Frank Leymann is a Professor of Computer Science at the University of Stuttgart, where he serves as Director and Founder of the Institute of Architecture of Application Systems. His career spans academia and industry, including 20 years at IBM Germany as a Software Architect. Research Focus: Workflow Management, Service Computing, Cloud Computing, Quantum Computing, Pattern Languages, Digital Humanities. Standards: Co-author of BPEL, BPMN, WS-RF, TOSCA, Human Task specifications. His work on quantum computing emphasizes hybrid quantum-classical applications and practical integration challenges. He pioneered the OASIS cloud standard TOSCA and developed the open-source OpenTOSCA platform, which has over 1,000 downloads. Scientific awards include an Honorary Doctorate from the University of Crete (2015), IBM Distinguished Engineer (2000), and IBM Academy of Technology membership (1996). Google Scholar cites his work over 43,300 times (H-Index 89), ranking him among the world's top computer scientists.
Elisabeth André is a Full Professor of Computer Science and Chair of Multimedia Concepts and Applications at University of Augsburg, where she has been faculty since 2001. She previously served as Managing Director of the Institute for Computer Science at Augsburg University from 2004 to 2006. Professor André has received multiple prestigious professorship offers, including W3-Professorships in Human-Computer Interaction and Cognitive Systems from University of Stuttgart and Human-Machine Interaction from Otto-Friedrich-Universität Bamberg in 2009. Her academic journey began with a Diploma in Computer Science (1988) and Dr. rer. Nat. (1995) from Saarland University. Before joining Augsburg, she spent over a decade as a Scientific Researcher at DFKI GmbH (German Research Center for Artificial Intelligence), where she rose to Principal Researcher and was appointed a DFKI Research Fellow. Professor André's research focuses on designing and evaluating interactive multimodal user interfaces, experimental learning environments with animated characters, and affective computing. She is internationally recognized as a pioneer in embodied conversational agents, having organized one of the first international workshops on the topic in 1997. Her work stands out for its empirical foundation, including extensive corpus studies of human behaviors to inform virtual agent behavior modeling. Notably, she has conducted significant cross-cultural research with Japanese partners to develop culture-specific behaviors in virtual agents. Her publication record shows a consistent trajectory of innovation in human-computer interaction, with particular emphasis on multimodal analysis, gaze behavior simulation, and emotion recognition systems. The research trends in her recent work demonstrate increasing sophistication in input recognition methods and the development of practical toolboxes (AuBT, EmoVoice, SSI) that have been adopted by research institutions worldwide. 2007 Alcatel-Lucent Fellowship at Universität Stuttgart Best Paper Finalist at International Conference on Intelligent Virtual Agents (2007-2009) 2005 Convivio Best Demo Award 2000 Best Paper Award at International Conference on Intelligent User Interfaces 1998 RoboCup Scientific Award Multiple student projects winning international awards including GALA Awards and TEI conference awards Professor André has supervised 2 completed dissertations and is currently guiding 11 PhD students and 1 Habilitation candidate. Her leadership extends to major research projects including EU-funded initiatives (METABO, E-Circus, IRIS, DynaLearn, CALLAS) and DFG projects (CUBE-G, OC-Trust). She serves on numerous editorial boards and has held significant organizational roles in major conferences including IUI, IVA, and CASA. Her laboratory has developed multiple software toolkits that are used internationally in large-scale research projects, demonstrating the practical impact of her work. Current research directions include advanced emotion recognition systems, culture-adaptive virtual agents, and applications of her technology to educational and healthcare domains.
Lina Theresa Schmid is a Lecturer at the Institute of Political Science, University of Vienna, within the Faculty of Social Sciences. Her research focuses on International Political Economy, Political Theory, Latin America, and Social Movements. She holds a BA and MA and is actively involved in academic service roles within the Institute. Research Interests : Schmid’s work explores the intersections of political economy, theoretical frameworks in political science, and regional studies with a focus on Latin America. Her work on social movements integrates structural analysis with case studies, emphasizing transnational dynamics and policy implications. Methodologically, she combines qualitative approaches with comparative frameworks. Publications Trends : Her recent publications (2012–2025) emphasize language pedagogy in translation and interpreting (TI) education, machine translation integration, and curriculum design. Key themes include skill development (e.g., mediation competence), technological impacts (LLM-driven tools), and cross-linguistic analysis (e.g., modal verbs). Affiliations & Service : She contributes to administrative roles at the Institute of Political Science, including research administration and public relations. No awards or grants are explicitly listed in the provided texts. Labs/Teams : No specific labs or collaborative teams are mentioned in her profile. Her work appears to be individual and institutionally focused.
Dr. Elsje van Bergen is an Associate Professor at Vrije Universiteit Amsterdam's Department of Biological Psychology and a Visiting Professor at the University of Oslo (2024-25 academic year). She leads an interdisciplinary research team investigating why neurodevelopmental conditions and educational outcomes run in families, bridging genetics, psychology, psychiatry, education, and public health through the Netherlands Twin Register. Her academic background includes: PhD in Child Development and Education from University of Amsterdam (2013) Postdoctoral Fellowship at University of Oxford (2012-2015) Bachelor's and Master's in Human Movement Sciences from VU Amsterdam ( cum laude ) Van Bergen's research disentangles genetic and environmental influences on learning differences across language, reading, and mathematics, with focus on dyslexia, dyscalculia, ADHD, and autism. Her work examines how these conditions relate to mental health and educational outcomes through twin studies, polygenic scores, and large cohorts like Norway's MoBa study. Her recent publications reveal dominant genetic influences in educational inequality and neurodevelopmental condition comorbidity. Methodologically innovative works leverage polygenic scores to resolve cultural transmission pathways, while meta-analyses quantify parent-offspring resemblance in reading. These studies, published in Nature Human Behaviour and Psychological Science , demonstrate interdisciplinary approaches to gene-environment interplay. Major recognitions include: ERC Starting Grant (2023) NWO VIDI Talent Grant (2021) Jacobs Foundation Research Fellowship (2020) NWO Rubicon (2012) and VENI (2016) Talent Grants Early-career awards from Society for Scientific Study of Reading, Association for Psychological Science, and Federation of Associations in Behavioral & Brain Sciences Fellow of Young Academy of Europe (2019) She mentors Master's and PhD students while securing major grants to investigate intergenerational educational cycles. Her ERC-funded project examines how parental genotypes influence offspring education through dynastic social processes. She co-leads Amsterdam Young Academy initiatives supporting early-career researchers and interdisciplinary collaboration. Based in VU Amsterdam's Department of Biological Psychology, she collaborates with LEARN! and Amsterdam Public Health research institutes. Her Oslo-based work with CREATE and PROMENTA centres leverages Norwegian registry data to study education-mental health intergenerational transmission across 114,000 families.
Paul Primus is a researcher at the Institute of Computational Perception, Johannes Kepler University Linz, specializing in audio processing and machine learning. His work focuses on sound event detection, acoustic scene classification, and language-based audio retrieval, with significant contributions to the DCASE (Detection and Classification of Acoustic Scenes and Events) challenges. Education: Dr. (PhD) MSc BSc Research Interests: Primus's research bridges audio signal processing and deep learning, addressing real-world challenges in machine listening. His work emphasizes device invariance, data efficiency, and transformer architectures for audio analysis. Key contributions include knowledge distillation for audio retrieval, multi-stage transformer training, and novel approaches to language-audio interaction. He actively explores low-complexity solutions suitable for embedded systems and edge deployment. Publication Trends: Primus's recent work (2023-2025) shows a clear trajectory toward multimodal audio-language systems, leveraging transformers and pretraining techniques. His publications increasingly focus on data efficiency, device generalization, and practical deployment constraints, as evidenced by his DCASE challenge submissions. The integration of metadata and cross-modal alignment represents a growing research emphasis. Activities: Adversarial Robustness in Data Augmentation (2020) Exploiting Parallel Audio Recordings to Enforce Device Invariance in CNN-based Acoustic Scene Classification (2019) Labs and Teams: Primus is a core member of the Institute of Computational Perception at JKU, which leads research in computational audio analysis. The institute maintains strong participation in international challenges like DCASE and collaborates extensively on audio transformer development and language-audio interaction systems.
Alan Said is an Associate Professor in the Department of Applied IT at the University of Gothenburg, where he also serves as Head of Education. His research focuses on recommender systems, user modeling, personalization, and the human-centered evaluation of AI technologies. He is actively engaged in promoting responsible, fair, and sustainable AI through interdisciplinary research and community leadership. Research Interests: User Modeling and Personalization Recommender Systems (RecSys) Human-Computer Interaction (HCI) and Human-Centered AI (HCAI) Explainable and Responsible AI Green AI and Environmental Impact of Recommender Systems Reproducibility and Evaluation Methodologies His recent publications reflect a strong trend toward ethical, sustainable, and socially conscious AI, with a focus on fairness in healthcare, environmental cost measurement, and interdisciplinary approaches to recommendation. He contributes extensively to top-tier venues such as ACM RecSys and UMAP. Scientific Awards: ACM Distinguished Speaker Advising and Grants: Alan Said advises students on topics ranging from fairness in AI to human-centered explanations and sustainable recommender systems. He has been involved in organizing workshops and special issues that promote critical reflection and interdisciplinary collaboration in the RecSys community. He has participated in funded research projects, including international collaborations supported by agencies like Vinnova. Labs and Teams: He is a key organizer of the Human-centered AI (HCAI) podcast and has co-organized influential workshops such as BEYOND and INTROSPECTIVES at RecSys, fostering dialogue on the societal and ethical dimensions of AI. His work bridges computer science, psychology, design, and ethics, emphasizing collaboration across disciplines.
Anna Weichselbraun is a researcher in the Faculty of History and Cultural Studies at the University of Vienna , specializing in the Institute for European Ethnology . Her work bridges political and legal anthropology , linguistic anthropology , and Science and Technology Studies (STS) , focusing on global technology governance through projects like nuclear regulation and cryptocurrency. Education : PhD in Sociocultural and Linguistic Anthropology (University of Chicago, 2016), Postdoctoral Research (Stanford University, 2016-2018), MA and BA in Interdisciplinary Anthropology, Sociology, and Gender/Media Studies (EHESS/ENS and NYU). Research : Explores knowledge practices in institutions like the IAEA, blockchain verification , and language ideologies in AI regulation . Her book manuscript on the IAEA is under review at Cornell University Press. Her recent work examines Large Language Models (LLMs) through language ideologies, funded by an ERC Consolidator Grant submission. She has held fellowships at Stanford and the Berggruen Institute, with field research in Vienna, SF Bay Area, and UN headquarters. Scientific Awards : ERC Consolidator Grant (submitted) Nuclear Security Postdoctoral Fellowship, Stanford University USC-Berggruen Fellowship Anna actively engages in public discourse via Bluesky, advocating against far-right policies in Austria and critiquing technocratic governance. Her publications appear in Cultural Anthropology , PoLAR , and Signs and Society .
Yuxi Xia is a researcher affiliated with the Faculty of Computer Science, specializing in data mining and machine learning. Current research activities focus on artificial intelligence validation, surrogate modeling for railway systems, and multimodal question-answering frameworks. BSc, MSc in Computer Science Active in AI Review publications (2024) Research interests span large language model calibration , digital twin technologies , and model ensembling . Recent articles address overfitting, multimodal fusion, and ethical implications of machine-generated text detection. Key publication trends include industrial AI applications for railway systems, federated learning security, and explainability in black-box models. Collaborations extend to interdisciplinary AI validation studies.
Janusz Kacprzyk is a Full Professor at the Systems Research Institute, Polish Academy of Sciences (1970–present, full-time). He concurrently holds part-time professorships at WIT – Warsaw School of Applied Information Technology and Management (since 1998), the Industrial Institute of Automation and Measurements (PIAP) (since 2007), and the Department of Electrical and Computer Engineering, Cracow University of Technology (since 2010). He is an IEEE Fellow (since 2006) and IFSA Fellow (since 1997), a Full Member of the Polish Academy of Sciences (since 2010), and Foreign Member of the Bulgarian Academy of Sciences (since 2013) and the Spanish Royal Academy of Economic and Financial Sciences (since 2007). Education M.Sc. in Automatic Control and Computer Science, Warsaw University of Technology, Poland Ph.D. in Systems Analysis, 1977 D.Sc. in Computer Science, 1991 Research Interests Professor Kacprzyk’s research exploits modern computational and artificial intelligence techniques—especially fuzzy logic—to address uncertainty, imprecision, and human-centric reasoning in systems. Core themes include: Multivalued and fuzzy logic for uncertainty modelling Natural-language-based system representation and reasoning Data mining and linguistic summarisation of large data sets for decision support Flexible database querying with imprecise or bipolar user preferences Computational models for group decision making, social choice, voting, and consensus reaching Multistage optimal fuzzy control via dynamic programming These strands converge on real-world applications in ICT, mobile robotics, business analytics, and finance. Scientific Awards & Distinctions 2014 WAC Lifetime Achievement Award in Soft Computing 2013 IFSA Award for Outstanding Academic Contributions and Lifetime Achievement 2010 Medal of the Polish Neural Network Society 2007 IEEE CIS Silicon Valley Chapter Pioneer Award 2006 IEEE CIS Fuzzy Systems Pioneer Award 2006 Kaufmann Award and Gold Medal (SIGEF & FEGI) 2000 AutoSoft Journal Lifetime Achievement Award Fellow, IEEE (2006–) Fellow, IFSA (1997–) Foreign Member, Bulgarian Academy of Sciences (2013–) Full Member, Polish Academy of Sciences (2010–) Foreign Member, Spanish Royal Academy of Economic and Financial Sciences (2007–) Leadership & Service President, Polish Operational and Systems Research Society (PTBOiS), since 2007 Past President, International Fuzzy Systems Association (IFSA), 2009–2011 Member, Administrative Committee (AdCom), IEEE Computational Intelligence Society, since 2010 Member, Award and Fuzzy Pioneer Committee, IEEE CIS, since 2010 Distinguished Lecturer, IEEE Computational Intelligence Society, 2010–2013 He has held visiting appointments in the USA, Italy, UK, Mexico, and China, and serves as Editor-in-Chief of six Springer book series and two journals, while sitting on the editorial boards of approximately 40 further journals.
Barbara Nußbaumer-Streit is Professor for Methods Research in Evidence Synthesis at the University for Continuing Education Krems, where she serves as Head of Centre Cochrane Austria and Co-Director of JBI-Austria - the Austrian Centre for Evidence-Based Healthcare. She coordinates the international Cochrane Rapid Reviews Methods Group and leads multiple research projects including the EU-funded MEDIATE project (2024-2027). Her research focuses on methodological aspects of evidence synthesis, particularly rapid review methodology, systematic review production efficiency, and knowledge translation. She has published extensively on rapid review methods, stakeholder engagement in evidence synthesis, and the application of evidence in healthcare decision-making. Her work bridges methodological research with practical implementation in healthcare settings. Nußbaumer-Streit's recent publications demonstrate a strong focus on improving evidence synthesis methods, with particular attention to rapid reviews, the use of technology in systematic review production, and knowledge user involvement. Her research spans diverse healthcare topics while maintaining a consistent methodological focus on how evidence is synthesized and used. She actively contributes to methodological guidance development through her coordination of the Cochrane Rapid Reviews Methods Group and has published multiple papers in the Rapid Reviews Methods Series in BMJ Evidence-Based Medicine. Nußbaumer-Streit regularly presents at international conferences on evidence synthesis methodology and teaches on systematic review methods. Her current projects include EU-funded work on evidence synthesis for public health and multiple studies focused on improving the efficiency and quality of rapid reviews.
Ignacio David Lopez Miguel is a PreDoc Researcher at the Cyber-Physical Systems department of Vienna University of Technology (TU Wien). His research focuses on formal verification techniques for safety-critical systems, particularly in the context of Programmable Logic Controllers (PLCs) used in industrial and high-stakes environments like CERN's Large Hadron Collider (LHC) cooling systems. Current projects include TAIGER (2023–2027), addressing neural network verification for PLC code. Collaborates with institutions such as CERN, GSI, and NASA on safety-critical control systems. Research Themes : Integration of formal verification with AI/ML components Runtime enforcement in cyber-physical systems Ethical considerations in engineering design Automated translation of natural language requirements to formal specifications His work spans interdisciplinary domains, connecting computer science, control theory, and engineering ethics through rigorous verification methodologies.
Sascha Hunold is an Associate Professor at TU Wien, affiliated with the Department of Parallel Computing within the Faculty of Informatics. He holds roles as Vice Dean of Academic Affairs for Informatics Bachelor programs and Curriculum Coordinator for the Master's program in High-Performance Computing. His research focuses on parallel computing, MPI optimization, scheduling algorithms, and reproducible HPC experiments. Education: Habilitation (venia docendi) in Computer Science from TU Wien, PhD in Computer Science from the University of Bayreuth, and MSc in Computer Science from Martin Luther University Halle-Wittenberg. Research interests include MPI collective communication performance, HPC benchmarking, algorithm selection, and task scheduling. He has contributed to tools like ReproMPI and Scheduling.jl. Key awards include Best Paper awards at IEEE CLUSTER 2020 and EuroMPI/Asia 2014, and recognition for reproducible research methodologies. His work emphasizes practical applications of parallel computing in large-scale systems. Teaching responsibilities include courses on parallel algorithms, scientific programming with Python, and HPC project supervision. Active in program committees for major conferences like IPDPS and SC.
Henderik Proper is a Full Professor of Business Informatics at TU Wien's Faculty of Informatics, leading the Research Unit in Business Informatics. He holds roles as Head of Research Unit, Faculty Council Substitute Member, and Curriculum Commission Principal Member. His expertise spans enterprise architecture, digital transformation, and conceptual modeling. Education: Holds a PhD and has held academic positions at TU Wien and previously at the University of Nijmegen. Research focuses on enterprise modeling, AI-driven systems, and governance frameworks. He leads projects like INTEND (2024–2026) and MFP 4.2 (2022–2023), emphasizing digital twin integration and low-code applications. Publications: Over 50 peer-reviewed articles in top venues like Springer and IEEE, focusing on enterprise engineering, process mining, and AI applications. His work bridges theory and practice, addressing challenges in digital transformation and model-driven architectures. Grants: Active in EU-funded projects (INTEND) and national initiatives (MFP 4.2). Advises on doctoral theses and teaches courses like 'Enterprise & Process Engineering' and 'Ontology-Driven Conceptual Modeling'. Labs/Teams: Leads research groups on enterprise architecture and digital systems within TU Wien's Informatics department, collaborating internationally on standards like ArchiMate extensions.
Manuela Waldner is an Associate Professor in the Department of Computer Graphics at Technische Universität Wien (TU Wien). Her research focuses on visual data exploration, human-computer interaction, and immersive analytics. She leads projects like 'Visual Analytics and Computer Vision meet Cultural Heritage' (FWF doc.funds.connect) and 'Joint Human-Machine Data Exploration' (FWF). She teaches courses including 'Computer Graphics', 'Information Visualization', and 'Visual Research Methods'. Awards include the Best Paper Award at EuroVA 2024. Her work spans medical visualization, VR navigation, and bias analysis in AI models. She advises numerous PhD and Master's students, contributing to 43+ publications.
Tova Milo is a Full Professor and Head of the Department of Computer Science at Tel Aviv University, where she has held academic roles since 1995. She specializes in database systems, XML, data integration, and crowd-sourcing. Her research bridges theoretical foundations and practical applications in data management. Education: Ph.D. in Computer Science from Hebrew University (1992). She has led major initiatives such as the ERC Advanced Investigators grant (MoDaS project) and holds ACM Fellow status. She chairs key committees like the ACM SIGACT-SIGMOD PODS executive committee and has organized over 50 international conference programs. Research interests focus on database management, XML, data-centric business processes, and leveraging crowd-sourcing for data tasks. Her work has been recognized with the ACM PODS Test-of-Time Award (2010) and an IBM Faculty Award (2008). Grants and funding include over 20 awards from the European Union, US-Israel Binational Science Foundation, and industry partners like IBM and Microsoft. She contributes to editorial boards of ACM Transactions on Database Systems and The VLDB Journal.
