Patrick Jermann is a Lecturer at EPFL’s School of Computer and Communication Sciences, affiliated with the Centre for Digital Education (CEDE) , SIN-ENS , and SSC-ENS departments. As Executive Director of CEDE since 2013, he leads Swiss MOOC Service (SMS), NOTO, and Campus Analytics initiatives. His research focuses on Computer Supported Collaborative Learning (CSCL) , Learning Analytics , and MOOCs , analyzing student interactions, gaze patterns, and attrition behaviors through clickstream data. Recent work explores pedagogical design, statistical methods, and software development for educational tools. His publications (2001–2015) reveal trends in eye-tracking for MOOCs, interaction analysis, and collaborative learning technologies. Notable contributions include frameworks for gaze-based feedback and metrics for perceived video difficulty. He has mentored PhD students such as Sharma Kshitij and Nüssli Marc-Antoine , and secured grants via the DRIL fund . As a CDS Member, he contributes to institutional digital education strategies.
Carlos Antonio Andújar Gran is a faculty member at the Faculty of Informatics of Barcelona (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Science. He actively contributes to the academic community through teaching and supervising numerous student projects, particularly in advanced computing domains. His research interests center on the application of computer graphics, virtual reality, and artificial intelligence to real-world problems. Key areas include the 3D visualization and virtual reconstruction of cultural heritage, physically accurate rendering, intelligent segmentation of images, and the use of machine learning and reinforcement learning in sports analytics, particularly for padel. His work bridges technical innovation with practical applications in cultural preservation and sports technology. The recent publications under his supervision reflect a strong trend in digital cultural heritage, with multiple projects focused on tools for virtual visits, reconstruction, lighting simulation, and web-based 3D visualization of heritage models. Another significant trend is the application of AI to padel, including ball and player tracking, virtual coaching, and training virtual agents using reinforcement learning. These projects demonstrate a consistent focus on computer vision, interactive systems, and data-driven modeling. Carlos Antonio Andújar Gran has supervised a substantial number of students, guiding both undergraduate and master's theses. While specific grant information is not available in the text, his sustained supervision across many years suggests active involvement in research projects. He plays a key role in mentoring the next generation of computer scientists at UPC. His work is closely tied to the Department of Computer Science at FIB, where he collaborates with other faculty members such as Imanol Muñoz Pandiella, Núria Pelechano Gómez, and Mohammadreza Javadiha on various student projects, indicating a collaborative research environment focused on graphics, AI, and VR applications.
Christian Decker is Professor of International and Corporate Finance at the Department of Economics, Hamburg University of Applied Sciences (HAW Hamburg). His research focuses on corporate and structured finance, corporate and investment banking, and methodical aspects of research. He specializes in competency-based instructional design, integrating e-learning, blended learning, and flipped classroom models into higher education. Decker has contributed extensively to academic research and writing methodologies, with a particular emphasis on digital education and educational media. University of Hamburg (Dipl.-Kfm., 1994) University of Bremen (Dr. rer. pol., 2007) University of Hamburg (M.H.Ed., 2020) His research spans corporate finance, educational innovation, and digital learning strategies. Recent publications analyze case-based assessments, poster conferences, and the Scholarship of Teaching and Learning (SoTL), reflecting his commitment to advancing pedagogical practices. Decker has supervised doctoral theses, including J. Beck's 2021 work on fintech financing for SMEs. He has received the Hamburg Teaching Award twice (2012, 2017) for his contributions to e-learning and team teaching. Hamburg Teaching Award 2012 Hamburg Teaching Award 2017 Decker's professional roles include leadership in curriculum reform and departmental governance. He has conducted workshops on inverted classroom models and digital mastery learning, collaborating with institutions like FH St. Pölten and RWTH Aachen. His educational media projects emphasize individualized learning through videos, webinars, and interactive labs.
Yaser S. Abu-Mostafa is a Professor of Electrical Engineering and Computer Science at the California Institute of Technology (Caltech), with a distinguished career spanning over four decades. He earned his B.Sc. from Cairo University in 1979, an M.S.E.E. from Georgia Tech in 1981, and a Ph.D. from Caltech in 1983. Holding roles such as Garrett Research Fellow (1983), Assistant Professor (1983-89), Associate Professor (1989-94), and Professor since 1994, he has cemented his reputation as a pioneer in artificial intelligence and machine learning. Educational Background B.Sc., Cairo University (1979) M.S.E.E., Georgia Institute of Technology (1981) Ph.D., California Institute of Technology (1983) Abu-Mostafa’s research bridges AI/ML with medical diagnostics and computational finance. His projects include non-invasive blood pressure measurement via ultrasound, AI-based detection of congestive heart failure through video analysis, and early stroke prediction using clot-detection algorithms. These innovations leverage machine learning to address biological variability and real-world complexity. His recent publications focus on predictive modeling for epidemiology (2022, 2021), theoretical advancements in machine learning (2015, 2006, 2005), and foundational work in swarm robotics and financial mathematics (2004). Trends in his work emphasize robustness, adaptability, and interdisciplinary applications. Scientific Awards Clauser Prize (Caltech’s most original Ph.D. thesis) ASCIT Teaching Awards (1986, 1989, 1991) GSC Teaching Awards (1995, 2002) Richard P. Feynman Prize for Excellence in Teaching (1996) Abu-Mostafa Fellowship established by Hertz Foundation (2005) Abu-Mostafa has advised numerous students and led research teams at Caltech, while also serving on scientific advisory boards and consulting for industries. His Caltech MOOC on machine learning has garnered over 8 million views, and his textbook Learning from Data is an Amazon bestseller. He collaborates extensively, including a major project with UCSF on heart failure detection and partnerships in computational finance. His work on a Caltech patent for stroke prediction received a US patent in 2025, alongside other medical AI patents.
Rolf Steier serves as Professor at Oslo Metropolitan University within the Faculty of Education and International Studies, Department of Primary and Secondary Teacher Education, holding the position of Head of Studies for Area of Responsibility 5. His office is located at Pilestredet 52, 0167 Oslo (B534), with contact details including mobile +47 906 92 626, office +47 672 36 014, and email rolf.steier@oslomet.no. He actively contributes to the Digital Learning Arenas research group, focusing on technology-enhanced educational environments. Steier's research centers on computer-supported collaborative learning (CSCL) and virtual reality applications in education, with specific expertise in embodied cognition, science education, museum learning, and narrative structures in STEM. His work examines how learners co-construct knowledge through digital interactions, particularly investigating the role of physical embodiment in virtual environments and the integration of narrative techniques to facilitate engagement in informal learning contexts. Recent projects explore immersive VR experiences for collaborative meaning-making and the adaptation of interaction analysis methodologies for technology-mediated educational research. Analysis of Steier's 2021-2025 publications reveals a clear trajectory toward increasingly sophisticated integration of virtual reality in educational research, with growing emphasis on interdisciplinary applications in science education. Key thematic developments include the refinement of interaction analysis frameworks for digital contexts, the exploration of perspective-taking across blended realities, and the strategic use of narrative to enhance STEM engagement in informal settings. His work consistently bridges theoretical learning science with practical educational technology implementation. The Digital Learning Arenas research group serves as the primary platform for Steier's collaborative work, functioning as an interdisciplinary hub for developing and studying innovative digital learning solutions. This group facilitates partnerships across educational sectors to transform teaching practices through emerging technologies, with recent focus on VR-based collaborative learning environments and cross-contextual knowledge transfer.
Cecilia Wallerstedt is a Professor at the University of Gothenburg, affiliated with both the Artistic Faculty at the Academy of Music and Drama and the Department of Education, Communication and Learning. As Pro-Dean of the Artistic Faculty, she bridges artistic and educational research, while leading the FILUR project focused on imagination development in early childhood education. Her research explores teaching and learning in music and other aesthetic subjects across educational levels, emphasizing teacher-child interactions and sociocultural theory. Current projects address play-responsive teaching, intergenerational play dynamics, and digital media integration in preschool settings. She supervises PhD students in the PReCEC graduate school and collaborates with Nordic institutions through networks like the Studies of Artistic Vision and the Network for Internship Development. Recent publications highlight play-responsive didaktik, metacognitive strategies, and cultural historical theory applied to music, narrative play, and multilingual engagement. While no scientific awards are mentioned, her work includes EU-funded research and systematic reviews of music education practices.
Prof. Dr. Carla Schelle is a Professor of Educational Science with a focus on School Pedagogy and Didactics at the Johannes Gutenberg University Mainz. Her work bridges comparative, reconstructive methodologies to analyze teaching practices across Germany, France, and Senegal, emphasizing political education, didactic innovations, and intercultural teacher training. Roles: Vice Dean for Studies and Teaching (2017-2023), Professor (since 2003), Deputy Professorships at University of Essen-Duisburg (2002-2003) and Goethe University Frankfurt (1997-1998). Education: Habilitation in School Pedagogy and Didactics of Social Sciences (2002, University of Hamburg), PhD in Qualitative Educational Research (1995, Justus Liebig University Giessen), Magister Artium (1988, Mainz). Research Interests center on reconstructive classroom research , comparative didactics , and cultural-hermeneutic pedagogy . She explores how educational content is co-constructed in diverse cultural contexts, with a focus on political-historical topics and visual learning materials. Publications span 15 recent works (2015-2025), including comparative studies on absolutism in French/German curricula, electoral education, and intercultural casuistry. Her projects, like CORE (DFG), examine narrative framings in students' critical online reasoning. Collaborations include co-leading the Interpretative Research Workshop on Classroom Practices and developing international partnerships with institutions in Paris, Dakar, and Bordeaux. She also contributes to editorial boards and peer review for journals like Recherche et Formation .
Professor George Ghinea is a distinguished academic in the Department of Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. With over 350 publications and 33 successfully supervised PhD students, he leads cutting-edge research at the intersection of computer science, media studies, and psychology. His educational background includes a PhD from the University of Reading (1999) where he pioneered the Quality of Perception (QoP) metric - a precursor to today's widely adopted Quality of Experience (QoE) concept. He holds multiple degrees with distinction from the University of the Witwatersrand in South Africa, including BSc, BSc (Hons), and MSc in Computer Science. Professor Ghinea's research focuses on perceptual multimedia quality and human-centered e-systems, with particular emphasis on mulsemedia (multiple sensorial media) - his own conceptual framework extending multimedia to engage non-traditional senses. His work spans eye-tracking applications, telemedicine, multi-modal interaction, and ubiquitous computing. Current research explores mulsemedia integration in autonomous vehicles, security-enhanced systems, and accessibility solutions. His publications reveal strong trends in multisensory computing (42% of recent works), telemedicine applications (28%), accessibility research (18%), and network optimization (12%). The work consistently bridges theoretical frameworks with practical implementations, often incorporating physiological data and user perception metrics. Distinguished Visiting Fellow of the Royal Academy of Engineering (2018) SPARC DUO-India 2020 Fellowship Programme recipient Principal Investigator for multiple EU Horizon 2020 projects Research featured in major media including BBC, Forbes, and Daily Telegraph Professor Ghinea has secured substantial research funding through projects like the EU H2020 NEWTON initiative, Royal Academy of Engineering partnerships, and multiple Newton Fund collaborations. His supervision portfolio includes 33 PhD completions with diverse research spanning security behavior in Ghana, physiological QoE in VR, smart city adoption in Oman, and sustainable digital transformation in Qatar. He leads the IMUSY research group focusing on mulsemedia systems and human perception. His laboratory work centers on the IMUSY research group where they develop mulsemedia applications integrating thermal, wind, and olfactory devices for enhanced user experiences. Current team projects include mulsemedia in autonomous vehicles (MulsEAV), physiological data for QoE assessment, and smart city adoption studies.
Professor Howard Schwartz is a distinguished academic in Electrical and Computer Engineering at Carleton University , with a career spanning academia, industry, and robotics research. He earned his BEng in Civil Engineering from McGill University (1982), followed by MSc (1984) and PhD (1986) in Aerospace and Mechanical Engineering from MIT. His academic leadership includes serving as Department Chairman (2009-2013) and authoring the seminal text Multi-Agent Machine Learning: A Reinforcement Approach (Wiley, 2014). As an Associate Editor for IEEE Transactions on Cybernetics , he shapes discourse in cybernetic systems and machine learning. Research Focus Professor Schwartz's research bridges theoretical and applied domains: Machine learning for robotics and autonomous systems Adaptive control theory and multi-agent systems Reinforcement learning algorithms with fuzzy logic integration Real-time video analytics and GPS receiver development Nonlinear control systems for UAVs and wind energy optimization Industry Experience His career includes impactful industry engagements: Early development of high-performance GPS receivers at Canadian Marconi Co. (1982-1984) Sabbatical at March Networks (2001-2002) for video analytics Software quality control at CMC Electronics (2008) Software development for TV set-top boxes at Espial Inc. (2014-2015)
Izaak Dekker is an Associate Professor of Didactics and Curriculum Development in Higher Education at Amsterdam University of Applied Sciences, affiliated with the Personalized Learning and Instruction research group. His research focuses on AI applications in education and interventions to enhance student success, retention, and well-being through experimental evaluation studies. He combines academic rigor with practical collaboration, working closely with lecturers and students to optimize flexible education models. Education: PhD in Academic Thriving (Evidence-Based Higher Education) from Erasmus University Rotterdam (2018–2022) Research interests span AI in education, evidence-based pedagogy, and behavioral interventions in higher education. His recent work explores desirable difficulties in learning, students-as-teachers models, and media literacy in the era of generative AI. Scientific awards include the Docentonderzoeker van het jaar (Academic Teacher of the Year, 2021) and the 100% Open Science Award (2024). He actively contributes to open data initiatives and peer review processes.
Alan Bovik is a Professor at The University of Texas at Austin, holding the prestigious Cockrell Family Endowed Regents Chair in Engineering. He serves as Director of the Laboratory for Image and Video Engineering (LIVE) and maintains dual faculty appointments in the Department of Electrical and Computer Engineering and the Institute for Neuroscience. His extensive contributions have established him as a leading authority in visual information processing with global impact. Dr. Bovik's research spans multiple domains with a primary focus on image and video processing, digital television and digital cinema, computational vision, and visual perception. His work has fundamentally advanced the understanding of human visual perception, leading to practical applications in video quality assessment and image processing systems. With over 800 technical publications cited more than 75,000 times and an H-index above 100, his research has had extraordinary impact across academia and industry. He is recognized as a Highly-Cited Researcher by Clarivate Analytics, placing him among the most influential researchers globally. Analysis of Dr. Bovik's recent publications reveals a strong emphasis on video quality assessment for emerging applications like user-generated content, high-motion streaming, and adaptive video delivery. His work seamlessly integrates deep learning approaches with traditional signal processing techniques to develop perceptually accurate models. There's a clear trend toward addressing practical challenges in video streaming quality, compression artifacts, and the unique characteristics of modern video content. His research bridges theoretical foundations with real-world applications, making significant contributions to both academic understanding and industry standards. Dr. Bovik's exceptional contributions have been recognized with numerous prestigious awards: IEEE Fourier Award (2019) for seminal contributions to perception-based image and video processing Edwin H. Land Medal (2017) from The Optical Society Primetime Emmy Award for Outstanding Achievement in Engineering Development (2015) Norbert Wiener Society Award (2013) Claude Shannon / Harry Nyquist Technical Achievement Award (2005) Multiple best paper awards from IEEE, EURASIP, and Picture Coding Symposium As an educator and mentor, Dr. Bovik has guided numerous students through his leadership at LIVE. His professional service includes founding and serving as Editor-in-Chief of the IEEE Transactions on Image Processing (1996-2002) and chairing the inaugural IEEE International Conference on Image Processing in 1994. His industry impact is substantial, evidenced by his Primetime Emmy Award and frequent consultation with major institutions. Dr. Bovik is also a registered Professional Engineer in Texas, demonstrating his practical engineering expertise alongside theoretical contributions. Dr. Bovik leads the Laboratory for Image and Video Engineering (LIVE), which maintains strong affiliations with multiple research centers including the Wireless Networking and Communications Group (WNCG), Center for Perceptual Systems, Telecommunications and Signal Processing Research Center, and Institute for Computational Engineering and Sciences. These interdisciplinary connections enable research that bridges engineering, neuroscience, and computer science to advance our understanding of visual perception and processing.
Channine Clarke is a Professor at the University of Brighton , serving as Associate Dean for Practice Learning and Partnerships in the School of Education, Sport and Health Sciences. An occupational therapist since 1998, she specializes in mental health and has held leadership roles in clinical governance and education development. Her 2012 PhD on role-emerging placements established her as an international authority in practice learning innovation. MSc in Occupational Therapy, University of Exeter (2002) PhD in Professional Identity Development, University of Brighton (2012) Her research focuses on practice learning , professional identity formation , and diverse clinical placements . She pioneered curriculum reforms requiring all Brighton occupational therapy students to complete placements in non-traditional settings. Her work in interpretative phenomenological analysis has shaped understanding of therapist-patient interactions across physical and mental health domains. Recent publications examine placement diversification in podiatry and identity development in UK community roles. She has developed a digital platform for occupational therapists and organizes annual conferences on diverse practice settings. Her teaching methodology combines problem-based learning with experiential theories, creating student-centered environments that emphasize critical reasoning and reflective practice. AdvanceHE National Teaching Fellowship (2024) Two Excellence in Facilitating Learning Awards (University of Brighton) As an MSc/PhD supervisor, she guides research on practice education, occupational science, and therapeutic interventions. Her Higher Education Academy grant funded the creation of authentic digital learning triggers that facilitate lifelong learning readiness. Active collaborations span multiple UK institutions, focusing on clinical education reform and therapist-patient dynamics.
Jianke Zhu is a Professor at the College of Computer Science and Technology of Zhejiang University . He obtained his Ph.D. in Computer Science and Engineering from The Chinese University of Hong Kong and conducted postdoctoral research at the BIWI Computer Vision Lab, ETH Zurich . His research focuses on Computer Vision and Machine Learning , with a particular emphasis on 3D scene understanding, LiDAR-based mapping, and neural rendering. Dr. Zhu’s research spans several subfields, including 3D Reconstruction , Semantic Segmentation , Multimodal Learning , and Autonomous Driving . His work integrates Neural Networks , LiDAR Processing , and Uncertainty Quantification to address challenges in real-time and adverse conditions. Selected Recent Trends: 2025 publications highlight his work in Hexagonal Mesh-based Neural Rendering , Instance-aware 3D Scene Understanding , and Efficient Visual Projectors for Multimodal LLMs . Earlier works include Box2Mask for Instance Segmentation (2024) and Token Selection for Point Cloud Learning (2025). Scientific Awards : Senior member of the IEEE Advising and Grants : As a Doctoral Supervisor , he mentors students in advanced topics like LiDAR Odometry and Multi-view Stereo Recovery . His projects have attracted funding for autonomous driving , 3D scene modeling , and neural rendering .
Hala Lamdouar is a Research Fellow at the University of Oxford , specifically affiliated with the Institute of Biomedical Engineering (IBME). She works under the supervision of Professor Alison Noble and completed her DPhil (PhD) at Oxford's Visual Geometry Group (VGG), advised by Professor Andrew Zisserman and Professor Weidi Xie . Her academic journey began with an Engineering degree in signal and image processing from ENSEIRB-MATMECA , Bordeaux, France, followed by a Master's in applied mathematics focusing on machine learning and computer vision at Ecole Normale Superieure , Paris, where she also worked on autonomous driving perception solutions for Valeo . Education Engineering degree, ENSEIRB-MATMECA, Bordeaux MSc in Applied Mathematics (MVA), Ecole Normale Superieure DPhil (PhD), Visual Geometry Group, University of Oxford Lamdouar's research centers on Video Understanding through single and multi-modal learning, particularly in clinical settings and challenging datasets. Key contributions include motion segmentation techniques for detecting camouflaged objects, the creation of the MoCA dataset (Moving Camouflaged Animals), and scalable synthetic data pipelines for motion-based object segmentation. Her work combines ConvNets, Transformers, and optical flow analysis to address partial occlusion and motion absence in videos. Notable achievements include the Best Paper Award at the CVPR Workshop on Robust Video Scene Understanding (2021). She has published in top conferences like BMVC (2021), ICCV (2021), and ACCV (2020), with applications in biomedical imaging, autonomous systems, and unsupervised learning. Additional affiliations include the Centre for Doctoral Training in Autonomous Intelligent Machines & Systems (AIMS).
Dr. Erick Hung is a Professor of Clinical Psychiatry in the Department of Psychiatry and Behavioral Sciences at the University of California, San Francisco (UCSF) School of Medicine. He serves as the Associate Dean for Students in the UCSF School of Medicine and is a member of the UCSF Academy of Medical Educators. Previously, he was the Program Director of the Adult Psychiatry Residency Training Program (2012-2022) and Director of Curricular Affairs for GME (2015-2022). M.D. from UCSF School of Medicine (2004) Psychiatry Residency from UCSF (2008) Forensic Psychiatry Fellowship from UCSF (2009) Diversity, Equity, and Inclusion Champion Training (2017) Dr. Hung's research focuses on primary care and mental health integration, forensic psychiatry, HIV psychiatry, and LGBTQ mental health. His educational scholarship centers on competency-based assessment, faculty development, and near-peer learning. His forensic expertise includes psychiatric injury in the workplace, LGBTQ workplace harassment, neuropsychiatric issues related to HIV, and immigration custody. His publication record demonstrates consistent contributions to medical education, particularly in psychiatry residency training, competency assessment, and global mental health initiatives. Recent publications focus on implementing competency-based frameworks, longitudinal clinical experiences, and mental health self-disclosure. UCSF Academy of Medical Educators, Excellence in Teaching Award (2010) Association of Academic Psychiatry Junior Faculty Award (2012) UCSF Teaching Scholars Program (2013) UCSF Excellence and Innovation Award in GME (2014) UCSF Academic Senate Teaching Award (2014) As a mentor, Dr. Hung works with trainees interested in medical education, interprofessional education, forensic psychiatry, HIV psychiatry, LGBT mental health, and integrated care. He serves as faculty mentor for career development and research projects. His leadership roles include directing residency programs and curricular affairs, demonstrating significant administrative contributions to medical education. Dr. Hung also directs initiatives related to diversity, equity, and inclusion, having completed specialized training in this area.
