Dr. Francisco Queiroz is a Lecturer in Digital Innovation Design at the School of Design, University of Leeds. He holds a PhD in Design from the Pontifical Catholic University of Rio de Janeiro, Brazil, and has academic qualifications in Digital Games Design (MA) and Advertising (BA). His research focuses on scientific software usability, immersive technologies, and gamification applied to citizen science and civic engagement. Key research interests include: Scientific software user experience (UX) Color psychology in digital environments Design for cognitive performance enhancement VR applications in education and design Gameful interfaces for scientific practice Recent work explores color's impact on cognitive tasks in virtual reality, digital material design for education, and bridging gaps between academia and industry through game-based methodologies. His editorial role with the Information Design Journal (2020–2022) reflects his commitment to advancing design communication standards. Teaching focuses on creative campaign development and digital innovation in advertising, integrating emerging technologies like AR/VR into design pedagogy.
Armando Fox is a Professor in the Department of Electrical Engineering and Computer Sciences at UC Berkeley, where he co-leads the ASPIRE Lab and directs the Berkeley MOOCLab. His work focuses on integrating online learning research into educational frameworks. He holds a PhD, MS and BS from Berkeley, Illinois, and MIT respectively. Fox's research spans applied statistical machine learning, Software as a Service (SaaS), cloud computing, parallel programming, and innovative online education methods. He pioneered Berkeley's first MOOC on software engineering and co-authored the textbook Engineering Software as a Service . His recent publications demonstrate strong focus on: AI-enhanced education tools and assessment systems Cloud-based learning management architectures Generative AI for collaborative programming education Automated testing frameworks for computer science Significant awards include: NSF CAREER Award ACM Distinguished Member Scientific American 50 top researcher recognition Fox previously contributed to Intel Pentium Pro microprocessor design and founded a mobile computing company based on his dissertation research.
Maurizio Morisio is a Full Professor at the Department of Control and Computer Science (DAUIN), Polytechnic University of Turin, where he is also a member of the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. He has held numerous leadership roles in national and international research projects and academic events. University: Polytechnic University of Turin Department: Department of Control and Computer Science (DAUIN) Research Affiliation: SmartData@PoliTO, SOFTENG Research Group Email: maurizio.morisio@polito.it His research interests include software engineering, mobile and web application testing, energy efficiency of software, machine learning, data science, and green software. He has led significant research in empirical software engineering, gamification of testing, and user-centric service platforms. The recent publications highlight a strong focus on GUI testing , gamification in education and testing , and software process improvement . These works reflect interdisciplinary integration of software engineering with human factors, education, and AI. Scientific Awards and Editorial Roles: Editor-in-Chief of IEEE SOFTWARE since 2008 Program Chair of major conferences including ICSR, ESEM, and GREENS workshops Advising and Grants: He has advised multiple PhD students, including Anna Arnaudo and Simone Leonardi. He has served as the Scientific Manager or Director on over 20 research projects funded by EU, national, regional, and commercial sources, including FP6, Clean Sky, FIRB, and industrial contracts in data science, AI, and software engineering. Research Groups and Labs: He is a key member of the SOFTENG - Software Engineering Group (DAUIN) and contributes to the SmartData@PoliTO center, focusing on data-intensive systems and AI applications in software engineering.
Marika Apostolova Trpkovska is an Associate Professor at the Faculty of Contemporary Sciences and Technologies, South East European University (Tetovo, Macedonia). Her academic work spans cybersecurity, blockchain technology, and educational technology with a focus on Industrial IoT security, semantic web applications, and digital learning systems. PhD in Computer Science (Specialty: e-Medical Services based on Semantic Web) MSc in Software Development and Applications BSc in Computer Sciences Her research covers cybersecurity frameworks for Industrial IoT, blockchain applications in public administration, and educational technology innovations including VR/AR integration and gamification. She has published extensively in international conferences and journals on these topics, with recent works focusing on machine learning-enhanced security protocols and decentralized real estate management systems. Current publications (2023-2024) highlight her expertise in IIoT security standards, smart contract development using Ethereum/IPFS, and cybersecurity threat modeling. Earlier works examine e-learning systems implementation, gender disparities in CS research, and real-time operating system validation. She serves as part-time academic staff member while maintaining technical roles in learning management system administration (LIBRI, ANGEL) and teaching responsibilities across software engineering, algorithms, and programming disciplines.
Dr. Markus Borg is a Senior Researcher and Adjunct Lecturer at Lund University, Sweden, specializing in the intersection of software engineering and applied artificial intelligence. He is a Principal Researcher at CodeScene and contributes to editorial boards for Empirical Software Engineering and IEEE Software . His work bridges academic research with industrial practice through collaborations with Ericsson and contributions to open-source tools like SMIRK. Markus's research focuses on empirical software engineering , technical debt , safety engineering , and requirements engineering for AI-integrated systems. He explores two key directions: AI4SE (applying machine learning to software engineering challenges like defect management and technical debt remediation) and SE4AI (ensuring quality assurance for ML components in safety-critical domains such as automotive systems). His work aligns with regulatory frameworks like the EU AI Act and industry standards for automotive safety. 2025 Contributions : Gamify Track: Two papers on gamification in software maintainability ICSE Journal-First: Longitudinal study on automated bug assignment at Ericsson IDE Track: Trust calibration in AI-assisted refactoring TechDebt Technical Papers: ACE tool for LLM-based technical debt remediation 2024 Contributions : PROFES: AI Act compliance in requirements engineering MO2RE: Code quality specifications TechDebt: Maintainable code ROI analysis Programming with AI: CodeScene platform demonstration 2023 Contributions : CAIN: ML testing in automotive perception systems EASE: Code ownership and defect resolution Mutation Track: Safety-critical mutation testing validation His recent publications emphasize automated defect management , LLM-driven refactoring , and safety validation for ML components , particularly in automotive contexts. Tools like SMIRK and ACE demonstrate practical applications of his research. Markus actively participates in program committees for ICSE, TechDebt, and ICSME, with a focus on bridging academic research with industrial AI/SE challenges.
Francisco Javier Oliver Bernal is a Lecturer at the University of Deusto in Bilbao, Spain, within the Faculty of Education and Sport and the Department of Physical Activity and Sports Sciences. He teaches across Computer Engineering, Physical Activity and Sports Sciences, and Primary Education bachelor's programs, as well as the Master's in Secondary Education. He earned his Doctor of Medicine and Surgery from the University of the Basque Country. His research spans Human-Computer Interaction, Educational Technology, and Science Education, with a strong emphasis on accessibility for visually impaired users. He has developed tools for e-learning, digital resource centers, and innovative teaching methodologies in computer science and natural sciences, aiming to enhance educational experiences through technology. His scholarly output, spanning from the 1990s to 2023, demonstrates a consistent focus on technology-enhanced learning, evolving from early work in 3D interfaces and computer graphics to recent applications in health, music, and interdisciplinary educational contexts. Key trends include the integration of accessibility features, the development of domain-specific educational tools (e.g., for biology and astronomy), and responses to contemporary challenges like the COVID-19 pandemic. He has supervised multiple theses on digital accessibility and cooperative systems, though student names were not listed. Details on research grants were not provided in the available text. As a member of the eVida research group (officially recognized by the Basque Government), he contributes to projects advancing accessible educational technologies, including the ACCE project for audiovisual accessibility and READIS digital resource centers for visually impaired users.
FH-Prof. Dr. Kerstin Blumenstein is a Professor in the Department of Media and Digital Technologies at the University of Applied Sciences St. Pölten. She has been with the institution since 2019, leading research in Interaction Design, User Experience, and Information Visualization. Her work focuses on multi-device ecologies, mobile computing, and digital media integration in cultural and educational contexts. Education includes a Bachelor's in Media Technology (2010) and a Master's in Digital Media Technologies (2012), both from St. Pölten University of Applied Sciences. Prior roles include student assistant at the Institute of Media Informatics and work as a Media Designer in Germany. Research projects like MEETeUX and Seekoi explore user-centered design for multi-device systems and context-aware mobile applications. Key interests span Human-Computer Interaction, second-screen applications, and visualization frameworks for real-time data. Publications emphasize cross-platform visualization tools, mobile interface design, and empirical evaluations of information displays. Current work addresses challenges in BYOD environments and cultural heritage digitalization through projects like KuKoNö . No scientific awards explicitly listed. Active in teaching across multiple programs including Media Technology (BA), Digital Healthcare (MA), and Interactive Technologies (MA).
Akos Ledeczi is a Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. His research focuses on computer science education and wireless sensor networks (WSN) , with notable contributions to visual programming tools like NetsBlox and anti-poaching systems like WIPER. He holds a Ph.D. from Vanderbilt University and a Diploma from the Technical University of Budapest. His education initiatives include the NetsBlox platform for K-12 STEM education and a popular Coursera MOOC on introductory programming. In WSN, his team developed a countersniper system with real-time shooter localization and a wearable system for military applications. He is also a leader in Model Integrated Computing , creating tools like the Web-based Generic Modeling Environment. Recent work includes NSF-funded projects on cybersecurity education in middle schools and animal-borne acoustic monitoring. His awards include the ACM SenSys Test of Time Award (2014) and the Best Showpiece Award at IEEE VL/HCC (2021). Key grants and collaborations span NSF projects, Vodafone innovation programs, and the Cyber Makerspace initiative. His lab develops tools like DeepForge and RoboScape Online , emphasizing open-source and collaborative platforms. Students supervised include Devin Jean (K-12 tools), Gordon Stein (robotics simulations), and Brian Broll (NetsBlox extensions).
Swapneel Sheth is a Practice Associate Professor in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science, where he also serves as Director of the CIS Master's Program. His academic journey includes a B.E. in Computer Engineering from Sardar Patel College of Engineering (Mumbai University) and M.S./Ph.D. degrees in Computer Science from Columbia University. Dr. Sheth's research focuses on: Innovative pedagogical approaches in computer science education Software engineering methodologies and testing frameworks Privacy requirements across cultural contexts Social recommender systems and knowledge sharing platforms Societal impacts of computational tradeoffs His publications demonstrate consistent contributions to SIGCSE, ICSE, and other premier venues, with thematic emphasis on gameful learning strategies, project-based curricula, and cross-cultural privacy frameworks. Awards recognizing his contributions include: Ruth and Joel Spira Distinguished Teaching Award (2023) Hatfield Award for Teaching Excellence (2019) SIGCSE Exemplary Paper (2017) Paul Charles Michelman Service Award (2013) He has advised over 120 graduate and undergraduate researchers on projects spanning educational technology, sustainability tools, healthcare applications, and financial systems. His leadership extends to multiple departmental committees including curriculum development and diversity initiatives.
Pieter Van Gorp is an Associate Professor at the School of Industrial Engineering at Eindhoven University of Technology (TU/e). He holds a part-time appointment at Utrecht University of Applied Sciences, focusing on societal applications of connected health games. His work spans digital health tools, personal health data economics, and cloud infrastructure for reproducible research. Education Background: Obtained PhD in Software Engineering from University of Antwerp, followed by a postdoc there. He has served as program manager for TU/e's Data Science Center (DSC/e) and Eindhoven AI Systems Institute (EAISI), linking research to societal challenges. Since 2023, he is Scientific Director of the Clinical Informatics EngD program. Research Interests: Focuses on personal health records as economic assets (e.g., MyPHRMachines platform), workflow model transformations (UML/BPMN/Petri-Net), and tools like SHARE/SciModeler for reproducible research. Active in gamification for corporate health and healthcare decision support systems. Awards: Awarded Best Paper (2007, 2012), 2nd Executable Paper Prize (2011). Current activities include teaching Health Information Systems and supervising 9 active PhD students. Advising & Grants: Mentor to 9 current PhD students and 5 alumni. Facilitates industry-academia collaboration through TU/e's innovation initiatives. Labs/Teams: Leads the Information Systems Lab at TU/e and co-leads EAISI Health. Involved in multidisciplinary teams addressing health tech and data science challenges.
Maurizio Leotta is an Assistant Professor in Computer Science at the University of Genova, Italy, where he has been employed since 2018. He is a member of the Department of Computer Science, Bioengineering, Robotics, and Systems Engineering (DIBRIS) within the School of Mathematical, Physical and Natural Sciences. Additionally, he serves on the School Council and the Department Board of DIBRIS. Dr. Leotta received his PhD in Computer Science from the University of Genova in 2015, with a thesis on Automated Web Testing under the supervision of Prof. Filippo Ricca. His doctoral work was revised by Prof. Massimiliano di Penta (Università del Sannio, Italy) and Prof. Ali Mesbah (University of British Columbia, Canada). Before his academic career, he worked as an IT Technician in various companies and participated in research and industrial projects funded by organizations such as Finmeccanica S.p.A. and the Italian Space Agency. Dr. Leotta's primary research focuses on Software Engineering, with particular emphasis on Test Automation, which is his main research topic. He collaborates with Prof. Paolo Tonella from USI, Switzerland on this area. His other significant research interests include Empirical Software Engineering, Requirements Engineering, Business Process Modelling, and Model-Driven Software Engineering. His work often addresses practical challenges in web and mobile application testing, with a growing interest in applying AI and gamification techniques to improve software testing processes. His recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional software testing methodologies, particularly in end-to-end web testing. He has made significant contributions to improving test robustness, addressing flakiness in test execution, and developing tools for better test maintenance. His work also shows increasing interest in gamification approaches to engage developers and students in software testing activities, as well as applications of large language models to enhance test automation. Dr. Leotta has received multiple prestigious awards for his research, including: Best Paper Award at ICST 2025 (Short Papers, Vision and Emerging Results) Distinguished Paper Award at ICST 2023 (Industry Papers) Best Paper Award at QUATIC 2022 (Full Papers) Best Paper Award at ICST 2022 (Demo and Testing Tool Papers) Best Paper Award at QUATIC 2020 (Full Papers) Best Student Paper Award at ICWE 2016 (Full Papers) Dr. Leotta has advised numerous graduate students, including three PhD candidates who have completed their degrees (Andrea Fasciglione in 2024, Dario Olianas in 2023, and Diego Clerissi in 2020). He currently supervises multiple Master's students working on topics related to software testing, web accessibility, and AI applications in software engineering. He has also served as a postdoctoral advisor for researchers including Diego Clerissi and Dario Olianas. Beyond advising, Dr. Leotta has secured research funding through collaborations with industry partners and has been involved in multiple research projects focused on software testing and verification. He co-directs the Software Engineering for Healthcare (SEH) Laboratory, which has been partially supported by Janssen Italia (previously by Actelion Pharmaceuticals Italia). The lab focuses on applying software engineering techniques to healthcare applications, particularly in the areas of wearable technology for patient monitoring and medical data analysis. Dr. Leotta is also active in the Gamify research community, organizing workshops on gamification in software development, verification, and validation.
Dimitri Van Landuyt serves as an Associate Professor in the Department of Computer Science at KU Leuven , affiliated with the Information Systems Engineering Research Group (LIRIS) . He leads and co-promotes multiple high-impact research projects focused on security and privacy engineering, including initiatives on model-driven security risk analysis , privacy by design , and IoT security . His work spans GDPR compliance, synthetic data management, and threat modeling innovations. Academic Leadership : Member of the Council of FEB and Campus Council Leuven/Kortrijk Research Pillars : Privacy threat modeling, security automation, IoT systems, GDPR technical implementation His publications demonstrate expertise in privacy-enhancing technologies, with recent work analyzing LLM applications in threat modeling, developing tree-based privacy analysis frameworks, and creating adaptive trust management architectures. He explores serious games for security training, synthetic data quantification standards, and runtime threat assessment mechanisms. Dimitri contributes to educational programs through courses in ICT Service Management , Security & Privacy by Design , and Research Methodologies . He supervises student research while collaborating with industry and academia on data protection challenges.
Josep Casanovas is a Full Professor at the Statistics and Operations Research Department of the Technical University of Catalonia (UPC), affiliated with the Barcelona School of Informatics. He previously served as head of inLab FIB (2012-2020) and as dean (1998-2004) and vice-rector (2006-2011) of UPC, leading strategic initiatives in university governance and ICT policies. His research focuses on Modelling and Simulation , Internet and Information Systems , and Urban Mobility . He has led projects for the European Union, including C-ROADS Spain, REMEDiAL, and ECHORD++, addressing intelligent transport, software automation, and robotic innovation. Recent publications highlight his work on agent-based simulation for urban health, deep learning applications in traffic and energy savings, and wildfire management tools . He co-directs LogiSim and coordinates the Severo Ochoa Research Excellence Program at the Barcelona Supercomputing Center (BSC-CNS).
Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences. University of Mannheim – Chair for Data Science in the Economic and Social Sciences GESIS – Scientific Coordinator for Digital Behavioral Data Complexity Science Hub Vienna – External Faculty Former Professor at RWTH Aachen University and University of Koblenz-Landau Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology His research focuses on computational social science , algorithmic fairness , network science , and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies. The recent articles reflect a strong trend in studying inequality in algorithmic systems , governance in decentralized organizations (DAOs) , and psychological profiling of AI . His work spans high-impact journals like Nature and Scientific Reports , emphasizing fairness, transparency, and societal impact of data-driven technologies. Notable scientific contributions include: Editor-in-Chief of EPJ Data Science (2018–2022) Founding co-chair of the Computational Social Science section of the German Informatics Society He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure. His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity , which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.
Per Lauvås is an Associate Professor at the Department of Computer Science, Faculty of Technology, Art and Design, Oslo Metropolitan University. His research and teaching focus on IT education, software engineering, and e-learning technologies. Key research areas include Software testing pedagogy Gamification in data modeling education Interactive web development tools Cloud computing and cybersecurity Assessment innovations in database courses Work-integrated learning for IT students Recent publications explore AI chatbots in education, employer prioritization of IT graduates, and gamified learning tools. His work emphasizes student-centered approaches and practical skill development. Contact: pelau8806@oslomet.no
