Jiannong Cao is a Chair Professor and Director of the University Research Facility in Big Data Analytics at the Department of Computing, Hong Kong Polytechnic University. He has held various academic roles since 1990, including Assistant Professor at City University of Hong Kong and Lecturer at Australian universities. PhD in Computer Science, Washington State University (1990) MSc in Computer Science, Washington State University (1986) BSc in Computer Science, Nanjing University (1982) His research focuses on cloud and edge computing , parallel and distributed computing , and mobile computing , with significant contributions to wireless sensor networks (WSN) for structural health monitoring (SHM) and software-defined networking (SDN) for vehicular communications. Recent work includes WiFi-based non-invasive health monitoring systems and multi-user computation partitioning in mobile cloud environments. Dr. Cao’s publications demonstrate trends in WSN optimization , SDN architectures , and cognitive modeling for network embedding , with applications in smart healthcare , transportation systems , and industrial IoT . Ministry of Education Natural Science Award (2018) ACM Distinguished Member (2017) IEEE Fellow (2014) Best Paper Awards at IEEE DSAA, SMARTCOMP, WCNC He has mentored numerous researchers, including Linchuan Xu , Xuefeng Liu , and Weigang Wu , who have authored key publications in top venues like ACM WSDM and IEEE INFOCOM . His professional roles include chairing IEEE committees and serving on grant panels for the Hong Kong Research Grant Council.
Alan Bovik is the Cockrell Family Regents Endowed Chair Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin's Cockrell School of Engineering. He also holds positions at The Institute for Neurosciences and serves as Director of the Laboratory for Image and Video Engineering (LIVE). With a career spanning over three decades at UT Austin, he has progressed from Assistant Professor (1984-1988) to Associate Professor (1988-1994) to his current position as Full Professor (1994-present). Dr. Bovik received his Ph.D. in Electrical and Computer Engineering in 1984 from the University of Illinois, Urbana-Champaign. Professor Bovik's research focuses on image and video quality assessment, visual perception, and digital media processing. He is renowned for developing groundbreaking algorithms including the Structural Similarity (SSIM) index, Visual Information Fidelity (VIF), and various blind quality assessment models like BRISQUE and NIQE. His work bridges engineering and neuroscience, creating perception-based models that optimize visual media delivery while reducing bandwidth consumption. These innovations have had profound industry impact, with his algorithms processing a significant proportion of global internet video traffic. His recent publications demonstrate continued leadership in perceptual quality assessment, with increasing focus on AI-generated content, high dynamic range (HDR) video, and novel applications in medical imaging. The research shows a clear trajectory toward more sophisticated, neural network-based quality metrics that better align with human visual perception across diverse content types. Professor Bovik has received numerous prestigious awards recognizing his contributions to the field: John Fritz Medal (2024) IEEE Edison Medal (2022) IAMB BaM Award (2022) Elected to the United States National Academy of Engineering (2022) Technology and Engineering Emmy Award (2021) IEEE Fourier Award for Signal Processing (2019) Progress Medal from The Royal Photographic Society (2019) Named Honorary Fellow of The Royal Photographic Society (2019) Primetime Emmy Award (2015) Edwin H. Land Medal from The Optical Society (2017) As Director of the Laboratory for Image and Video Engineering (LIVE), Professor Bovik has secured substantial research funding from organizations including the National Science Foundation and the National Institute for Standards and Technologies. His lab has produced numerous influential datasets including the LIVE Image and Video Quality Databases. He has mentored many successful students who have gone on to make significant contributions in academia and industry, though specific student names are not provided in the source materials. The Laboratory for Image and Video Engineering (LIVE) under Professor Bovik's direction has become a world-renowned center for research in perceptual image and video quality. The lab maintains close collaborations with major technology companies including Netflix, Amazon, and YouTube, ensuring that research has direct practical applications. LIVE has developed numerous influential tools and databases that are widely used in both academic research and industrial applications worldwide.
Adam Jatowt is a Professor and Head of the Data Science group at the Department of Computer Science, University of Innsbruck. He also serves as Deputy Head of the Digital Science Center and Research Center for Digital Humanities. His academic career spans roles at Kyoto University (2010-2020), National Institute of Advanced Industrial Science and Technology (AIST), and visiting positions at Karlsruhe Institute of Technology, University of La Rochelle, and University of California Berkeley. Research interests focus on temporal aspects of NLP/IR, computational history, large language models, and future forecasting. He leads projects combining digital humanities with advanced AI techniques, including temporal validity assessment and hint generation systems. Recent publications (2025) emphasize LLM applications in temporal analysis, QA systems, and energy sector digitalization. His work has been recognized through awards like the Friedrich Wilhelm Bessel Research Award (2024) and top-cited paper distinction in Information Sciences. He actively organizes conferences like ECIR 2026 and Text2Story workshops. Key contributions include developing WikiHint dataset, PlausibleQA framework, and tools like Rankify. His research also addresses societal challenges through ESG rating prediction and medical LLM applications.
Henry Jäger is a Professor in Food Technology at the University of Natural Resources and Life Sciences, Vienna (BOKU) since 2014. Previously, he worked as a Project Manager at Nestlé (2012-2014) and Lecturer at TU Berlin (2012-2017), following his PhD/Postdoc at TU Berlin (2006-2012) and Diploma in Food Technology (2000-2006). His research focuses on electrotechnologies in food processing , particularly pulsed electric fields (PEF) and ohmic heating , for microbial inactivation, food preservation, and quality optimization. He explores applications in plant material processing , gluten-free baking , and novel food preservation methods . His work also addresses edible insect processing for allergenicity reduction and protein recovery. Recent publications (2025-2024) analyze synergies between PEF and ohmic heating, biofilm imitation systems for hygiene validation, and computational models for sterilization processes. These studies span food safety , sustainable processing , and functional food design . Henry Jäger actively contributes to scientific communities, serving on the EFFoST managing board , as scientific advisor for food conferences, and as reviewer for journals like Food Chemistry and Trends in Food Science & Technology . He has organized workshops on PEF applications and contributed to EU food technology initiatives.
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.
Chris Marone is a Full Professor (Professore Ordinario) at La Sapienza Università di Roma since 2020, with prior roles as Professor of Geophysics at The Pennsylvania State University (2003–2020) and Associate/Assistant Professor at MIT (1997–2000, 1992–1997). His research spans earthquake physics, geomechanics, and rock deformation. Ph.D. in Geophysics from Columbia University (1988) 40+ years of academic experience across multiple institutions His work focuses on frictional mechanics, slow earthquakes, and fault slip behaviors, integrating laboratory experiments and field observations. Recent themes include rate-state friction laws, rock-fluid interactions, and granular mechanics. Key trends in his publications reveal interdisciplinary approaches combining deep learning (2022), high-frequency seismic signatures (2022), and poromechanics (2022) with traditional geophysical methods. His research has dominated fault healing and stress dynamics for decades. ERC Advanced Grant: TECTONIC Louis Néel Medal (European Geosciences Union) Fellow of the American Geophysical Union Paul F. Robertson Award for Breakthrough of the Year Kerr-McGee Career Development Professorship
Syukuro Manabe is a renowned climate scientist affiliated with Princeton University's Atmospheric and Oceanic Sciences Program as a Professor . He has held various prestigious roles, including Director of the Global Warming Research Program at the Frontier Research System for Global Change (1997–2001) and Senior Scientist at the Geophysical Fluid Dynamics Laboratory (GFDL) of NOAA (1995–1997). Education: BS, Tokyo University (1953) MS, Tokyo University (1955) PhD, Tokyo University (1958) Research Interests: Manabe pioneered the development of radiative-convective models of the atmosphere in the early 1960s, focusing on greenhouse gases' role in climate change. His work with Kirk Bryan in the late 1960s on coupled atmosphere-ocean-land general circulation models revolutionized climate simulation, enabling studies of global warming and natural climate variability across time scales. He also explores past climate changes using models of varying complexity. Scientific Awards and Honors: Nobel Prize in Physics (2021) for physical modeling of Earth's climate and predicting global warming Carl-Gustaf Rossby Research Medal (1992) Blue Planet Prize (1992) Volvo Environmental Prize (1997) William Bowie Medal (2010) Franklin Institute Awards (2015) Professional Memberships: Member, National Academy of Sciences (1990–) Foreign Member, Academia Europaea (1994–) Fellow, American Meteorological Society (1997–) Fellow, American Geophysical Union (since 1967)
Uwe Zdun is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice-Director of Studies for Computer Science and Head of the Research Group Software Architecture. His teaching portfolio includes core courses such as Software Engineering 2, Advanced Software Engineering, and Practical Software Courses for Bachelor's and Master's theses across multiple semesters (2024W-2025S). His research spans software architecture with emphasis on microservices, cloud computing, and DevOps. Key focus areas include architectural design decisions, infrastructure-as-code conformance, security in distributed systems, and the integration of machine learning operations (MLOps/RLOps). He investigates cognitive aspects of architecture practices through controlled experiments and develops model-driven approaches for quality assessment in complex systems. Recent publications (2024-2026) reveal three dominant trends: (1) Security and coupling analysis in infrastructure-as-code deployments, (2) MLOps/RLOps integration for Industry 4.0 cyber-physical systems, and (3) Performance optimization patterns for CI/CD pipelines and autoscaling. His work bridges theoretical architecture models with industrial practice, particularly in microservice ecosystems and reinforcement learning applications. Professor Zdun leads the Research Group Software Architecture at the University of Vienna's Faculty of Computer Science. The group focuses on empirical validation of architectural patterns, tool development for conformance checking, and advancing design decision methodologies in cloud-native and AI-driven systems.
Lars Nyberg is a Professor of Neuroscience at Umeå University's Medical Faculty and Director of the Umeå Centre for Functional Brain Imaging (UFBI) since 2001. He has held concurrent roles as Guest Professor in Bergen and Oslo, Norway, and led the Wallenberg Centre for Molecular Medicine (WCMM) from 2019. His academic leadership includes directing major initiatives like the EU-funded Lifebrain project (2017–2022) and holding the Torsten & Ragnar Söderberg Research Professorship in Medicine (2012–2017). Education: PhD in Psychology (1993) and Docent (1996) from Umeå University, with postdoctoral training at the Rotman Research Institute, Toronto. His research focuses on neuroimaging techniques (MRI/PET), dopamine systems, working memory, aging, and episodic memory. Key contributions include linking dopamine receptor availability to cognitive decline and demonstrating brain maintenance mechanisms in aging. Research Interests: Neuroimaging of memory systems, dopamine's role in cognition, aging-related brain changes, and cognitive reserve. Grants: EU Horizon 2020 (Lifebrain, €10M), KA Wallenberg Scholarships (2009, 2016), Swedish Research Council funding for COBRA (2013–2017). His awards include Royal Swedish Academy of Sciences membership (2008), Mångbergs Prize in Neural Sciences (2008), and multiple Wallenberg grants. Nyberg has supervised 27 PhD students and 11 postdocs, advancing translational neuroscience and aging research through interdisciplinary teams at UFBI and WCMM.
Univ.-Prof. Aiko Voigt is a Professor and Head of the Department of Meteorology and Geophysics at the University of Vienna. Her research focuses on climate dynamics, cloud physics, and atmospheric processes. She leads the Environment and Climate Research Hub and teaches advanced courses like 'Climate Modelling Lab' and 'Cloud Physics.' Her work explores cloud-radiative interactions, climate change impacts, and extreme weather dynamics. Recent studies analyze energy imbalances, high-cloud feedbacks, and tropical precipitation patterns. Voigt's contributions bridge climate modeling with observational data, emphasizing high-resolution simulations and interdisciplinary approaches. Teaching includes courses such as 'Climate System of the Earth,' 'Scientific Communication,' and 'Introduction to Computational Meteorology.' Her research spans from present-day climate to Snowball Earth scenarios, addressing both modern and paleoclimatic challenges. Publications highlight advancements in radiative transfer algorithms, cyclone dynamics under warming, and uncertainties in climate model predictions. Her work underscores the critical role of clouds in amplifying climate sensitivity and reshaping atmospheric circulation patterns.
Prof. Pierre Jaïs serves as University Professor in Cardiology and Cardiac Electrophysiology at the University of Bordeaux and Head of the Electrophysiology Unit at Bordeaux University Hospital. He concurrently leads the Electrophysiology and Heart Modeling Institute (LIRYC) as CEO since 2021, driving innovation in cardiac rhythm disorder treatments through multidisciplinary research. His research revolutionized cardiac electrophysiology by identifying pulmonary veins as primary sources of atrial fibrillation, establishing pulmonary vein isolation as the global treatment standard. Current work focuses on pulsed field ablation—a non-thermal technique with potential to replace conventional ablation—and developing advanced imaging for precise arrhythmia targeting, reflecting his commitment to translating scientific discovery into clinical solutions. Analysis of recent publications (2017-2021) reveals dominant trends in pulsed field ablation optimization, comparative ablation techniques, and AI integration in cardiovascular imaging. These works consistently address atrial fibrillation treatment efficacy, safety profiles, and technological innovation, positioning him at the forefront of electrophysiology advancement. His distinguished contributions are recognized through prestigious awards including: 2019: Eli S. Gang Most Innovative Abstract Award (Heart Rhythm Society) 2018: Eric N. Prystowsky Lectureship Award 2012: Academy of Medicine Membership (Paris) 2009: Circulation Best Paper Award Multiple National Academy of Medicine honors Prof. Jaïs actively mentors electrophysiology trainees and secures substantial research funding, notably leading an EU-funded randomized trial comparing pulsed field versus thermal ablation. His LIRYC institute integrates cardiology, engineering, and computational expertise to accelerate therapeutic innovation. The LIRYC institute operates as a collaborative hub where clinicians, biomedical engineers, and data scientists develop next-generation electrophysiology tools. Current projects include real-time arrhythmia mapping systems, tissue-selective ablation protocols, and AI-driven predictive models for treatment personalization, fostering seamless translation from bench to bedside.
Marco Di Renzo is a CNRS Professor (Directeur de Recherche Titulaire) at University of Paris-Saclay, affiliated with CentraleSupelec and the Signals and Systems Laboratory (L2S). He serves as Coordinator of the Communications Networks Area at the DigiCosme Laboratory of Excellence and Editor-in-Chief of IEEE Communications Letters. His academic leadership includes membership in the Ph.D. School on ICT Admission Committee at Paris-Saclay University. His educational background includes a Laurea (cum laude) and Ph.D. in Electrical Engineering from University of L'Aquila, Italy (2003, 2007), and a Habilitation à Diriger des Recherches from University Paris-Sud (2013). Laurea (cum laude), Electrical Engineering, University of L'Aquila (2003) Ph.D., Electrical Engineering, University of L'Aquila (2007) Habilitation à Diriger des Recherches, University Paris-Sud (2013) Di Renzo's research focuses on next-generation wireless communications, particularly reconfigurable intelligent surfaces (RIS), 6G technologies, and stochastic geometry modeling. His work bridges theoretical communication theory with practical implementations in cellular networks, millimeter-wave communications, and ultra-wide band systems. Recent publications demonstrate leadership in holographic metasurfaces, integrated sensing and communication (ISAC), and AI-empowered network design, establishing him as a pioneer in electromagnetic wave manipulation for future networks. His award-winning publications span RIS-aided communications, channel modeling, and security frameworks. Analysis of his recent work reveals consistent focus on three pillars: (1) fundamental electromagnetic theory for wave manipulation, (2) practical RIS implementations across frequency bands, and (3) integration with AI for network optimization. His articles frequently address industrial applications including factory automation and space-air-ground networks. Di Renzo's scientific recognition includes: IEEE Fellow (2020) and IET Fellow (2020) Highly Cited Researcher (Web of Science, 2019) SEE-IEEE Alain Glavieux Award (2017) Multiple Best Paper Awards (IEEE ICC, EURASIP) Nokia Foundation Visiting Professorship (2020) As Principal Investigator for CNRS, he coordinates multiple Horizon 2020 projects including SURFER, PathFinder, and MetaWireless. His leadership extends to serving as Project Coordinator for H2020 5Gwireless, 5Gaura, MAPNET, and REDESIGN. With over 350 publications, 17,000+ citations, and h-index of 66+, his research group maintains strong industry partnerships with Nokia and other telecommunications leaders. Di Renzo directs the Signals and Systems Laboratory (L2S) at Paris-Saclay and coordinates the DigiCosme Excellence Lab's Communications Networks Area. His team specializes in electromagnetic modeling for wireless networks and has pioneered the European Telecommunications Standards Institute (ETSI) Industry Specification Group on RIS. The group maintains active collaborations with Aalto University (Finland), University of Technology Sydney (Australia), and University of L'Aquila (Italy).
Kiemeney Lambertus is a Professor of Cancer Epidemiology at the Department of Health Evidence, Radboud University Medical Center in Nijmegen, Netherlands. He serves as Chair of the Department of Health Evidence and Scientific Director of the Radboud Institute for Health Sciences. His academic career includes roles as Head of the Department of Cancer Registry and Research, and Director of Research at the Netherlands Comprehensive Cancer Organisation. Lambertus holds a Master's in Biomedical Sciences (cum laude) from Radboud University and a Bachelor's in Physiotherapy (cum laude). His research focuses on urological cancers, genetic and clinical epidemiology, and biobanking. Key areas include prostate and bladder cancer genetics, risk prediction models, and validation of biomarkers like PCA3. He has pioneered studies on FGFR3 and JAG1 genes in bladder cancer susceptibility, and demonstrated the safety of coal tar treatments in dermatology. His over 500 publications include foundational work in genome-wide association studies (GWAS), with a Nature Genetics paper on bladder cancer susceptibility genes cited over 200 times. Lambertus has received global recognition including the Dominique Chopin Distinguished Researcher Award and inclusion in Thomson Reuters' most influential scientists list. Teaching Excellence: Multiple lecturer-of-the-year awards highlight his educational contributions. Leadership: Oversee large research institutes and national cancer initiatives. Global Impact: Collaborates with institutions worldwide, including Johns Hopkins University and the European Institute of Oncology. Current research emphasizes translational studies linking genetic discoveries to clinical outcomes, with a focus on reducing overdiagnosis in prostate cancer screening.
Jürgen Gauss is a Professor of Theoretical Chemistry at Johannes Gutenberg-Universität Mainz, Germany. With over 350 publications and an h-index of 85 (ISI WebOfScience)/96 (Google Scholar), his work focuses on high-accuracy quantum-chemical methods for energy and property calculations. Education: PhD in Theoretical Chemistry (1988), Universität zu Köln Positions: Full Professor (2001-present), Associate Professor (1995-2001), Research Associate (1991-1995), Postdoctoral Researcher (1990-1991) His research revolutionized NMR chemical shift calculations through the GIAO-MP2 scheme, extended to Cholesky decomposition techniques. He pioneered the first CCSD(T)-level analytic second derivatives for magnetic properties and developed the HEAT protocol for sub-kJ/mol thermochemical accuracy. Scientific Awards: Carl-Duisberg Gedächtnispreis (1996) Medal of International Academy of Quantum Molecular Science (1997) Akademiepreis (2003) Gottfried-Wilhelm Leibniz-Prize (2005) Foreign Member, Norwegian Academy of Science and Letters (2018) Advisees: Current PhD students include Sophia Burger, Florian Mast, Max Erichsen, and Malte Hellmann. His group develops the widely-used CFOUR quantum chemistry software package (over 1,000 licenses).
Professor Celso Grebogi, Sixth Century Chair in Nonlinear & Complex Systems at the University of Aberdeen, is a globally recognized leader in nonlinear dynamics , chaos theory , and systems biology . He founded the Institute for Complex Systems and Mathematical Biology and co-founded the Aberdeen-Lanzhou-Tempe Research Centre. His career spans institutions including University of Maryland, University of São Paulo, and Max-Planck-Society (External Scientific Member since 1998).
