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Aleksandra Urman serves as a Postdoctoral Researcher at the Social Computing Group within the Department of Informatics, Faculty of Business, Economics and Informatics at the University of Zurich. Her position bridges computational methodologies with social science inquiry to investigate digital political landscapes. Her academic credentials include a PhD in Social Sciences from the University of Bern (2020), a Master's in Political Science from Central European University (Budapest), and a BA in Asian Studies from the Higher School of Economics (Moscow). This interdisciplinary background informs her approach to analyzing online political behavior. Urman's research specializes in computational political communication with emphases on polarization mechanisms, authoritarian regime tactics, far-right group dynamics, and algorithmic bias in search systems. She employs large-scale data analysis to examine how digital platforms shape political discourse, including studies of Telegram far-right communities, cross-national Twitter polarization, and Russian social media dynamics. Her methodology combines web tracking, content analysis, and cross-platform comparison to audit information ecosystems. Recent publications reveal a concentrated focus on algorithm auditing across search engines and social media, particularly examining generative AI's impact on news consumption, visual representation of historical events, and misinformation patterns during elections. Key trends include cross-lingual comparisons of AI guardrails, longitudinal analysis of search result consistency, and cross-national studies of user trust in algorithmic systems. As an active contributor to the University of Zurich's Digital Society Initiative, Urman participates in multiple research communities including DSI Communication, DSI Democracy, and DSI Cybersecurity. Her work involves collaborations across disciplines to address societal challenges in digital governance and platform accountability.

• Computational Social Science
• Political Communication
• Social Media Analysis
• +5 more

Kévin Huguenin is a Full Professor and head of the Information Security and Privacy (ISP) Lab at the University of Lausanne (UNIL), within the Faculty of Business and Economics (HEC). His research focuses on security and privacy in distributed systems, mobile/social networks, and interdisciplinary areas such as health informatics and legal aspects of privacy. He has held academic positions since 2016, including Assistant Professor (2016–2020) and Full Professor (2020–present). He previously worked at LAAS-CNRS and EPFL, with postdoctoral research at McGill University. Education: PhD (Computer Science, Université de Rennes, 2010), MSc (Network and Distributed Systems, University of Nice Sophia Antipolis, 2007), BSc (Computer Science, University of Rennes, 2006). He is an alumnus of École Normale Supérieure de Cachan. Research Interests: Interdependent privacy, wearable device security, genomic privacy, privacy-preserving technologies, and the social/human aspects of cybersecurity. His lab collaborates with institutions like CSEM and EPFL on projects such as PrivacyLife (SNF-funded). Recent Work: Focuses on second-hand storage device privacy, shadow health data, and participatory design for privacy solutions. Recent studies include personality inference from wearables and user behaviors in fitness data sharing. Awards: Best Paper Awards at OPODIS’09 and IEEE ICDCS’10, CNRS Excellence Award, and Best Teacher Award in the Master of Information Systems. Grants & Collaborations: Swiss National Science Foundation (SNF), Fondation Hasler, and industry partnerships like Nokia Research Center. Current projects include second-hand device privacy (SNF-funded) and mHealth privacy. Labs & Teams: ISP Lab at UNIL, collaborating with CSEM and EPFL on interdisciplinary projects. Active in program committees for venues like USENIX Security, PETS, and WEIS.

• Information Security
• Privacy
• Cybersecurity
• +7 more

Patrick Thomas Eugster is a Full Professor of Computer Science at the Università della Svizzera italiana (USI), leading the Software Systems (SWYSTEMS) group within the Computer Systems Institute, which he co-founded. Previously, he held faculty positions at Purdue University (2005-2016) and TU Darmstadt (2014-2017), with a visiting role at MIT (2012/2013). His research focuses on distributed systems, networking, security, and programming languages, with over 160 publications and significant industry collaborations with companies like Amazon, Google, and Facebook. Education: He holds an M.S. (1998) and Ph.D. (2001) in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL). Research Interests: His work addresses distributed systems challenges such as fault-tolerance, security, and efficient resource management. Recent topics include datacenter reliability, quantum network verification, and confidential computing. His team explores intersections between systems, languages, and networks to build robust and secure distributed applications. Publications: Recent work spans topics like failure detection in datacenters, formal verification of systems, and network congestion control. Key venues include USENIX ATC, ACM SIGMETRICS, IEEE Network, and TACAS. His 2025 work on failure detection and TCAM encoding exemplifies contributions to system resilience and hardware optimization. Awards: Jean-Claude Laprie Award (2025), TACAS Best Paper (2025), ERC Consolidator Grant (2014), NSF CAREER Award (2007). Advising & Grants: Supervised over 20 PhD and postdoctoral researchers. Active grants include EU Horizon Europe CloudStars, Swiss National Science Foundation, and industry partnerships with Cisco and SAP. Labs & Teams: Directs the SWYSTEMS group, collaborating on projects like secure cloud analytics, quantum network verification, and datacenter monitoring. Former students hold roles at universities, tech firms, and startups.

• Distributed Systems
• Networks
• Security
• +5 more

Ulrich Ultes-Nitsche is a Professor in the Department of Informatics at the University of Fribourg, where he also serves as Dean of the Faculty of Science and Medicine. His research spans theoretical computer science, formal methods, and cybersecurity, with a strong focus on automata theory, model checking, and secure network systems. Institution: University of Fribourg School: Faculty of Science and Medicine Department: Department of Informatics Role: Professor and Dean His research interests include theoretical computer science, automata theory, formal verification, temporal logic, and cybersecurity. He has made significant contributions to the understanding of Büchi automata, liveness properties, and secure authentication mechanisms using Trusted Platform Modules. His interdisciplinary work extends to secure medical data access and ecological network analysis. The recent publications highlight a clear trend: a deep and sustained focus on automata theory, particularly Büchi automata, with increasing integration of machine learning techniques like graph neural networks for analysis. His earlier work laid foundational contributions in formal verification, model checking under fairness, and secure network protocols, especially in firewall and EAP-TLS authentication. The research consistently bridges theoretical computer science with practical security applications. Carolin Latze InSeon Yoo Dominik Jungo David Buchmann Thierry Nicola Michael Hayoz Christoph Ehret Nayla Sokhn Ulrich Ultes-Nitsche has led and co-organized numerous international workshops (e.g., NCMA, MSVVEIS, VCL) on formal methods and verification, demonstrating a strong commitment to the academic community. His work has been supported by research in formal verification, network security, and trusted computing, often involving collaborations across institutions. He has also contributed to projects involving secure e-commerce, medical data access, and enterprise information systems. He has been a key figure in organizing and editing proceedings for the International Workshop on Modelling, Simulation, Verification and Validation of Enterprise Information Systems (MSVVEIS) and the ACM Sigplan Workshop on Verification and Computational Logic (VCL), fostering research communities in formal methods and verification.

• Theoretical Computer Science
• Automata Theory
• Formal Verification
• +7 more

Colin Porlezza is Associate Professor of Digital Journalism and Director of the Institute of Media and Journalism (IMeG) at the Università della Svizzera italiana (USI), Faculty of Communication, Culture and Society. He also leads the European Journalism Observatory (EJO) and holds an Honorary Senior Research Fellow position at City, University of London. Previously, he was a Research Fellow at Columbia University’s Tow Center for Digital Journalism. PhD in Communication Sciences – Università della Svizzera italiana Licentiate (BA/MA) in Communication Sciences – USI, specialization in Mass Communication and New Media Work experience at University of Zurich and University of Neuchâtel His research centers on digital journalism, with emphasis on automated journalism, artificial intelligence, datafication, disinformation, and journalistic ethics. He investigates how digital technologies reshape journalistic roles, norms, and practices, particularly in public service and hybrid news environments. His work bridges technical innovation with ethical and societal implications. The 15 most recent articles highlight a consistent trajectory in AI and journalism, focusing on automation, accountability, verification tools, and innovation. Keywords span communication, AI, ethics, and media policy, while subfields include algorithmic transparency, hybrid workflows, fact-checking, and value-sensitive design—reflecting a strong interdisciplinary focus on responsible technological integration in newsrooms. Knight News Innovation Fellowship Prof. Porlezza has secured major research grants from the Swiss National Science Foundation, Horizon 2020, Google Digital News Initiative, and OFCOM. He leads the JoIn-DemoS and Diacomet projects and previously directed Designing Hybrid Journalism and DMINR. He advises PhD students as Director of the PhD Program and collaborates with media organizations like SRG SSR and Tamedia. His advisory roles include the Austrian National Journalists' Study and Innovamedia network. He leads the Institute of Media and Journalism (IMeG) and the European Journalism Observatory (EJO), fostering collaborative research across Europe. These units serve as hubs for innovation, policy dialogue, and knowledge transfer between academia and professional journalism.

• Digital Journalism
• Automated Journalism
• Artificial Intelligence in Media
• +7 more

Alessandro Facchini is a Professor at the Department of Innovative Technologies at SUPSI - University of Applied Sciences Western Switzerland, based in Lugano, Switzerland. He holds a PhD in Computer Science (2010) from the University of Lausanne and the University of Bordeaux, with prior research roles at institutions including the University of Warsaw, University of Amsterdam, and University of California, Santa Cruz. His current research focuses on logic, rationality theories, probability, and the philosophy and ethics of AI, complemented by past work in automata theory and game theory. He has received notable awards such as the FNP Homing Plus Grant (2012) and the Paul Bernays Award (2011). Education PhD in Computer Science (2010), co-supervised by Prof. J. Duparc (U. Lausanne) and I. Walukiewicz (U. Bordeaux) Doctoral Program in Logic and Foundations of Mathematics (2004-2006), University of Barcelona Master in Humanities (Logic, Linguistics, Mathematics) (1998-2003), University of Neuchâtel Research Interests : Facchini’s work bridges formal logic, AI ethics, and foundational questions in probability and quantum theory. His recent projects include the European University on AI in Curricula and SmartH2O, a platform leveraging gamification for water resource management. He explores topics like quantum rational preferences, causal models, and the societal implications of AI systems. Awards & Recognition : FNP Homing Plus Grant (2012) Paul Bernays Award (2011) Teaching & Leadership : Facchini leads courses such as “Ethics of Technology and Engineering” and “Fundamentals of Artificial Intelligence,” emphasizing ethical and legal dimensions of data analytics. He also oversees projects like the Smart UniverCity initiative. Collaborations & Labs : Active member of IDSIA (Istituto Dalle Molle di Studi sull’Intelligenza Artificiale), a leading Swiss AI research institute. His work often intersects interdisciplinary teams addressing environmental, healthcare, and ethical challenges posed by AI.

• Logic
• Probability Theory
• AI Ethics
• +4 more

Jacopo Staiano is a Senior Assistant Professor (RTDb) at the Department of Economics & Management, University of Trento (Italy). His academic journey includes previous positions as Head of Research at reciTAL.ai, research affiliate at Data-Pop Alliance, senior data scientist at Fortia Financial Solutions, and post-doctoral researcher at LIP6, UPMC - Sorbonne Universités and Fondazione Bruno Kessler. Staiano received his BSc in Computer Engineering from the University of Pisa (2003), an MA in Sonic Arts from Queen's University of Belfast (2005), and an MSc in Human Language Technologies and Interfaces from the University of Trento (2010). He completed his PhD under Prof. Nicu Sebe at the Department of Information Engineering and Computer Science, University of Trento. His academic visits include the Intelligent Systems Lab at University of Amsterdam, Ambient Intelligence Research Lab at Stanford University, Human Dynamics Lab at MIT Media Lab, and Telefonica I+D. Staiano's research spans multiple domains with a strong focus on Natural Language Processing and Human-Computer Interaction. His work ranges from modeling human behavior when interacting with technology to analyzing social network structures and virality dynamics. His recent publications demonstrate a significant shift toward large language models, with applications in sustainability reporting, medical diagnostics, financial analysis, and bias detection. His work shows sophisticated integration of technical AI capabilities with social science perspectives. Staiano has received several prestigious awards throughout his career, including an Honorable Mention at ACM DIS 2012, Best Paper Award at ACM UbiComp 2014, the UMUAI James Chen Award 2016, and most recently the Ten Year Technical Impact Award from ACM ICMI 2024. These awards reflect the sustained impact and quality of his research across multiple domains. His research has been supported by collaborations with major institutions including MIT Media Lab, Stanford University, and Telefonica I+D, as well as industry partnerships. His work on projects like DepecheMood for emotion analysis and SALSA for multimodal group behavior analysis has established him as a significant contributor to affective computing and social signal processing. Staiano maintains active connections with multiple research communities, particularly in the areas of computational social science, natural language processing, and affective computing. His work bridges technical AI development with real-world applications in finance, healthcare, and social good initiatives.

• Natural Language Processing
• Artificial Intelligence
• Social Network Analysis
• +7 more

Cerstin Mahlow is a Professor of Digital Linguistics and Writing Research at the ZHAW School of Applied Linguistics , where she leads initiatives like the CAS Texten: effektiv schreiben und Generative KI effizient nutzen . Her work bridges linguistic theory with computational methods, focusing on writing process analysis, NLP-based authoring tools, and socio-cultural impacts of digital transformation in education. PhD in Computational Linguistics (University of Zurich, 2011) M.A. in Computational Linguistics, Spanish Linguistics, and Political Science (Erlangen-Nürnberg, 2008) Continuing Education in E-Learning (ETH Zurich/University of Zurich, 2003) Her research explores linguistic modeling of writing processes using digital tools, with a focus on sentence-centric analysis and AI-driven writing support. She investigates how large language models (LLMs) and generative AI reshape academic writing practices, authoring workflows, and literacy requirements. Recent publications highlight trends in writing analytics , including sentence history modeling (2025), feedback revision strategies (2023), and cognitive writing aids (2022). She co-leads projects like Computational Competencies for Non-Tech Students and Potentials of Advanced Text Technologies , emphasizing machine learning applications. Prof. Mahlow serves on the steering committees of the ACM Symposium on Document Engineering and coordinates the SIG Writing special interest group under EARLI. She actively contributes to networks like Girls Can Code Switzerland and the Association for Computational Linguistics .

• Digital Linguistics
• Writing Technology and Document Engineering
• Linguistic Analysis and Modeling of Writing Processes
• +4 more

Mark Cieliebak is a Professor for Speech and Text Processing at the Zurich University of Applied Sciences (ZHAW), School of Engineering, where he leads the Natural Language Processing (NLP) research group at the Centre for Artificial Intelligence. He has held this position since December 2018, following prior roles as a lecturer at ZHAW (2012-2018). His educational background includes a Dr. sc. techn. in Computer Science from ETH Zürich (1999-2003) and a Diplom in Computer Science from Universität Dortmund (1990-1999). His research focuses on Natural Language Processing , Text and Speech Analysis , and Machine Learning applications . Primary domains include dialogue systems evaluation, low-resource speech recognition (particularly Swiss German), automated text generation assessment, and NLP for social media analysis. He also explores educational applications through flipped classroom methodologies and machine learning operations. Cieliebak's publications (2020-2024) demonstrate strong emphasis on NLP evaluation frameworks, speech corpus development for dialects, and generative AI validation. Recurring themes include robustness testing, bias mitigation in automated metrics, and multilingual processing challenges. His work frequently involves large-scale dataset creation and ensemble learning techniques. Scientific Awards: SwissNLP Award 2023 Best Paper Award - Honorable Mention at EMNLP 2020 ZHAW Teaching Award 2015 He leads numerous research projects including: Unified Model for Text Generation Evaluation End-to-End Swiss German Speech Translation Holistic Analysis of Misinformation in Social Networks Automated News Processing (AutoNews) Chatbot Development for Language Learners He co-founded SpinningBytes AG (2015-present) and maintains extensive industry collaborations. As head of the NLP research group, he oversees doctoral candidates and master's students, though specific advisee names aren't listed.

• Natural Language Processing
• Text Analysis
• Speech Processing
• +4 more

Clément Pit-Claudel is a Tenure-Track Assistant Professor at École Polytechnique Fédérale de Lausanne (EPFL), leading the SYSTEMF Laboratory in the School of Computer and Communication Sciences. His work bridges programming languages, formal verification, and systems engineering to build high-assurance software and hardware components. PhD in Computer Science from MIT (2016), thesis on proof-producing compilers MSc in Computer Science from MIT BSc in Computer Science from École Polytechnique (France) Research Interests focus on correct-by-construction program synthesis , domain-specific compilers , and formal verification . He develops tools like Alectryon for interactive Coq proof visualization and Rupicola for verified compiler construction. His work spans hardware description languages (e.g., Kôika ), software verification (e.g., Fiat ), and regex engine formalization (e.g., Elk and Warblre ). Recent publications include foundational work on JavaScript regex mechanisms (ICFP 2024), relational compilation (PLDI 2022), and hardware simulation (ASPLOS 2021). His lab SYSTEMF emphasizes full assurance without compromise through machine-checked proofs and hardware-software co-design. Awards include the MIT Frederick C. Hennie III Teaching Award (2016) and MIT William A. Martin Thesis Award (2016). He has served as program committee member for conferences like PLDI, POPL, and Coq Workshop. Teaching includes Software Construction (400+ students at EPFL) and Interactive Theorem Proving graduate course. He has advised doctoral students in formal methods and compiler design.

• Programming Languages
• Formal Verification
• Compilers
• +5 more

Anja Belz is a Professor at Dublin City University's School of Computing, specializing in Natural Language Processing research. She leads the Natural Language Processing Research Group and has established herself as a leading expert in human evaluation methodologies, reproducibility in NLP, and data-to-text generation systems. Her work bridges theoretical research and practical applications with significant contributions to medical text generation and evaluation standards. Her research interests center on creating robust evaluation frameworks for NLP systems, with particular focus on human evaluation methodologies, reproducibility assessment, and quality criteria standardization. She has pioneered work on the Human Evaluation Data Sheet (HEDS) and the QCET (Quality Criteria for Evaluation Taxonomy), addressing critical gaps in evaluation comparability across NLP research. Her work on reproducibility spans multiple shared tasks (ReproNLP, ReproGen) that have become benchmarks in the field, examining how different experimental conditions affect evaluation outcomes. Analysis of her recent publications reveals a clear research trajectory focused on making NLP evaluation more rigorous, transparent, and comparable. Her work increasingly incorporates large language models while maintaining critical scrutiny of their evaluation methodologies. She has made significant contributions to understanding when LLM-based evaluation correlates with human judgments, and has developed frameworks for assessing the reproducibility of NLP evaluation results in quantified terms. Professor Belz has organized numerous workshops and shared tasks focused on human evaluation and reproducibility in NLP, including multiple ReproNLP shared tasks that have attracted international participation. Her research has been consistently published in top-tier NLP conferences including ACL, EMNLP, and INLG, with a strong emphasis on methodological rigor and practical applicability to real-world NLP evaluation challenges. She has also contributed significantly to NLP research in under-resourced languages, particularly Irish, Welsh, Breton, and Maltese. Her work on medical text generation has practical implications for healthcare applications, particularly in automating clinical documentation and systematic reviews. She has developed methods for biomedical synthesis generation that could significantly reduce the time and cost of keeping medical practitioners updated with research. Her research on consultation checklists aims to standardize the human evaluation of medical note generation systems, addressing critical challenges in clinical safety and quality assessment.

• Natural Language Processing
• Human Evaluation
• Reproducibility
• +4 more

Prof. Dr. Mascha Kurpicz-Briki is a computer science professor at the Bern University of Applied Sciences, leading the Applied Machine Intelligence research group within the Institute for Data Applications and Security (IDAS). Her work focuses on human-centered applications of natural language processing in mental health and societal challenges, particularly addressing bias mitigation in AI systems. Education: PhD in energy-efficient cloud computing from University of Neuchâtel Expertise: Applied NLP, fairness in AI, augmented intelligence for health Leadership: Deputy lead of Applied Machine Intelligence Research Group Her research emphasizes augmented intelligence - creating AI systems that support rather than replace humans. Current projects investigate NLP applications for: Burnout and depression detection in clinical psychology Fairness measurement in word embeddings and language models Human augmentation through AI in industrial and healthcare settings Recent publications highlight her contributions to: Bias detection frameworks for European languages Machine learning in eating disorder diagnostics Generative AI integration in art therapy She maintains active memberships in IEEE, ACM, ACL, and the Swiss Center for Augmented Intelligence, with expertise in German, English, and French language technologies.

• Applied Natural Language Processing
• Fairness and Diversity in AI
• Augmented Intelligence for Mental Health
• +2 more

Heinz Riener is a Researcher at the Integrated Systems Laboratory (LSI) within the School of Computer and Communication Sciences (IC) at EPFL, Lausanne, Switzerland. He holds a Ph.D. (Dr.-Ing.) in Computer Science from the University of Bremen, Germany. Previously, he worked at the German Aerospace Center (DLR) and the University of Bremen's Reliable Embedded Systems group. His research focuses on logic synthesis , formal methods , and computer-aided verification of hardware and software systems. Key areas include quantum computing (e.g., AQFP circuits), nanotechnology (e.g., RFET-based circuits), and emerging technologies like adiabatic quantum-flux parametron systems. Developed open-source tools like mockturtle and easy for logic synthesis and ESOP forms. Principal Investigator on projects like the Open Logic Synthesis Libraries initiative. Active in program committees for conferences like DAC, DATE, and FDL. Collaborates with institutions such as TU Graz, TU Hamburg, and UC Berkeley. His work emphasizes reproducibility and open-source collaboration in logic synthesis, contributing to benchmarks and libraries widely used in academia and industry.

• Logic Synthesis
• Formal Methods
• Computer-Aided Verification
• +4 more

Dr. Si Liu is a researcher at ETH Zürich's Institut für Informationssicherheit, specializing in distributed systems and database verification. His research focuses on developing formal methods to ensure consistency and isolation guarantees in database transactions, DNS security, and neural network verification. His work bridges theoretical computer science with practical system design, creating tools like Plume for black-box isolation checking and techniques for compositional DNS attack analysis. Recent projects include NOC-NOC for optimal distributed transactions and abstraction-based DNN verification. Dr. Liu has contributed significantly to protocol design for internet architectures and database concurrency models, with publications spanning top conferences including EuroSys, OSDI, and USENIX Security.

• Database Systems
• Distributed Systems
• Formal Verification
• +3 more

Sascha Zuber is a Research and Teaching Fellow (Assistant Professor) at the Center for the Interdisciplinary Study of Gerontology and Vulnerability (CIGEV), Faculty of Psychology and Educational Sciences, University of Geneva. He leads the research group Variability and Plasticity in Lifespan Development (V+Life) and is an associate member of the Institute on Aging & Lifelong Health at the University of Victoria. He is affiliated with the Swiss Center of Expertise in Life Course Research LIVES and serves on the editorial boards of Swiss Psychology Open and Cognitive Development . His research focuses on prospective memory, executive functions, and cognitive development across the lifespan . He investigates how cognitive abilities evolve from childhood to old age, with a strong emphasis on individual differences, plasticity, and interventions. His work integrates experimental, longitudinal, and naturalistic approaches to understand cognitive aging, memory monitoring, and the impact of psychological and social factors on cognitive health. The recent publications highlight a strong trend in longitudinal cognitive aging, online cognitive assessment tools (e.g., Geneva Space Cruiser, eCOGTEL), and methodological innovations in life course research . His work frequently appears in top journals such as Journal of Memory and Language , Psychology and Aging , and Memory , reflecting a cohesive program on the cognitive architecture of intention maintenance and memory variability. LIVES Young Scholar grant (2024) for 'Creating a Prospective Memory Longitudinal Data Catalog (ProMLoD)' LIVES Young Scholar grant (2024) for 'Expanding the Geneva Spacer Cruiser' Swiss National Science Foundation (SNSF) Postdoctoral Fellowship (2021–2023) Vontobel Award for Research on Age(ing) (2016) Dr. Zuber has been involved in advising and collaborative research, particularly within the CIGEV and LIVES networks. He has contributed to large-scale integrative projects on life course risk and health, often in collaboration with international teams. His work is supported by competitive grants focused on open science and longitudinal data infrastructure. He leads the V+Life research group, which develops and validates online cognitive tools and investigates variability in cognitive development. The group promotes open science by providing free access to neuropsychological test batteries such as the Geneva Space Cruiser and COGTEL, supporting reproducibility and collaborative research.

• Developmental Psychology
• Cognitive Aging
• Prospective Memory
• +9 more