Paolo Tonella is a Full Professor and Director of the Software Institute at the Faculty of Informatics, Università della Svizzera italiana (USI) in Lugano, Switzerland. He also holds an Honorary Professorship at University College London (UK) and previously led the Software Engineering group at Fondazione Bruno Kessler (Italy). His research focuses on software testing, analysis, and AI-driven systems. He has authored over 200 peer-reviewed papers and 100 journal articles, with an H-index of 72. He teaches courses in Data and Software Engineering and Informatics, including Information Modeling, Probability & Statistics, and Knowledge Search. Key contributions include foundational work on web application testing (ICSE MIP award), evolutionary testing techniques (eToc/EvoSuite tools), and reverse engineering of object-oriented systems. He led the ERC-funded PRECRIME project on anticipatory testing. His recent work addresses AI dependability, autonomous systems testing, and deep learning fault analysis. Scientific awards include the ICSE MIP Award (2001) and ERC Advanced Grant (2018). He has served on editorial boards for major journals like IEEE Transactions on Software Engineering and ACM TOSEM. Current roles include leadership in the Software Institute and organizing the SIESTA summer school.
David Basin is a Full Professor at the Department of Computer Science, ETH Zurich, and heads the Information Security Group. He has held academic positions since 2003, including roles at the University of Freiburg (1997–2002) and the Max-Planck-Institut für Informatik (1992–1997). His research focuses on Information Security, including methods and tools for secure systems, formal verification, and cryptographic protocols. He is Editor-in-Chief of the ACM Transactions on Privacy and Security and Springer's Information Security and Cryptography book series. Basin founded the Zurich Information Security Center (ZISC) in 2003 and led it until 2011. Education: B.Sc. in Mathematics (Reed College, 1984), Ph.D. (Cornell University, 1989), and Habilitation (University of Saarbrücken, 1996). Research interests span formal methods for security protocol verification, privacy-preserving systems, and cryptographic implementations. He has contributed to foundational work on security protocols, including the Tamarin verification framework. His work addresses real-world systems like payment protocols (EMV), DNS security, and database isolation guarantees. Awards: ACM Fellow (2018) for contributions to Information Security and Formal Methods, IEEE Fellow. He has organized numerous conferences, including IEEE S&P, Euro S&P, and ACM CCS. Labs/Teams: Leads the Information Security Group at ETH Zurich and co-founded Anapaya Systems, a startup focused on network security solutions. His team develops tools like VeriMon (formally verified monitoring) and Tamarin for protocol analysis.
Mathias Payer is an Associate Professor at EPFL's School of Computer and Communication Sciences (IC), leading the HexHive Laboratory . His work focuses on software security, particularly addressing memory corruption and type violations through binary analysis and compiler-based techniques. He contributes to research in secure system design, fault isolation, and fuzzing methodologies. Current PhD students : Di Bartolomeo Luca, Feng Zhiyao, Hofhammer Florian, Lyu Tao, Mao Philipp Yuxiang, Zhang Chibin, Zheng Han Past EPFL PhD students: Badoux Nicolas Daniel, Bhattacharyya Atri, Hazimeh Ahmad His research explores software security in areas like: Protecting applications from vulnerabilities Binary exploitation and mitigation Compiler-driven security hardening Strong sanitization and privilege separation Memory corruption detection The HexHive group develops tools and frameworks for: Automated fuzz driver generation Gradual compartmentalization State inference for feedback optimization Secure cell architectures Recent publications highlight advancements in: Fuzzing hybrid approaches (e.g., DUMPLING, MendelFuzz) Memory safety validation (QMSan, Pacmem) Compiler-assisted defenses (Gradient, Type++)
Reinhard Heckel is a Tenured Associate Professor (equivalent to Professor) of Machine Learning at the Department of Computer Engineering, Technical University of Munich (TUM), and Adjunct Faculty in Electrical and Computer Engineering at Rice University. He was previously an Assistant Professor at Rice (2017–2019), a postdoc in the Berkeley Artificial Intelligence Research (BAIR) Lab at UC Berkeley, and a researcher at IBM Research Zurich. Education: PhD, 2014 – ETH Zurich Visiting PhD student – Department of Statistics, Stanford University Research Interests: His work centers on machine learning and information processing with three major thrusts: (1) developing algorithms and theoretical foundations for deep learning, especially for accelerated magnetic resonance imaging ; (2) establishing rigorous mathematical and empirical underpinnings for modern machine-learning systems; and (3) leveraging DNA as a digital information-storage medium , including error-correction coding and system design for DNA-based storage. Across more than 100 peer-reviewed papers since 2017, Heckel’s research exhibits a strong interdisciplinary blend of computational imaging , machine-learning theory , and molecular data storage . Recent 2024–2025 publications show intensive focus on robust MRI reconstruction using diffusion priors, evaluation of bias in large web-text corpora, and state-of-the-art error-correcting codes for DNA storage channels. A forthcoming book, Deep Learning for Computational Imaging (Oxford University Press), consolidates his contributions to the field. Outreach & Media: Keynote and panel talks at DLD, TUM, and major ML conferences Op-eds in Frankfurter Allgemeine on ChatGPT and DNA storage Science features on Netflix, BBC, and German television (Galileo, “Gut zu Wissen”) Research Environment: At TUM he leads a group investigating theoretical and applied aspects of deep learning, compressed sensing, and coding for DNA storage. Open-source repositories on GitHub (e.g., dna_data_storage , supplement_deep_decoder ) provide code and data supplements accompanying his publications.
Prof. Oliver Faude is a Professor and Researcher at the Department of Motor Performance & Biomechanics within the University of Basel's Department of Sport, Exercise and Health (DSBG). His research focuses on exercise physiology, sports medicine, and the application of physical activity in managing chronic conditions like type 2 diabetes. He supervises doctoral students, including Vivien Hohberg, whose work on telephone-based health coaching for diabetes patients was published in the Journal of Science and Medicine in Sport. Faude collaborates on projects such as the dbcoach intervention, funded by Innosuisse and health insurers, demonstrating how personalized coaching increases physical activity in diabetic populations. His work also extends to musculoskeletal imaging innovations, such as the UMUD web application for ultrasonography data access, and the PrepAir study addressing chemotherapy-induced sensory dysfunction in children. Faude's interdisciplinary approach integrates clinical research, biomechanics, and public health, with a particular emphasis on aging populations and pediatric oncology. He contributes to injury prevention strategies in sports like badminton and soccer, while advancing methodologies for muscle volume assessment via 3D ultrasound and MRI comparisons. Key Projects: dbcoach program, PrepAir study, musculoskeletal imaging tools, agility training for frailty prevention. Grants: Innosuisse, SwissLife Foundation, Voluntary Academic Society of Basel. Students: Vivien Hohberg (PhD). Labs/Teams: Motor Performance & Biomechanics lab, collaborations with Prof. Bart Roelands (Vrije Universiteit Brussel) on overtraining syndrome research.
Jinhan Kim is a Postdoctoral Researcher at the Università della Svizzera italiana (USI) in the Faculty of Informatics, working in the TAU lab under Prof. Paolo Tonella. He earned his Ph.D. from KAIST under Prof. Shin Yoo, focusing on software engineering research in mutation testing, fault localization, and deep learning system testing. His work bridges traditional software engineering techniques with AI-driven methodologies, emphasizing AI4SE and SE4AI paradigms. Education: Ph.D. in Software Engineering, KAIST, 2023 Research Interests: Mutation Testing Deep Learning System Testing Autonomous Systems Testing Adversarial Attack Detection Empirical Software Engineering Service and Leadership: Organized SBFT 2026 and DeepTest 2026 (co-located with ICSE 2026) Program Committee Member for ASE, ISSTA, Mutation, and DeMeSSAI Board of Distinguished Reviewers for TOSEM (2024–2025) Labs and Teams: Active contributor to the TAU Lab at USI, focusing on advanced software testing and AI integration.
Dr. Hongwei Wang is a Senior Researcher at Tencent AI Lab Seattle , specializing in applied machine learning for Natural Language Processing and Interconnected Systems . His work bridges Knowledge Graphs , Recommender Systems , and Graph Neural Networks , with a focus on large language models and retrieval-augmented generation. Ph.D. (2018), B.E. (2014) in Computer Science from Shanghai Jiao Tong University Postdoctoral Researcher : Stanford University (2019-2021), University of Illinois Urbana-Champaign (2021-2022) Dr. Wang’s research explores integrating Knowledge Graphs with Graph Neural Networks to enhance recommendation systems, language models, and information retrieval. His work spans Retrieval-Augmented Generation , Representation Learning , and GAN-based Graph Modeling , with recent papers on State-Space Exploration for LLM agents and Semantic Watermarking . His 15 most recent publications (2022-2024) focus on Retrieval Granularity , Interactive Memory , and Agent Systems , with keywords spanning Computer Science , Machine Learning , and Knowledge Graphs . Trends highlight advancements in Token-Level Semantic Matching , Schema-Guided Event Prediction , and Multi-Document Summarization . Scientific Awards: 2020 CCF Outstanding Doctoral Dissertation Award 2018 Google Ph.D. Fellowship Dr. Wang contributes to open-source projects like DKN and RippleNet , with 11 repositories on GitHub. He actively engages in Knowledge Graph Conferences (KDD, WWW, AAAI) and studies Chinese Classical Poetry and Film Arts .
Adrian Perrig is a Full Professor at the Department of Computer Science at ETH Zürich. He leads research in network security, distributed systems, and internet architecture, focusing on projects like the SCION secure internet architecture and its commercialization through Anapaya Systems. His work emphasizes secure communication, denial-of-service defense, and public key infrastructure (PKI) innovations. Affiliations: ETH Zürich, Institute for Information Security Key Contributions: SCION, SAGE, RHINE, F-PKI Research interests include path-aware networks, cryptographic protocols, and resilient systems. His publications span over 295 results since 2005, with notable awards including the Best Paper Award (CoNEXT 2021) and ANRP 2023. He has contributed to foundational work in secure routing, DNS security, and GPU attestation. Scientific awards include Best Paper Awards at CoNEXT and ACM SIGCOMM, as well as recognition for applied networking research. His work bridges academia and industry, addressing challenges in global network security and scalability.
Reza Etemad is a Professor at EHL Hospitality Business School (part of HES-SO), specializing in marketing and hospitality technology. His research focuses on human-robot interaction, healthcare technologies in elderly care, and the application of technology in service delivery. He has led multiple projects funded by HES-SO and private partners, including studies on service robots' ethical implications, connected health technologies for seniors, and virtual agents in B2B/B2C contexts. Notable achievements include extending the Technology Acceptance Model (TAM) to healthcare and robotic service contexts, analyzing cultural impacts on online shopping risks, and investigating customer perceptions of revenue management practices in restaurants. He has published widely in journals such as International Journal of Hospitality Management and International Journal of Social Robotics , with a focus on bridging technological advancements and human-centric service solutions. Education: BSc in Hospitality from EHL. Key Projects (2010-2021): Led projects totaling over 298,600 CHF, including studies on robot ethics, smart home healthcare, and virtual agent impacts on B2B platforms. Awards: None explicitly listed, though his impactful research has driven industry-relevant insights. Labs/Teams: Collaborates with researchers like Justine Gentinetta and Valentina Clergue on robotics and healthcare tech. Partnerships include Touchmind for B2B digital solutions. Future Work: Expanding studies on AI ethics in service robots, sustainable healthcare technologies, and post-pandemic digital education strategies. His work emphasizes balancing technological innovation with ethical considerations, particularly in preserving human interaction's role in healthcare and hospitality sectors.
Simon Ruffieux is a Senior Researcher and Lecturer at the Department of Computer Science, University of Fribourg, and a member of the Human-IST Institute. He currently leads the HIP-Initiative (Human-IST x SwissPost Initiative) and coordinates academic projects related to Swiss Post. His academic roles include Lecturer and Senior Assistant , reflecting his active engagement in teaching and research. His research focuses on leveraging advanced technologies to support individuals, particularly those with special needs. Key areas include: Machine Learning and Data Science for urban systems (e.g., bike-sharing optimization) Human-Computer Interaction (HCI), especially gesture recognition and multimodal interfaces Augmented and Virtual Reality applications in rehabilitation and assistance Development of smart glasses for visually impaired users Physiological signal analysis for workload classification The 15 most recent publications reveal a strong trend in applying AI and data science to real-world challenges, particularly in assistive technologies and urban mobility. His work often involves interdisciplinary collaboration, integrating computer science with psychology, rehabilitation, and industrial applications. There is a consistent emphasis on user-centered design and real-world usability. Simon Ruffieux has not been mentioned as receiving specific scientific awards in the provided text. He has advised or collaborated with several researchers, including Nicolas Spycher, Samuel Torche, and Nicolas Ruffieux, on projects related to forecasting, AR, and gesture recognition. While no formal grant details are listed, his leadership of the HIP-Initiative suggests involvement in externally funded academic projects. His work is closely tied to the Human-IST Institute, where he contributes to interdisciplinary research in human-centered computing. He is actively involved in research teams focused on assistive technologies, gesture interaction, and data-driven urban solutions. The Human-IST Institute serves as the primary hub for his collaborative efforts, particularly through the HIP-Initiative with Swiss Post.
Katarzyna Wac is a researcher at the University of Geneva affiliated with the Faculty of Economics and Management and the Information Science Institute . Her work bridges Digital Health , Mobile Computing , and Human-Computer Interaction , focusing on leveraging wearable devices, smartphones, and AI for health and quality of life (QoL) quantification. Research Themes: Digital biomarkers for Alzheimer's and migraines, QoL assessment via ubiquitous computing, peer- and self-reported behavioral data, and QoE of mobile applications. Labs: Leads the mQoL Lab , a platform for interactive, mobile, and wearable-based studies. Her recent publications explore Transformer models for health data analysis, social robots in homecare, and ethical frameworks for digital mental health. She has contributed to standards for proxy-reported QoL measures and personalized drug delivery systems in digital health. The multimodal integration of emotional signals and context-aware QoS/QoE provisioning for m-health services are recurring technical themes. Key collaborations include the MobiHealth project and COPD24 , translating future internet technologies into telemonitoring solutions. Her work spans from foundational studies on mobile cognition to applied ambulatory assessment of affect and health risks.
Jürgen Sauer is a Full Professor at the University of Fribourg , affiliated with the Department of Psychology under the Faculty of Letters and Human Sciences . With over 120 publications, his research focuses on Human-Machine Interaction , Usability Testing , User Experience (UX) , and Automation Design , particularly in high-stakes environments like X-ray baggage screening and spaceflight simulations . Email: juergen.sauer@unifr.ch Phone: +41 26 300 7622 Address: RM 01 bu. C-1.117, Rue PA de Faucigny 2, 1700 Fribourg Orcid: 0000-0003-2105-1694 His research projects, funded by the Swiss National Science Foundation (FNS), include: Improving work design for airport security officers (2019-2024): Developed pictorial scales for measuring psychological constructs in security environments. Social stress and support in hybrid teams (2018-2023): Investigated machine-induced social stressors and mitigation through social support. Automation in visual inspection tasks (2014-2018): Examined adaptable automation for baggage screening and system reliability effects. Usability testing effectiveness (2012-2016): Analyzed cultural background impacts and non-usability product features influencing test outcomes. Key contributions include the Luggage Inspection Simulation (LIS) environment for modeling work environments and the development of pictorial usability scales for multilingual applicability. His work bridges ergonomics , human factors , and applied psychology , with notable collaborations with researchers like Adrian Schwaninger and Andreas Sonderegger . His recent publications (2025-2014) analyze: Human-machine performance under false alarms and miscues Social stressor dynamics in hybrid teams Usability scale animation effects Phubbing behavior in professional contexts Accessible website design for non-disabled users
Marc Torrens Arnal is an Associate Professor in the Department of Operations, Innovation and Data Sciences at ESADE Business School, Ramon Llull University. He serves as Academic Director of the Executive Master in Business Analytics and is an active researcher at ESADE D3 – Institute for Data-Driven Decisions. Education: PhD in Artificial Intelligence, École Polytechnique Fédérale de Lausanne (EPFL) Computer Science Engineering, Universitat Politècnica de Catalunya (UPC) Marc's research centers on the application of Artificial Intelligence to solve real-world business and societal challenges. He is particularly passionate about leveraging AI to enhance human decision-making, improve lives, and bridge the gap between academic research and industrial implementation. His work spans machine learning, recommender systems, data-driven marketing, cybersecurity, and ethical AI. He emphasizes practical, impactful innovation grounded in scientific rigor. The most recent articles reflect a strong trend toward applying AI in business analytics, financial technology, and cybersecurity. There is a consistent focus on personalization, decision support, and ethical considerations. His publications span top venues in AI and human-computer interaction, demonstrating a long-standing contribution to both foundational and applied research. Scientific Awards: No awards explicitly mentioned in the text. Marc has advised numerous industry leaders through his entrepreneurial ventures and academic roles. He co-founded Strands, Inc., where he led innovation for over 14 years, building a globally recognized fintech platform. Though no formal students are listed, his leadership in executive education suggests significant mentorship of professionals and entrepreneurs. He has secured substantial real-world impact through patents and commercial deployment rather than traditional research grants. Labs and Research Teams: ESADE D3 - Institute for Data-Driven Decisions
Krisztian Balog is a Professor of Computer Science at the University of Stavanger and a Staff Research Scientist at Google DeepMind. His work focuses on advancing AI-driven information retrieval, natural language processing, and machine learning for user-centric systems. Key affiliations include co-organizing the Sim4IA 2025 Workshop at SIGIR, leading tutorials on user simulation in generative AI, and directing the NorwAI research center’s PhD project on LLMs for recommendations. Research Interests: User simulation, conversational AI, transparency in recommender systems, and simulation frameworks like SimIIR 3 . Scientific Recognition: Recipient of the Karen Spärck Jones Award (2018) and Best Resource Paper Award at CIKM’23 . Leadership: Serves on program committees for SIGIR, WSDM, WWW, and ECIR. Co-organized workshops and tutorials at SIGIR, AAAI, and WWW. Recent Publications highlight advancements in user simulation methodologies, generative AI applications, and open web infrastructure (e.g., SimIIR 3 , OpenWebSearch.eu ). His work bridges theoretical models (e.g., Markov Decision Processes) with practical toolkits for synthetic data generation and system evaluation.
Gianvito Laera is a Postdoctoral Research Fellow at the University of Geneva's Department of Psychology within the Faculty of Psychology and Educational Sciences. He works in the Cognitive Aging Lab, focusing on prospective memory research with particular emphasis on time-based memory processes across the lifespan. His research integrates cognitive psychology, neuroscience, and gerontology to understand how people remember to perform future intentions. Dr. Laera received his PhD in Psychology from the University of Geneva (2018-2023), following a Master of Science in Neuroscience and Neuropsychological Rehabilitation from the University of Padua, Italy (2013-2016), and a Bachelor of Science in Psychological Sciences and Techniques from the University of Bari 'Aldo Moro', Italy (2010-2013). Prior to his doctoral studies, he worked as a Research Assistant at Keele University's Neuropsychology Lab (2016-2018) and completed a research internship at the University of Padua (2015-2016). His research primarily investigates prospective memory—particularly time-based prospective memory—which involves remembering to perform intended actions at specific future times. His work examines age-related differences in these processes, neural correlates using EEG methodology, strategic monitoring behaviors, and the impact of various contextual factors on memory performance. He employs both laboratory and web-based experimental approaches to study how people monitor time, check clocks, and manage cognitive resources when executing delayed intentions. His research has important implications for understanding cognitive aging and developing interventions to support memory in older adults. Analysis of his publication record reveals consistent focus on time-based prospective memory mechanisms across 15 recent publications. His work demonstrates sophisticated methodological approaches including meta-analyses, experimental manipulations of clock-speed, EEG measurements, and longitudinal assessments. Key trends include examining the cost of monitoring behavior, strategic clock-checking patterns, neural correlates of memory retrieval, and the relationship between personality factors and cognitive performance in aging populations. While no specific scientific awards are documented in the available information, his research has been published in high-impact journals across psychology, neuroscience, and gerontology, reflecting recognition within his field. As a postdoctoral researcher, Dr. Laera continues to develop his independent research program while collaborating with senior researchers in the Cognitive Aging Lab. His work bridges experimental cognitive psychology with real-world applications for understanding memory changes in aging populations.
