Ian Horrocks is a Professor of Computer Science at the University of Oxford and a Fellow of Oriel College. His research focuses on knowledge representation, description logics, automated reasoning, and semantic web technologies. He has held academic positions at the University of Manchester (2003–2007) and served as Chief Scientist at Cerebra Inc. (2001–2006). Horrocks earned his BSc (1st class), MSc, and PhD in Computer Science from the University of Manchester (1981–1997). His work includes foundational contributions to ontology languages (e.g., OWL) and reasoning systems such as HermiT and ELK. He has supervised over twenty doctoral students and postdoctoral researchers. His honors include Fellowships from the Royal Society (2011), ECCAI (2009), and the British Computer Society (2005). He serves as Editor-in-Chief of the Transactions on Graph Data and Knowledge and leads initiatives in semantic web standards and knowledge graph applications. Key Roles: Editor-in-Chief (Journal of Web Semantics), Co-Chair (W3C OWL Working Group) Grants: EPSRC Senior Research Fellowship (2005), numerous international collaborations Labs: Oxford Semantic Technologies, involvement in projects like RDFox and PAGOdA
Joseph Sifakis is a CNRS Research Director and founder of Verimag Laboratory in Grenoble, France. He holds the INRIA-Schneider endowed industrial chair since 2008 and has been instrumental in advancing concurrent systems specification and verification. Education: Electrical Engineering (Technical University of Athens), Computer Science (University of Grenoble) Research interests focus on component-based design , real-time systems , and correct-by-construction techniques . He pioneered the development of the BIP framework and contributed to model checking, a cornerstone of industrial system verification. Recent publications emphasize component-based modeling, formal verification, and distributed system design, reflecting his work's impact on embedded systems and critical applications like aerospace and telecommunications. Scientific awards include: Turing Award (2007) CNRS Silver Medal (2001) Test-of-Time Award (2012) Multiple honorary doctorates (2008-2011) Member of prestigious academies Industry collaborations span Airbus, ST Microelectronics, and the European Space Agency, with applications in aeronautics, telecommunications, and industrial software standards. He leads the ARTIST2 Network of Excellence and directs the CARNOT Institute 'Intelligent Software and Systems'.
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.
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.
Victor Vianu is a Professor of Computer Science and Engineering at the University of California, San Diego and holds the INRIA International Chair at INRIA-Saclay in Paris. He has maintained continuous faculty status at UC San Diego since 1983 while developing extensive international collaborations, particularly with French research institutions including INRIA, ENST-Paris, ENS-Paris, and the University of Paris. His academic credentials include a Ph.D. in Computer Science from the University of Southern California (1983) and undergraduate studies in Mathematics and Informatics at the University of Bucharest (1974-1977). Professor Vianu's research spans computational logic, database systems and theory, and automatic verification. His work uniquely bridges theoretical foundations with practical applications in XML processing, workflow systems, and data-driven applications. He has made seminal contributions to understanding the theoretical underpinnings of database query languages and their expressive power, particularly in the context of XML technologies and workflow systems. His research demonstrates a consistent trajectory from theoretical computer science to practical database systems applications. His publication record reveals significant contributions to database theory spanning over three decades, with particular emphasis on XML technologies, workflow systems, and formal methods for data-driven applications. His work shows a clear evolution from foundational theoretical work to practical applications in business processes and web technologies. INRIA International Chair (2013) Fellow of the American Association for the Advancement of Science (AAAS) (2013) ACM PODS Alberto O. Mendelzon Test-of-Time Award (2010) Fellow of the Association for Computing Machinery (ACM) (2006) Professor Vianu has held significant leadership roles including Editor-in-Chief of the prestigious Journal of the ACM, numerous program committee chair positions for major database conferences (PODS, ICDT, ASIAN), and General Chair for ACM SIGMOD conferences. He has served on the executive committees of SIGMOD (1998-2000) and PODS (1993-2004), and was a member of the ICDT Council (1997-2007), demonstrating sustained influence in the theoretical database community. His extensive invited talks at major conferences including College de France, ACM PODS, and International Conference on Database Theory highlight his international recognition.
Giovanni De Micheli is a Professor of Electrical Engineering and Computer Science at EPF Lausanne, Switzerland. He also serves as Director of the Integrated Systems Centre and the Institute of Electrical Engineering at EPFL, and chairs the Scientific Committee of CSEM in Neuchatel. Previously, he held academic roles at Stanford University for 18 years, including Full Professor, Associate Professor, and Assistant Professor in the Department of Electrical Engineering. His research spans synthesis of digital circuits, hardware/software co-design, low-power design, and Networks on Chip (NoC) technology. 2003: IEEE Emanuel Piore Award 2000: Golden Jubilee Medal of the IEEE CAS Society 2000: ACM Fellow 1994: IEEE Fellow 1990: IEEE/CS Distinguished Service Award 1988: NSF Presidential Young Investigator Award His seminal contributions include pioneering C-based synthesis and Boolean matching algorithms for digital circuits, foundational work in dynamic power management using stochastic control, and the development of Network-on-Chip (NoC) technology. His publications, such as "Networks on Chips: A New SoC Paradigm" and "Dynamic Power Management for Portable Systems" , have shaped modern SoC design practices. With over 400 technical articles, 9 books, and an H-index of 56, his work remains highly influential.
Sylvain Lefebvre is a permanent researcher at INRIA (Institut National de Recherche en Informatique et en Automatique) in France, where he leads the MFX research team since 2018. Previously, he was part of the ALICE group at INRIA Nancy (2009-2018) and the REVES team in Sophia Antipolis (2006-2009). His career includes a postdoctoral position at Microsoft Research Seattle (2005) following his PhD at INRIA Rhones-Alpes under Fabrice Neyret. His educational background includes a PhD in Computer Graphics from Université Joseph Fourier (Grenoble) in 2005, preceded by a Master in Computer Graphics from INP Grenoble in 2001. His habilitation thesis focused on Runtime Texture Synthesis. Lefebvre's research centers on simplifying content creation for highly detailed patterns, structures, and shapes with applications spanning Computer Graphics to additive manufacturing. He develops fast, controllable by-example synthesis approaches that generate content while enforcing user-specified constraints. His work addresses computational challenges through novel data structures and algorithms optimized for GPUs and FPGAs, including his Silice programming language. The ERC-funded ShapeForge project (2012-2017) advanced shape generation for 3D printing, leading to the IceSL software for digital modeling and fabrication. Analysis of his 15 most recent publications reveals a strong focus on additive manufacturing optimization, with recurring themes in structural integrity, material efficiency, and geometric algorithms. His work bridges computer graphics theory with practical fabrication constraints, particularly in microstructure design, slicing techniques, and mechanical metamaterials. The interdisciplinary nature spans computer science, materials engineering, and robotics. EUROGRAPHICS Young Researcher Award (2010) ERC Starting Grant for ShapeForge project (2012) Lefebvre has advised over 25 PhD students and interns including Marco Freire, Thibault Tricard, and Jimmy Etienne. His ShapeForge project received significant ERC funding, supporting research in computational fabrication. He serves on numerous program committees including SIGGRAPH, Eurographics, and SIGGRAPH Asia, reflecting his leadership in the computer graphics community. As leader of the MFX team since 2018, Lefebvre directs research in computational fabrication, focusing on IceSL software development for 3D printing workflows. The team integrates computer graphics techniques with manufacturing constraints, developing tools that simplify complex object design and fabrication while addressing real-world challenges in material usage and structural integrity.
Georg Langs is a Full Professor of Machine Learning in Medical Imaging at the Medical University of Vienna and Founding Director of the Computational Imaging Research Lab (CIR). He leads a 25-member interdisciplinary team focusing on machine learning methodologies for medical image analysis. Key roles include Director of the Joint Initiative on AI in Medical Imaging (European Institute of Biomedical Imaging Research) and Scientific Lead of the Respiratory Disease Phenotype Observatory (ZODIAC, UNO/IAEA). He is affiliated with MIT’s CSAIL and serves on advisory boards for global AI initiatives. Education: PhD in Computer Science, Graz University of Technology (2007) M.Sc. in Mathematics, Vienna University of Technology (2003) Research Interests: Machine learning-driven precision imaging, neuroimaging, clinical data phenotyping, and cross-species brain connectivity analysis. His work bridges imaging biomarkers with biological mechanisms and large-scale clinical data integration. Grants & Funding: Over €6M in competitive grants as Principal Investigator in the last two years. Projects include ARTEMIS (fatty liver disease digital twins) and AI-POD (personalized risk scores via imaging). Awards: 2022 IS3R Emerging Leaders Club 2022 National Academy of Medicine Emerging Leader Programme 2018 Advisor, AI Mission Austria 2030 Lab & Teams: CIR Lab focuses on AI-driven medical imaging solutions. Co-founded contextflow GmbH , a MedUni spin-off developing AI software for imaging analysis.
Edgar Weippl is a Professor at the Faculty of Computer Science, University of Vienna, where he serves as Vice Dean and Head of the Research Group Security and Privacy. His work spans cybersecurity, blockchain, and machine learning, with teaching roles in information security and software security courses. Current Positions: Vice Dean (Faculty of Computer Science), Head (Security and Privacy Research Group), Deputy Head (Neuroinformatics & Knowledge Engineering Groups) Research Interests: Cybersecurity, blockchain, IoT security, code obfuscation, privacy technologies, reinforcement learning, and socio-technical systems security Selected Publications: Focus on blockchain privacy, VoWiFi security, code obfuscation, and reinforcement learning applications
Univ.-Prof. Martin Pinzger is a Professor at the Department of Informatics Systems, Alpen-Adria-Universität Klagenfurt. He serves as Head of Department and Member of the Senate, actively contributing to academic governance. Research Focus: Automating Software Engineering Tasks, Mining Software Repositories, Program Analysis, Software Evolution and Visualization Recent Work: Developing tools for API evolution analysis, cybersecurity AI (CAI), robotics benchmarking (RobotPerf), and dependency validation His research combines empirical studies with tool development for software maintenance and security. Current projects address challenges in REST API breaking changes, cloud security certifications, and robotic system performance evaluation. Publications since 2023 demonstrate continued engagement with topics spanning AI-driven code segmentation, microservice API evolution, and cybersecurity tool development. Key trends include cross-disciplinary applications of NLP to software engineering and security-focused tool creation. Contact: martin.pinzger@aau.at
Maximilian Schreieck is an Associate Professor for Information Systems at the Department of Information Systems, Production and Logistics Management, University of Innsbruck. He earned his PhD at Technical University of Munich (2020) and completed habilitation at University of Innsbruck (2025). Previously a DFG Walter Benjamin Fellow at Wharton School (2021-2022). Education: PhD in Information Systems, Technical University of Munich (2020) Habilitation in Information Systems, University of Innsbruck (2025) His research focuses on digital platform ecosystems, platform governance, digital platforms for social causes, and digital transformation of established companies. He has published extensively in top journals like MIS Quarterly, Information Systems Journal, and Electronic Markets. Recent publications address generative AI ecosystems, EU digital regulation impacts, cloud platform adoption, and multi-platform strategies. His work combines technical platform analysis with organizational and regulatory implications. Scientific awards include: Best Paper Award, AIS SIG Grounded Theory Methodology (2021) Paper of the Year Award, AIS SIG Electronic Markets (2020) His research has practical applications in automotive, banking, and refugee integration platforms, with collaborations at SAP, BMW, and EU policy contexts. Teaching activities include master's theses supervision and courses on digital platform management.
Martin Bicher is a PostDoc Researcher at TU Wien, affiliated with the Department of Data Science under the Faculty of Informatics. He specializes in agent-based simulation, epidemiological modeling, and decision support systems for public health crises. His work focuses on optimizing resource allocation, vaccination strategies, and policy evaluation during pandemics. He teaches courses such as Modeling and Simulation (194.076), Modelling and Simulation in Health Technology Assessment (194.094), and Advanced Modeling and Simulation (194.056). His research is supported by projects like DynOptTestControl (2022–2026) and KLIPHA-COVID19 (2020–2021). Key research interests include agent-based modeling frameworks, integration of machine learning into simulation systems, and multi-criteria decision support for public health interventions. His publications analyze pandemic response strategies, vaccination prioritization, and the impact of environmental factors on disease spread. Recent work includes developing mathematical models for equitable disease testing, simulating vaccination strategies under supply uncertainties, and evaluating contact-tracing policies. He collaborates with interdisciplinary teams to address challenges in healthcare resource optimization and policy design. Advising two students, Bicher has mentored theses on railway simulation and delay modeling. His contributions to pandemic decision support have been featured in high-impact journals like Omega and PLoS ONE.
Theresa Scharl-Hirsch is a Senior Scientist and Deputy Scientific Director at the Core Facility Bioinformatics, University of Natural Resources and Life Sciences, Vienna (BOKU). She holds concurrent appointments at the Institute of Statistics, BOKU, and has extensive experience in bioprocess modeling, machine learning, and statistical computing. Her work bridges biochemical engineering with advanced data science methodologies. Her research focuses on real-time monitoring of biopharmaceutical processes, clustering of high-dimensional data (particularly RNA sequencing), and application of explainable machine learning techniques. She has developed statistical models for process optimization and quality prediction in antibody capture and protein purification, with a strong emphasis on industrial implementations using R programming. Key trends in her publications include three-way data analysis, matrix-variate Gaussian mixture models, and permutation-based variable importance methods for deep learning architectures. Her work spans bioprocess engineering, bioinformatics, and industrial data science applications.
Dr. Franz-Karl Skala is a Senior Lecturer at the Vienna University of Economics and Business (WU) in the Business Education department, with over 15 years of academic and professional experience in higher education. He has held teaching and research positions at institutions including the University of Graz, University of Applied Sciences Burgenland, and Fachhochschule Wiener Neustadt. Current Senior Lecturer at WU (since 2012) Teaching focus on programming didactics and e-learning Specializes in business informatics didactics and vocational training Research interests center on curriculum development for hybrid education models, digital transformation in business training, and vocational education reform. His recent FLUENT project (2022-2025) develops flexible universal education models for AI-era learning. He has secured multiple Erasmus+ grants for international education initiatives in Central Asia. Scientific awards include four Vienna University of Economics and Business Innovative Teaching Awards (2020, 2019, 2017, 2010), University of Graz teaching excellence recognition (2020), AK Science Prize (2013), and Leopold-Kunschak Science Prize (2013). Developed modular curriculum frameworks Created e-learning platforms for entrepreneurs Conducted comparative studies on vocational vs academic degrees
Rudolf Ramler is an External Lecturer at TU Wien's Faculty of Informatics, Department of Information Systems Engineering. He specializes in software testing methodologies, automated testing frameworks, and software quality assurance. His research focuses on improving testing practices for legacy systems, industrial automation software, and defect prediction in software projects. He teaches the Software Testing course (VU 188.280) in 2025S. His work spans empirical investigations, tool-supported testing, and systematic literature reviews. Ramler has contributed to projects like CDL-SQI (2018–2024), exploring practical approaches for testing industrial automation systems. Research interests include test code readability, automated testing strategies, and value-driven testing frameworks. His publications address challenges in retrofitting tests for legacy code, comparing manual and automated testing efficacy, and developing context-specific defect prediction models. He has collaborated with industry partners to apply academic research to real-world software engineering problems.
