Dominik Schörkhuber is a PreDoc Researcher at the Vienna University of Technology (TU Wien) in the Computer Vision department. With a background in Informatics (BSc, Dipl.-Ing.), he focuses on computer vision applications for autonomous driving, robotics, and human-machine interaction. His work spans driver action recognition, pedestrian prediction, and adaptive lighting systems. Current projects: Empathic Vehicle (2024–2026), SyntheticCabin (2021–2025), SmartProtect (2020–2025) Research themes: Video transformers, synthetic data transfer learning, multi-task learning, and sensor-lighting integration Specializes in 3D sensing, nighttime driving analysis, and mobile video creation tools
Professor Moncef Gabbouj is a distinguished academic and researcher currently serving as Professor of Signal Processing at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences, Tampere University, Finland. Previously, he held the same position at Tampere University of Technology before the merger in 2019. He has also held visiting professorships at prestigious institutions including Hong Kong University of Technology and Science, University of Southern California, and Purdue University. Ph.D. and MSc. in Electrical Engineering from Purdue University, USA (1989 and 1986) B.Sc. in Electrical Engineering from Oklahoma State University, USA (1985) Prof. Gabbouj's research spans multiple domains within signal and image processing, with a strong focus on machine learning applications. His primary research interests include artificial intelligence, machine learning, Big Data analytics, multimedia content-based analysis, indexing and retrieval, nonlinear signal and image processing, voice conversion, and video processing and coding. His work bridges theoretical advancements with practical applications across various industries, particularly in multimedia communications and biomedical applications. His extensive publication record demonstrates a clear evolution from traditional signal processing techniques toward more sophisticated machine learning and deep learning approaches. Recent work shows increasing focus on convolutional neural networks for various applications including ECG classification, video processing, financial time-series analysis, and image recognition tasks, reflecting the broader trend in the field toward deep learning methodologies while maintaining strong foundations in signal processing theory. IEEE Fellow (2011) Member, Finnish Academy of Science and Letters (2014) Knight, First Class, of the Order of the White Rose of Finland (2006) Nokia Foundation Recognition Award (2005) Nokia Foundation Visiting Professor Award (2012) Finnish Cultural Foundation for Art and Science Award (2017) TUT Foundation Grand Award (2015) Prof. Gabbouj has supervised 64 doctoral and 72 Master's theses, demonstrating his significant contribution to academic mentoring. His research has been supported by substantial funding, including research grants totaling 8.5 million Euro (2001-2015). He has served as Academy of Finland Professor during 2011-2015 and has been involved in numerous EU research projects including Horizon, ESPRIT, HCM, IST, COST, Tempus and Erasmus programs. As Editor, Guest Editor or member of the Editorial Board of 6 international scientific journals, he has significantly influenced the academic discourse in his field. He leads the Signal Analysis and Machine Intelligence (SAMI) research group at Tampere University and serves as the Finland Site Director of the NSF IUCRC funded Center for Visual and Decision Informatics. His research unit focuses on applying advanced machine learning techniques to solve complex problems in signal processing, computer vision, and multimedia analytics, with applications ranging from healthcare to multimedia communications and financial analysis.
Hui Pan is a distinguished academic holding dual positions as Nokia Chair in Data Science and Professor of Computer Science at the University of Helsinki, and Chair Professor of Computational Media and Arts at the Hong Kong University of Science and Technology (HKUST). His research spans networking, mobile computing, augmented reality, and computational social science. He earned his Ph.D. in Computer Science from the University of Cambridge in 2007. His work bridges social networks with mobile systems, pioneering fields like mobile social networks and opportunistic forwarding algorithms. Research interests include data science, complex networks, and innovative applications of augmented reality. His recent publications focus on low-latency AR frameworks, blockchain for computation offloading, and mobile web visualization. He has received prestigious awards, including IEEE Fellow (2018), ACM Distinguished Scientist (2016), and the Nokia Chair Endowment (2017). He has supervised over 15 PhD and 12 MPhil graduates, with 13 current Ph.D. students and 2 MPhil students. His editorial roles include Associate Editorships at IEEE Transactions journals and guest editorships at top venues like IEEE JSAC and ACM Transactions. He has organized conferences such as WWW Track Chair and ExtremeCom General Chair.
Assoc. Prof. Dr. Klaus Schöffmann is an Associate Professor at the Institute of Information Technology (ITEC) at Klagenfurt University, Austria. He holds a PhD and MSc in Computer Science, and received his habilitation (venia docendi) in 2015. His research focuses on video content understanding (including medical/surgery videos), deep learning, multimedia retrieval, and interactive multimedia. He has secured over €2M in research funding and mentored 6 PhD candidates. He chairs the Video Browser Showdown (VBS) and Lifelog Search Challenge (LSC), and is a member of IEEE/ACM. He has served as program co-chair for MMM 2021, CBMI 2021, ACM ICMR 2020, and others. Affiliations: Deputy Head of the Institute of Information Technology, Chairman of the Curricular Commission for Computer Science. Grants & Impact: €2M+ funding from FWF, KWF, and industry; Google H-index 36 (4,000+ citations). Teaching: Courses in computer vision, multimedia technologies, and app development. He actively organizes conferences including general co-chair roles for ACM ICMR 2024, CBMI2025, and ACMMM2025, and contributes as a reviewer for top journals/conferences in multimedia and medical imaging.
Wolfgang Klas is a Professor at the Faculty of Computer Science, leading the Research Group Multimedia Information Systems. His research focuses on multimedia systems, data management, and information retrieval, with significant contributions to multimedia content analysis and database systems. He has been actively involved in multiple research projects, including TP2 PRECIOUS (2013-2016), SciLink (2011-2014), and OptFI (2010-2013). His work intersects with emerging technologies like blockchain, as seen in his public engagements and talks on topics such as 'From Blockchain to Web' and IT4S Forum presentations. His research interests span multimedia systems, database design, and the application of declarative programming for security and data integrity. Recent projects emphasize fake review detection and sentiment analysis using advanced algorithms and neural models. He has collaborated internationally, contributing to workshops like SMAP 2020 and publishing in journals like Algorithms and Applied Sciences . Grants/Projects: TP2 PRECIOUS (2013-2016), SciLink (2011-2014), OptFI (2010-2013) Activities: Speaker at IT4S Forum (2024), Blockchain-related talks (2020–present) Labs/Teams: Research Group Multimedia Information Systems
Armin Kirchknopf serves as a Junior Researcher at the Media Computing Research Group within the Institute of Creative Media/Technologies, Department of Media and Digital Technologies at the University of Applied Sciences St. Pölten. His interdisciplinary work bridges artificial intelligence, computer vision, and social media analysis, with significant contributions to misinformation detection and disaster response systems. Based at Campus-Platz 1 in St. Pölten, Austria, he actively collaborates on EU-funded projects and publishes in top-tier AI venues. His educational journey spans humanities and technology: a Bachelor of Arts in Egyptology and Master of Arts in Classical Archaeology from the University of Vienna (including fieldwork at excavation sites across Austria, Germany, and Egypt), followed by a Bachelor of Science in Media Technology from FH St. Pölten. This unique background informs his human-centered AI research approach. Kirchknopf's research centers on explainable multimodal AI systems for real-world challenges. His recent work demonstrates expertise in transformer-based architectures for cross-lingual fake news detection, sexism identification, and flood monitoring through social media imagery. He pioneers techniques like Grad-CAM for object detection explainability and develops visualization tools for complex data interpretation, emphasizing transparency and social impact in AI deployment. Analysis of his 13 publications (2017-2022) reveals a strategic shift toward applied AI in societal contexts , particularly using social media data for disaster management and combating online toxicity. His projects consistently integrate computer vision with natural language processing, showing increasing sophistication in multilingual capabilities and model interpretability frameworks. His scientific recognition includes: Creative Business Award for co-developing the Tenjin learning quiz application No documented student advisement or grant leadership appears in current records, though he actively mentors through project-based collaborations. His work with the Media Computing Research Group drives innovation in educational technology and public safety applications. Kirchknopf contributes to the Media Computing Research Group's portfolio including Fake News Detection, SAiEX (Safe AI with explainable integrity), InfraBase (building footprint segmentation), and Ressel Center music therapy projects. His cross-disciplinary collaborations span computer scientists, archaeologists, and social scientists, reflecting the group's commitment to human-centric technological solutions .
Ivan Viola is an Associate Professor at the Institute of Computer Graphics and Algorithms, part of the Faculty of Informatics at TU Wien, Austria. He holds a leave of absence until December 2024 while also being affiliated with King Abdullah University of Science and Technology (KAUST) as an Associate Professor funded by the Vienna Research Groups program. His research focuses on visualization techniques in medicine, biological sciences, and earth sciences, with a specialty in illustrative visualization and DNA-nanotechnology applications. Viola has contributed over 100 scientific works and serves as a reviewer and panelist for major conferences in computer graphics and visualization. Education: M.Sc. (2002) and Ph.D. (2005) in Computer Graphics from TU Wien. Postdoctoral research at the University of Bergen (2006-2011), where he became Full Professor before returning to TU Wien. Research Interests: Whole-cell visualization Molecular modeling Interactive 3D environments Biomedical visualization Data-driven colormap techniques Awards: IEEE VIS 2017 Best Paper Honorable Mention, 'Best Overall Concept' for CellView, and multiple visualization awards. Active in EuroVis and IEEE VIS organizing roles. Grants & Supervision: Leads the Visualization Group at TU Wien, supervising student projects and master’s theses. Involved in grants like the Vienna Research Groups program. Labs/Teams: Visualization Group at TU Wien, collaborating on projects like CellView and Molecumentary.
Professor Dong Xu is a Tenured Professor in the Department of Computer Science at the University of Hong Kong (HKU), part of the School of Computing and Data Science. He holds a B.Eng. and Ph.D. from the University of Science and Technology of China (USTC). His career includes tenured roles at Nanyang Technological University and the University of Sydney, alongside postdoctoral research at Columbia University. His research focuses on Artificial Intelligence, Computer Vision, Multimedia, and Machine Learning , with applications in autonomous driving, AR/VR, medical image analysis, and video surveillance. Xu has authored over 150 papers in top journals and conferences, including CVPR, ICCV, and IEEE Transactions. He actively contributes to the academic community as an editorial board member for journals like ACM Computing Surveys and IEEE Transactions, and through leadership roles in conferences such as ACM Multimedia and ICME. Notable awards include Fellowships from IEEE and IAPR, and the IEEE Signal Processing Society Distinguished Lecturer title (2021–2022). Education: B.Eng. (USTC, 2001), Ph.D. (USTC, 2005) Professional Service: Program Coordinator of ACM Multimedia 2024, Guest Editor of over ten special issues.
Shah Nawaz is an Assistant Professor at the Institute of Computational Perception , Johannes Kepler University Linz. His research focuses on multimodal systems, deep learning applications in healthcare, and cross-modal learning frameworks. He leads projects addressing challenges like missing modalities in machine learning, face-voice association, and medical image analysis. Key research interests include machine learning for medical diagnostics (e.g., breast cancer detection, skin lesion segmentation), speech recognition, and adaptive neural network architectures. He has contributed to frameworks like Chameleon for robust multimodal learning and the FAME challenge for face-voice association in multilingual environments. Publications emphasize practical applications, such as bilingual healthcare chatbots for pregnant women and light-weight speech recognition models for resource-constrained systems. His work bridges theoretical advancements and real-world deployment in healthcare and security domains. Shaw Nawaz actively participates in academic communities through workshops like DaQuaMRec@RecSys2025 and has developed open-source frameworks for image restoration and multimodal fusion. His lab focuses on scalable solutions for multimodal data challenges in both technical and clinical contexts.
Christian Timmerer is a Professor at the Institute of Information Technology, Alpen-Adria-Universität Klagenfurt. His research focuses on adaptive video streaming , energy efficiency , MPEG standardization , and quality of experience (QoE) , with significant contributions to HTTP Adaptive Streaming (HAS), multi-codec optimization, and immersive media systems. Email: christian.timmerer@aau.at Office Hours: Monday 3:00-4:00 PM (by appointment) Projects: CD-Labor ATHENA, GAIA, SPIRIT His research integrates machine learning and generative AI to enhance video encoding, super-resolution, and voice dubbing, while prioritizing sustainability through energy-aware algorithms and open-source tools like GREEM and VEED. Current work emphasizes latency reduction and dynamic bitrate adaptation in live streaming environments. Recent publications address VVC optimization , multi-resolution encoding , and perceptual quality modeling , reflecting interdisciplinary efforts in networking , computer vision , and human-computer interaction . Awards include leading funded projects on adaptive streaming and green video systems.
Mostafa Ammar is a Regents' Professor and Interim Chair of the School of Computer Science at the Georgia Institute of Technology. He has held leadership roles including Associate Chair (2006–2012) and has been a faculty member since 1985. His research focuses on network architectures, protocols, and services, with contributions to mobile cloud computing, network virtualization, and disruption-tolerant networks. He has advised 39 Ph.D. students and secured funding from agencies like NSF, DARPA, and industry partners such as Cisco and IBM. Education : S.B. and S.M. from MIT, Ph.D. from the University of Waterloo. Research Interests : Network architectures, mobile cloud computing, overlay networks, video streaming, and network simulation. His work bridges theoretical advancements with practical implementations, emphasizing scalable and efficient network solutions. Publications : Over 214 publications with a focus on network virtualization, mobile edge computing, and distributed systems. Recent work explores encrypted traffic analysis and femto-cloud resource sharing. Awards : ACM/IEEE Fellowships (2002–2003), Best Paper Awards (2012, 2018), and multiple teaching excellence recognitions. Service : Editor-in-Chief of IEEE/ACM Transactions on Networking (1999–2003), conference co-chair roles, and steering committee memberships. Advising & Grants : Mentored 39 Ph.D. students and secured multi-million-dollar grants. His research has influenced industry standards and academic curricula. Labs/Teams : Active in Georgia Tech’s networking research groups, contributing to open-source network simulators and collaborative projects with global institutions.
Prof. Hermann Hellwagner is a Full Professor at the Department of Information Technology, University of Klagenfurt. He has held roles such as Vice President (Natural and Technical Sciences) at the Austrian Science Fund (FWF) and Vice Dean of the Faculty of Technical Sciences. His research focuses on multimedia communication, network engineering, and future internet architectures. Notable projects include work on adaptive streaming, edge computing, and drone networks. He holds a Ph.D. in Systolic Architectures from the University of Linz (1988). Research interests span distributed multimedia systems, information-centric networking (ICN), and optimizing video streaming quality-of-experience (QoE). Recent work emphasizes edge computing solutions for low-latency streaming and dynamic codec adaptation. His contributions include frameworks like ALPHAS and MEDUSA for bitrate optimization, and studies on point cloud streaming in augmented reality. Publications (2021–2025) highlight advancements in edge-assisted streaming, hybrid P2P-CDN architectures, and transcoding techniques. His work often bridges theoretical models with real-world implementations, addressing challenges in latency, cost, and device adaptability. Current projects involve 6DoF video streaming and multi-robot system optimization. Labs/Teams: Part of the Institute of Information Technology (ITEC), Klagenfurt. Collaborates on EU-funded projects and industry partnerships in 5G edge computing and drone networks. Active in standards groups for HTTP adaptive streaming protocols.
Borivoje Furht is a Professor of Computer Science and Engineering at Florida Atlantic University (FAU) in Boca Raton, Florida, a position he has held since 1992. He maintains dual affiliations with FAU and the Mathematical Institute of the Serbian Academy of Sciences and Arts. At FAU, he serves as Director of the NSF-sponsored Industry/University Cooperative Research Center for Advanced Knowledge Enablement since 2009. His academic leadership includes serving as Chair of the Department of Computer and Electrical Engineering and Computer Science (2009-2013) and Chair of the Department of Computer Science and Engineering (2002-2009). He earned his Ph.D. in electrical and computer engineering from the University of Belgrade, following early career positions at the Institute Boris Kidric-Vinca in Yugoslavia and Modcomp (a computer division of Daimler Benz). Dr. Furht's research spans multiple areas in computer science with a strong focus on multimedia technologies. His current research interests include multimedia systems, video coding and compression, cloud computing, big data, mobile multimedia, and wireless multimedia applications. Over his career, he has secured approximately $15 million in research funding from government agencies including NSF, NIH, Department of Navy, DoD, and NASA, as well as private industries such as IBM, Google, Apple, LexisNexis, Motorola, and Emerson. His scholarly contributions include founding and serving as editor-in-chief of the Journal of Multimedia Tools and Applications (Springer) and co-founding the Journal of Big Data (Springer). His work has been recognized with numerous awards including multiple FAU Researcher of the Year Awards (2019, 2013), a Distinguished Engineering Education Award from The Engineer's Council (2019), and various technical achievement awards throughout his career spanning from 1982 to 2019. Dr. Furht has also served as a consultant to various companies, colleges, and universities, leveraging his expertise in multimedia systems and computer engineering across both academic and industrial settings.
Ahmet Tekalp is a Professor in the Department of Electrical and Computer Engineering at Koc University's College of Engineering since 2001. He holds dual citizenship in Turkey and the USA, with prior academic roles at the University of Rochester (1986-2005) and research positions at Eastman Kodak (1984-1987) and Rensselaer Polytechnic Institute (1981-1984). He chairs the Electronics and Informatics Group at TUBITAK since 2004 as a part-time position. B.S. (1980) in Electrical Engineering & Mathematics, Bogaziçi University M.S. (1982) and Ph.D. (1984) in Electrical, Computer, and Systems Engineering, Rensselaer Polytechnic Institute His research focuses on digital image and video processing, including video compression, motion-compensated filtering for high-resolution applications, video segmentation, object tracking, content-based video analysis, multi-camera surveillance processing, and digital content protection. He has led numerous European and U.S. grants, including FP7 STREP projects and NSF awards, emphasizing applications in sensor networks, visual databases, and medical imaging. His scholarly work spans diverse areas such as superresolution reconstruction, head gesture animation, 3DTV streaming, and reversible data hiding. He has played pivotal roles in editorial boards, including serving as Editor-in-Chief of Signal Processing: Image Communication, and has contributed to major standards bodies like ISO MPEG and ANSI NCITS. Member, Turkish Academy of Sciences (TUBA) Fellow, IEEE Fulbright Senior Scholarship (1999) TUBITAK Science Award (2004) IEEE Signal Processing Society Distinguished Lecturer (1998) He has led multiple international research collaborations and projects, including European FP6/FP7 networks and NATO programs, with substantial grant funding from NSF, NYSTAR, and industry partners like Eastman Kodak, Xerox, and Siemens.
Ines Zeitlhofer is a PhD student and Research Assistant at the Department of Educational Science, University of Salzburg, affiliated with the School of Education. Her research focuses on metacognition and problem-solving in digital learning environments, with a particular emphasis on pedagogical agents and multimedia learning. Prior to this role, she earned a Master of Educational Sciences from the University of Salzburg and worked as a teacher at Group Scolarie Sophie Barat in Paris and a lecturer for Business German at the Université Paris Cité’s Faculty of Law and Economics. Her work explores cognitive and metacognitive strategies to enhance learning performance, leveraging digital tools and multimedia approaches. Recent publications highlight her contributions to understanding appraisal processes in multimedia learning, the impact of pedagogical agents on motivation, and the application of cognitive prompts in digital platforms. Ines is part of the Digital Learning Research Group (DLRG), collaborating on projects that bridge educational theory and technological innovation. She holds no explicitly stated awards but is actively engaged in advancing evidence-based practices in digital education.
