Communications group at IEMN DOAE and currently serves as Director of the Electronics Department at INSA Hauts-de-France since 2020. His academic career has been primarily associated with institutions in the Hauts-de-France region, including significant roles at the University of Valenciennes and now INSA Hauts-de-France. Within IEMN, he has held leadership positions including Deputy Director of IEMN-DOAE (2010-2018), member of the IEMN Laboratory Council (2001-2011), and current member of the Scientific Council of the IEMN (2019-present). His educational background includes a Doctorate in Electronics from the University of Valenciennes (1994), Magistère in Image Engineering (1991), DEA in Electronics: imaging and ultrasound (1991), Master's in Audiovisual Communication (1990), and DEUG in Sciences (1988). Professor COUDOUX's research focuses on four main areas: end-to-end optimization strategies for multimedia transmissions over wired or wireless networks; robust MIMO-OFDM transmission of video streams; video pre- and post-processing systems; and data transmission over electrical networks. His work integrates expertise in image/video processing with telecommunications to optimize quality of service in video communication systems. He has contributed significantly to the reduction of blocking artifacts in DCT-coded images and videos, developing perceptual approaches to enhance visual quality in compressed video. His scientific contributions have been recognized through numerous publications since the early 1990s, with consistent output in prestigious journals and conferences. His research shows a clear evolution from foundational work on blocking artifact reduction to more complex systems involving MIMO-OFDM transmission and cross-layer optimization approaches. The publications demonstrate expertise spanning signal processing, image/video coding, telecommunications, and perceptual quality assessment. Among his notable achievements are leadership of the ANR TOSCANE project (2007-2010), participation in the CPER 2009-2013 CISIT research program, and two research contracts with Philips Electronics Laboratories. He has also served as a scientific expert for the ANR, AERES, and for both Walloon and Flemish regions of Belgium. Professor COUDOUX has supervised 8 PhD theses throughout his career and has been actively involved in academic service, including organizing conferences like ISIVC 2012, serving on program committees for CISST and ITST conferences, and reviewing for journals including IEEE Communications Letters and IEEE Transactions on Broadcasting. His teaching responsibilities focus on telecommunication systems, digital communications, and signal processing, particularly in image and video domains.
Professor Oh Jin Kwon is a faculty member in the Department of Electronic Engineering at Sejong University since 1999. His research focuses on image/video analysis, compression algorithms, image quality enhancement, fusion techniques, watermarking, and steganography. He has developed patented algorithms for region adaptive image coding, image watermarking, backward compatible HDR image coding, and progressive image coding. Education: Ph.D. in Electrical and Computer Engineering from University of Maryland, College Park (1994) M.S. in Electrical Engineering from University of Southern California, Los Angeles (1991) B.S. in Electronic Engineering from Hanyang University, Seoul (1984) His extensive research includes image processing , watermarking , and cyber resilience . Recent publications explore deep learning applications in cybersecurity , image coding standards , and 360-degree imaging . His work has been published in Electronics (Switzerland) , Applied Sciences (Switzerland) , Drones , and other journals. Scientific Awards & Grants NSF Grant 91-00655 DACA 76-92-C-0079 DACA 76-89-C-0019 DACA 76-92-C-0009 Professor Kwon has advised numerous PhD and MS students in areas like Point Cloud Coding , JPEG Privacy & Security , and AI-based image coding . He leads research projects funded by institutions including the Korea Aerospace Research Institute and Electronics and Telecommunications Research Institute . His laboratory, the Video Communication Research Lab , focuses on JPEG systems standards , image security , and smart store technologies . Current research includes operator-friendly interface technology for unmanned vehicles and composite material cultural heritage data encryption.
Jin Young Lee is an Assistant Professor at the School of Intelligent Mechatronics Engineering , Sejong University , specializing in image and video processing. He previously worked as a Staff Engineer at Samsung Electronics from 2008 to 2018. Education : Ph.D. (2018), M.S. (2008), B.S. (2006) from KAIST and Sungkyunkwan University Research Focus : Video coding standards, super-resolution, image denoising, and defect detection His research explores 3D video coding , multi-view compression , and deep learning for image restoration . Recent articles highlight applications in brain MR imaging and industrial quality control . Key article trends include lightweight neural networks (e.g., DCP-based U-Net), quaternion transformers for noise reduction, and distributed feature fusion in defect detection. Most works intersect computer vision , deep learning , and signal processing .
Justus Verhagen is an Associate Research Scientist at Yale School of Medicine's Department of Radiology & Biomedical Imaging, with a secondary appointment at The John B. Pierce Laboratory. His work integrates behavioral and neural methods, utilizing optogenetic imaging and stimulation in awake rodents to study food perception and olfactory processing. Education: PhD in Neuroscience, University of Delaware (2001) MSc in Cognitive Neuroscience, University of Amsterdam (1996) Dr. Verhagen's research focuses on olfactory system dynamics , particularly retronasal smell encoding, temporal coding of odor signals, and input-output relationships in olfactory bulb glomeruli. Collaborative projects include multi-modal imaging (fMRI/calcium imaging) with Fahmeed Hyder and exploration of odor navigation through the NSF-funded BRAIN Initiative. His recent publications analyze odor plume intermittency, neurovascular coupling, and advanced neural coding frameworks in olfactory systems. Key trends in his 15 most recent publications reveal expertise in olfactory bulb dynamics , optogenetic imaging , and multi-sensory integration across Neuroscience , Biomedical Imaging , and Behavioral Neuroethology disciplines.
Professor Marek Domański is a distinguished faculty member at Poznań University of Technology, holding the position of Professor at the Institute of Multimedia Telecommunications within the Faculty of Computing and Telecommunications. With over four decades of academic career since completing his dissertation in 1983, he has established himself as a leading researcher in video coding and processing. His research primarily focuses on advanced video coding techniques, particularly Video Coding for Machines (VCM), neural network applications in video processing, immersive video coding, and multiview video compression. Professor Domański has made significant contributions to the field through his extensive publication record and active participation in international standardization efforts, particularly at MPEG meetings. Analysis of his recent publications (2020-2025) reveals a strong emphasis on machine-oriented video coding, with numerous contributions to MPEG standardization activities. His work demonstrates a consistent evolution from traditional video coding toward specialized techniques for machine vision applications, incorporating artificial neural networks to improve coding efficiency and processing capabilities. As an academic supervisor, Professor Domański has guided 27 doctoral students to completion, with recent dissertations focusing on cutting-edge topics in video processing and coding. His research group at PUT maintains active international collaborations, particularly with South Korean institutions like ETRI, reflecting the global relevance of his work. Professor Domański's research has practical applications in virtual reality, free-viewpoint television, and machine vision systems, with numerous technical reports indicating ongoing research projects focused on improving machine vision coding techniques. His work bridges theoretical advances with practical implementations, contributing significantly to both academic knowledge and industry applications in video technology.
Saverio Paglianiti is a Professor at the Brera Academy of Fine Arts (ABABO) in Milan, where he has taught since 2011. He also teaches at the Academy of Fine Arts of Bologna (since November 2022) and previously at ACME of Novara (2016-2018) and ACME of Milan (2010-2011) Private Academies of Fine Arts. He earned an Academic Diploma in Scenography from the Academy of Fine Arts in Milan on February 24, 1998, scoring 110/110. His professional credentials include Certified 3d Studio Max 2012 Associate and Certified 3d Studio Max 2012 Professional – Models to Motion certifications. Paglianiti specializes in comprehensive 3D digital modeling techniques across multiple creative disciplines. His expertise spans line and polygonal modeling, material creation, advanced lighting systems (VRAY SUN, LIGHT, DOME, IES), rendering techniques, and 3D animation. He founded A23DS, a Milanese graphic studio in 2017 that produces high-quality 3D content for nautical, architectural, mechanical and cinematographic applications. He teaches the course 'Digital Modeling Techniques – 3D Computers' (Code: ABTEC41) across six different departments with varying credit values (6-8 CFA), requiring Windows-based systems with NVIDIA RTX graphics. His instruction methodology combines in-person teaching with custom video tutorials, assessing students through project-based evaluations including storyboard creation, concept development, and 3D scene construction. His technical proficiency includes: 3D Modeling & Animation: Autodesk 3D Studio Max Rendering: VRAY by Chaos Group Fluid Dynamics: PhoenixFD by Chaos Group Video Editing: Adobe Premiere & After Effects Image Processing: Adobe Photoshop & Illustrator
Prof. Kai Erenli serves as a Professor at the University of Applied Sciences BFI Vienna, where he heads the bachelor's program "Interactive Media & Games Business". Additionally, since 2013, he has directed the legal department of a Viennese animation company, specializing in gaming law and contract law. His career uniquely bridges academic scholarship and industry practice, with deep expertise in IT law dating back to 2003, certified project management credentials, and prior experience managing an advertising agency. Erenli's research centers on the legal frontiers of digital innovation, with primary emphases on IT law, gaming law, and the regulatory challenges of virtual/augmented reality environments. His scholarship critically examines intellectual property frameworks in virtual worlds, cryptocurrency regulation, and the application of gamification principles in educational contexts. He consistently explores tensions between technological advancement and existing legal structures, advocating for adaptive jurisprudence that accommodates immersive technologies while protecting user rights and commercial interests. Analysis of his 2012-2019 publications reveals a sustained focus on practical legal implications of emerging technologies. His work demonstrates increasing sophistication in addressing virtual asset ownership, location-based gaming compliance, and VR/AR content regulation, with notable contributions to educational technology law and cryptocurrency governance. The interdisciplinary nature of his research bridges computer science, legal theory, and media studies. Scientific recognition includes: ars docendi state prize in "Economics and Law" category (Austrian Federal Ministry of Science, Research and Economy, 2015) As academic program head, Erenli provides institutional leadership and mentorship for bachelor's students in interactive media and gaming business. His role involves curriculum development, industry partnership cultivation, and academic oversight, though specific doctoral advisees or research grants aren't documented in available sources. His industry legal consultancy demonstrates applied scholarship beyond traditional academia. Prof. Erenli has pioneered the VICERO virtual world education platform and contributed to establishing a major German-speaking e-learning infrastructure. His collaborative projects frequently involve cross-disciplinary teams integrating legal experts, technologists, and educators to develop compliant immersive experiences. Current work continues through his blog Virtuellewelten.at and ongoing industry consultancy.
Prof. Dr. Jan Fröhlich is a Professor for Motion Picture Engineering at Stuttgart Media University (HdM), specializing in advanced imaging technologies. His research focuses on high dynamic range (HDR) and wide color gamut (WCG) image encoding, color rendering, camera metrology, and HDR workflows. Prior to his academic appointment, he held key industry positions including Senior Image Scientist at ARRI Munich where he contributed to professional cinema camera systems, and Dolby Laboratories where he helped develop the ITU Rec.2100 ICtCp color space and Dolby Vision platform. He also served as Technical Director at CinePostproduction GmbH. His core research areas include: HDR/WCG encoding and color science Virtual production workflows Camera metrology and image sensor technology Perceptual aspects of high frame rate and HDR imaging Real-time HDR/SDR conversion systems Recent publications demonstrate extensive work in virtual production technologies, including LED volume workflows, HDR broadcast graphics, and light field displays. His research consistently addresses both theoretical foundations and practical implementation challenges in cinematography and broadcast engineering.
Shree K. Nayar is the T. C. Chang Professor of Computer Science in the School of Engineering at Columbia University, where he heads the Columbia Vision Laboratory (CAVE). He served as Department Chair from 2009-2012 and was Director of Research at Snap Inc. from 2018-2024. Nayar received his PhD from Carnegie Mellon University and has been at Columbia since 1991, progressing from Assistant to Full Professor. His educational background includes a PhD in Electrical and Computer Engineering from Carnegie Mellon University (1990), an MS from North Carolina State University (1986), and a BS from Birla Institute of Technology in India (1984). He began his career as a Research Engineer at Taylor Instruments in New Delhi before pursuing graduate studies. Nayar's research spans three interconnected areas: novel computational cameras that capture new forms of visual information, physics-based models for vision and graphics, and algorithms for scene understanding. His work in computational imaging has transformed digital photography, with applications in smartphones, robotics, virtual reality, and human-computer interfaces. His research has produced over 300 publications with nearly 60,000 citations and 80 patents. Analysis of his recent publications reveals a strong focus on computational imaging challenges including low-light vision, depth sensing, mobile interaction, and accessibility technologies. His work consistently bridges theoretical foundations with practical applications, as evidenced by commercial implementations of his assorted pixels technology in smartphone cameras. Elected to National Academy of Engineering (2008), American Academy of Arts and Sciences (2011), National Academy of Inventors (2014), and Indian National Academy of Engineering (2022) Okawa Prize (2023), IEEE PAMI Distinguished Researcher Award (2019) Two-time David Marr Prize winner (1990, 1995) - the highest honor in computer vision Multiple best paper awards at major conferences including SIGGRAPH Asia (2024) and ECCV (2024) National Young Investigator Award (1991), Packard Fellowship (1992) Nayar has supervised numerous PhD and Master's students throughout his career at Columbia. His lab has received continuous funding from NSF, industry partners, and foundations. The Columbia Vision Laboratory (CAVE) is known for its interdisciplinary approach, combining optics, hardware design, and algorithms to solve fundamental vision problems. Nayar's Bigshot Camera project demonstrates his commitment to education, providing hands-on learning experiences for students worldwide. The Columbia Vision Laboratory (CAVE) develops cutting-edge computational imaging and computer vision systems. Under Nayar's leadership, the lab has pioneered technologies including self-powered cameras, high dynamic range imaging systems, and novel computational cameras. The lab maintains strong industry connections, particularly through Nayar's role at Snap Research, and emphasizes translating research into real-world applications that benefit society.
