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.
Atakan Aral serves as an Associate Professor at the Faculty of Computer Science, University of Vienna, where he leads research in edge computing, distributed systems, and environmental monitoring applications. His work focuses on developing efficient and resilient computing systems for environmental applications, with particular emphasis on neuromorphic edge AI and the cloud-edge continuum. He maintains an active teaching schedule offering courses in Distributed Systems Engineering, Cloud Computing, and Practical Software Courses with Bachelor's Thesis work across multiple semesters through 2025. Dr. Aral's research interests span several critical areas in modern computing including edge computing architectures, federated learning approaches, neuromorphic computing for environmental monitoring, and resilient systems design. His work addresses fundamental challenges in resource-constrained environments, particularly focusing on latency-sensitive applications and energy-efficient computation. The interdisciplinary nature of his research bridges theoretical computer science with practical environmental applications, developing systems that can operate effectively in remote or resource-limited settings. Analysis of his recent publication trajectory reveals a clear evolution from foundational cloud computing research toward increasingly specialized edge intelligence systems. Early work focused on resource allocation and scheduling in cloud environments, while his current research emphasizes neuromorphic approaches for sustainable environmental monitoring. His publications demonstrate growing interdisciplinary collaboration, particularly with environmental scientists, and increasing focus on practical implementations of theoretical concepts in real-world monitoring systems. Dr. Aral leads significant research projects including TROCI (Towards Resilient Operation of Critical Infrastructure), an ongoing initiative, and SWAIN (Sustainable Watershed Management Through IoT-Driven AI), which ran from February 2021 to February 2024. His work spans multiple dimensions of computing systems, from hardware-aware algorithms to application-level implementations, with consistent contributions to major conferences and journals in distributed systems and edge computing. He is an active member of the Scientific Computing research group at the University of Vienna, working from Room 6.49 at Währinger Straße 29. His research environment includes collaboration with the Environment and Climate Research Hub, reflecting the interdisciplinary nature of his work that bridges computer science with environmental applications. His publications indicate strong international collaboration across European institutions and research groups.
Claudia Plant is a Professor in the Faculty of Computer Science , leading the Research Group Data Mining and Machine Learning . Her research focuses on clustering algorithms, data mining, and machine learning applications in areas like biomedical data, wind energy, and causality inference. She has contributed to projects such as Knowledge-infused Deep Learning for Natural Language Processing (2020–2028) and Hybrid Computational Sciences (2021–2021). Plant has authored over 160 publications, with recent work emphasizing deep learning, anomaly detection, and GPU-optimized algorithms. She actively engages in academic activities, including talks on clustering methods and interdisciplinary projects like Governing Algorithms: The Politics of Data and Decision-Making . Her research interests span clustering algorithms , graph neural networks , causality discovery , and ethical digital transformation . Notable projects include causal analysis of wind farm dynamics and AI-enhanced education tools. Plant’s work bridges computational methods with societal challenges, such as empowering marginalized communities through ethical technology adoption.
Luca Cardelli is a Principal Researcher and Assistant Director at Microsoft Research Cambridge, UK, since 1997. He holds visiting professorships at Imperial College London (Department of Computing, 2004–2009) and the University of Trento (2005–2007). He earned his PhD in Computer Science from the University of Edinburgh in 1982. His research spans type theory , molecular programming , and principles of programming languages , with applications to systems biology and concurrency theory. Notable contributions include formal frameworks for modeling biochemical systems (e.g., the stochastic π-calculus) and designing DNA-based circuits. Key achievements include the AITO Dahl-Nygaard Senior Prize (2007) and multiple Most Influential Paper Awards at POPL and ETAPS. His work bridges computer science and biology, advancing both theoretical foundations and practical molecular computing.
Dario Vretenar is a Professor of Physics at the Department of Physics, Faculty of Sciences, University of Zagreb (since 2001). He has held academic roles including Associate Professor (1997-2001) and Assistant Professor (1993-1997). His research focuses on theoretical nuclear physics, particularly energy density functional theory, nuclear weak interactions, and computational physics. He has held visiting positions at institutions such as Technical University Munich (Visiting Professor, 1999-2000) and University of Tokyo (2010). Education: Ph.D. in Theoretical Nuclear Physics (University of Zagreb, 1988); M.Sc. in Physics (University of Zagreb, 1982). Postdoctoral fellowships included Yale University (1990) and Alexander von Humboldt Fellowships at Technical University Munich (1991-1993, 1997). Research Interests: Algebraic structure models for high-angular momentum states Low-energy nuclear effective field theory Nuclear astrophysical applications Development of relativistic energy density functionals Publications: Over 210 peer-reviewed articles (h-index 43, 7,000+ citations), 8 books, and 100+ conference contributions. Notable works include studies on nuclear clustering, quantum phase transitions, and neutron skin structure. Awards: Croatian Academy of Science and Arts Award for Science and Mathematics (2002) Croatian National Award for Science (2003) Fellow of the Croatian Academy of Sciences and Arts (2012) Service Roles: President of the Croatian Science Foundation (2013–present) Chair of the Physics Committee, Agency for Science and Higher Education, Croatia (2009–present) Board Member of Euroschool on Exotic Beams (2012–present) Teaching: Courses include Quantum Physics, Nuclear Structure, and Nuclear Astrophysics at undergraduate and graduate levels. Supervised numerous students in theoretical nuclear physics.
Alessandro Astolfi is a Professor of Nonlinear Control Theory in the Department of Electrical and Electronic Engineering at Imperial College London, where he has been faculty since 1996. He also holds a professorship at the Department of Civil Engineering and Computer Science Engineering at the University of Rome Tor Vergata since 2005. From 2022 to 2025, he serves as College Consul for the Faculty of Engineering and Business School, and previously served as Head of the Control and Power Group from 2010 to 2022. His research expertise spans multiple areas of control theory: Nonlinear control theory Adaptive and robust control Discontinuous stabilization Model reduction Geometric control theory Observer design Astolfi's work has produced significant applications across diverse fields including aerospace systems (under-actuated satellites, autonomous aircraft), power systems (multi-machine systems), game theory (population dynamics, multi-agent systems), and industrial processes (model reduction applications). His research contributions have been recognized with numerous prestigious awards: 2003 Philip Leverhulme Prize for outstanding research achievements of young scholars 2007 IEEE Control Systems Society Antonio Ruberti Young Researcher Prize 2009 IEEE Fellow for contributions to nonlinear control theory 2009 Googol Best New Application Paper Award 2012 George S. Axelby Outstanding Paper Award 2012 IEEE CSS Distinguished Member Award 2015 Sir Harold Hartley Medal from the Institute of Measurement and Control (UK) Professor Astolfi has authored more than 120 journal papers, 30 book chapters, and over 240 conference papers. He co-authored the monograph 'Nonlinear and Adaptive Control with Applications' (Springer-Verlag). He currently serves as Chair of the IEEE CSS Conference Editorial Board and has participated in program committees of numerous international conferences. His research group at Imperial College London maintains strong connections with academic institutions worldwide including ETH Zurich, Rice University, and SUPELEC, with whom he has established visiting lecturer relationships spanning decades.
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.
Cornelia Schneider is a Professor and Head of the Institute of Computer Science at the University of Applied Sciences Wiener Neustadt. She leads research in digital health and care technologies, focusing on applications like Augmented Reality, sensor data analysis, and social robotics for vulnerable populations. Her work emphasizes user-centered design and has been supported by projects funded by FFG and the Active Assisted Living Programme. Her research spans telemedicine infrastructure, elderly care robotics, and health monitoring systems. Notable projects include 24/7-Digital (2023-2026), Care about Care (2021-2023), and AgeWell (2019-2022). She has pioneered solutions like CARU cares and DigiCare training programs. Dr. Schneider has been recognized with the AAL Award (2014) and the tecnet | accent Innovation Award (2021). She coordinates interdisciplinary teams and actively participates in conferences like Health Informatics Meets Digital Health. Her lab collaborations include FOTEC and Salzburg Research, where she previously led the e-Health Competence Center until 2019.
Cesare Franchini is a full Professor at the University of Vienna's Faculty of Physics, leading the Computational Materials Physics research group. His work focuses on theoretical understanding and computational modeling of quantum materials using first principles methods, particularly VASP. He maintains an active research program with numerous postdocs, PhD students, and collaborations across multiple institutions including the University of Bologna. Professor Franchini's research centers on quantum materials with many interacting degrees of freedom (lattice, spin, and electron orbital) that enable novel electronic and magnetic phases. His specific interests include metal-insulator transitions, polaron physics (electron-phonon interactions), non-collinear spin orderings, topological Dirac/Weyl phases, multiferroism, and superconductivity. He has increasingly incorporated machine learning data-driven tools and diagrammatic Monte Carlo techniques into his computational approaches. Analysis of his recent publications (2024-2025) reveals a strong focus on polaron physics across multiple material systems, with significant work on hematite, titanium dioxide, and quantum paraelectrics like KTaO3. His research increasingly integrates machine learning with traditional first-principles methods, particularly for studying hydrogen diffusion, surface science phenomena, and electronic structure calculations. There's also substantial work on single-atom catalysis and the application of advanced computational techniques to understand fundamental charge transport mechanisms in energy materials. Professor Franchini actively supervises numerous PhD students and postdocs, including Andrea Angeletti, Viktor Birschitzky, Lorenzo Celiberti, and several others working on diverse aspects of computational materials physics. He leads or participates in major research projects including TACO (Taming Complexity in Materials Modeling), DCAFM (Doctoral College Advanced Functional Materials), and the recently launched Spin-orbit entangled anharmonic polarons project. His group maintains strong collaborations with experimentalists at Charles University, Technical University of Vienna, and other international institutions.
Gheorghe Paun is a Senior Researcher at the Institute of Mathematics of the Romanian Academy (1994–present) and a Visiting Researcher at the University of Sevilla (2009–present). He earned his Ph.D. in Mathematics from the University of Bucharest (1977), supervised by Solomon Marcus. His research spans Automata and Language Theory (descriptional complexity, regulated rewriting), Natural Computing (DNA computing, membrane computing), and he is the initiator of membrane computing . Education : M.Sc. in Mathematics (1974), University of Bucharest (specialization: computer science) Ph.D. in Mathematics (1977), University of Bucharest His work includes foundational contributions to DNA computing (book DNA Computing. New Computing Paradigms , 1998) and membrane computing (book Membrane Computing. An Introduction , 2002). He has collaborated with over 100 researchers globally and advised multiple Ph.D. students, including Victor Mitrana and Gianina Georgescu. His scientific awards include the Gheorghe Lazar award (1981), Corresponding Member of the Romanian Academy (1997), Doctor Honoris Causa from Silesian University of Opava (2007), and recognition as an ISI Highly Cited Scientist (2007). He also holds honorary citizenships in Curtea de Arges (1998), Arges County (2007), and Cicanesti village (2009). Paun has served on editorial boards for journals like Theoretical Computer Science. Natural Computing Series and Natural Computing , and organized major workshops in membrane computing. His academic contributions include over 150 publications and editorial roles in 20+ journals.
François Peeters is a Full Professor of Physics at the University of Antwerp, Belgium, holding the position since 2000 (with Dutch title 'gewoon hoogleraar' since 2003). He previously served as Research Director (FWO-VI) at the University of Antwerp (1996-1999), Research Leader (NFWO) (1992-1996), and Senior Research Assistant (NFWO) (1988-1992), establishing a distinguished academic career spanning over three decades. His educational background includes a Ph.D. in Physics from the University of Antwerp (1982), followed by a Habilitation (Hoger aggregaat) from the same institution (1987), and a postdoctoral fellowship at Bell Laboratories in Murray Hill, New Jersey (1982-1983). His academic journey also featured research periods at prestigious institutions including the High Magnetic Field Laboratory in Grenoble, University of California Berkeley, Oxford University, and several Brazilian and Australian universities. Peeters' research focuses on theoretical condensed matter physics , specializing in the electronic, optical, and magnetic properties of nanostructured systems. His work encompasses semiconductors , superconductors , graphene , and hybrid quantum systems , with particular emphasis on strong correlations in both classical (colloids, dusty plasma) and quantum (quantum dots) environments. His theoretical frameworks bridge fundamental quantum mechanics with practical nanotechnology applications, driving innovations in spintronics and quantum device design. Analysis of his publication record reveals a clear evolution from foundational work on polaron physics and quantum Hall systems in the 1980s-1990s toward contemporary research on graphene, topological materials, and programmable quantum nanodevices. His most cited works demonstrate consistent leadership in mesoscopic physics, with recent publications showing increased focus on spin-dependent transport phenomena and two-dimensional material systems. His scientific recognition includes: Fellowship in the American Physical Society (2005) APS Outstanding Referee award (2008) Doctor Honoris Causa from University of Szeged, Hungary (2009) Peeters has supervised 26 completed PhD theses and currently leads the Condensed Matter Theory research group comprising 3 ZAP researchers, 16 PhD students, and 8 postdocs. His grant portfolio includes coordination of an EU Marie Curie Training site on 'Electrons on helium', participation in multiple EU projects, COST actions, and ESF networks, demonstrating sustained success in securing competitive international funding. The Condensed Matter Theory group maintains extensive international collaborations, evidenced by Peeters' research visits to over 10 institutions worldwide and regular hosting of 3-4 international visitors at postdoc or professorial levels. The group's output of over 770 refereed publications with 12,000+ citations reflects its position at the forefront of theoretical condensed matter physics research.
Julian Jauk is a Researcher at the Institute for Architecture and Media, TU Graz. His work focuses on innovative material systems, digital fabrication, and sustainable architectural design. He explores the integration of clay composites, mycelium-based materials, and knitted structures with advanced manufacturing techniques like 3D printing. Key research themes include lightweight ceramic structures, biocomposite materials, and computational design methodologies. His research emphasizes material-driven innovation, structural optimization, and environmental sustainability. Notable projects include MyCera (clay-mycelium composites) and ClayKnit (3D-printed clay-knitted hybrids). He also investigates mixed reality tools for architectural sketching and kinetic architectural prototypes. Publications from 2021–2024 highlight trends in bio-based materials, additive manufacturing, and material-property analysis. His work bridges traditional craftsmanship with cutting-edge digital fabrication, aiming to redefine sustainable building practices.
Markus Vincze is an Associate Professor at the Institute of Automation and Control Engineering (ACIN) at Vienna University of Technology (TU Wien). He founded the Vision for Robotics (V4R) group in 1996 to advance robotic perception, particularly in real-world environments and homes. His work focuses on cognitive computer vision techniques for robotics. Education: Diplom in Mechanical Engineering (1988) and PhD (1993) from TU Wien; M.Sc. (1990) from Rensselaer Polytechnic Institute. V4R coordinates EU projects like ActIPret, robots@home, HOBBIT, and national initiatives like vision@home. Markus has edited a book on Robust Vision with Gregory Hager and authored 62 peer-reviewed journal articles and over 400 reviewed publications. His recent research explores zero-shot 6D pose estimation, sim-to-real transfer, and transparent object detection. Markus has served as program chair for ICRA 2013 and organized HRI 2017 in Vienna. He has advised numerous students and secured grants from the Austrian Academy of Sciences for work at HelpMate Robotics and Yale's Vision Laboratory. The V4R group leads innovations in robotic vision, including frameworks for synthetic data generation (Unrealgensyn), depth completion (CAGT), and educational robotics applications for sustainability. Their work spans household robotics (RH3), agricultural robotics (EdgeSoil), and human-robot collaboration.
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.
