Lassenius Casper is a Professor at the Department of Computer Science, School of Science, Aalto University. His research focuses on agile software development methodologies, scaling frameworks like SAFe, continuous delivery, and DevOps practices. He has contributed extensively to understanding challenges and benefits in large-scale agile transformations, particularly in global and distributed organizations. Key research interests include: Agile Scaling Frameworks (e.g., SAFe) Continuous Delivery and DevOps Software Engineering Education Agile Adoption Challenges Large-Scale Agile Development Recent publications explore topics such as data-limited experimentation in software ecosystems, challenges in adopting agile frameworks, and the impact of minimum viable products on software failure. His work emphasizes empirical studies and case analyses in industry settings.
Professor Jacob VAKKAYIL is a Full Professor at IÉSEG School of Management in France, serving as the Academic Director for the Human Resource Management track. He holds a Ph.D. from the Xavier Institute of Management in India. His career includes progressive roles from Assistant Professor (2008) to his current position, with prior experience at Indian institutions like the Indian Institute of Management, Kolkata. Research interests focus on institutional dynamics, cross-cultural organizational behavior, and global management challenges. Notable themes include boundary spanning in organizations, resource governance in marginalized regions (e.g., Meghalaya's coal mining), and migrant labor dynamics. His work bridges theoretical frameworks with real-world contexts, particularly in developing economies. Publications span 20 years, reflecting a shift from early career explorations of learning processes and ERP systems (2000s) to contemporary topics like platform labor (2020s). Key areas include: Immigrant worker identity and organizational belonging Informal resource extraction economies Globalization strategies in Indian business schools Awards and grants are not explicitly listed, but his academic leadership roles and prolific publishing underscore his institutional contributions. He teaches in the Grande École and International MBA programs, emphasizing India-centric business contexts and leadership in organizational change.
Colin Fidge is a Professor in the Department of Computer Science at Queensland University of Technology (QUT), Australia. His research focuses on software engineering, cybersecurity, and distributed systems, with emphasis on microservices architecture, industrial control systems, and IoT applications. He collaborates extensively with institutions like QUT's School of Electrical Engineering and Computer Science, contributing to projects in smart cities, fog computing, and blockchain-based manufacturing security. Key research interests include reengineering legacy systems into microservices, anomaly detection in industrial networks, and secure communication protocols for UAVs. He has published widely in top journals like IEEE Transactions and Information and Software Technology. His work spans theoretical contributions (e.g., Petri net models for anomaly detection) and applied solutions (e.g., fog/IoT framework optimizations). Notable publications address challenges in edge computing, data distribution for large-scale systems, and cybersecurity for critical infrastructure. He has co-authored over 161 papers and contributed to books on secure manufacturing and asset management.
Dr. Eng. Kamal Matouk is a researcher in the Department of Process Management at Wrocław University of Economics . His work focuses on Business Intelligence systems, ERP modernization, cognitive technologies, and data-driven decision-making. He has extensively published on topics such as Industry 4.0 integration, cognitive agents in management systems, and knowledge management frameworks. Research Interests : Business Intelligence and Decision Support Systems ERP 4.0 and Industry 4.0 technologies Cognitive agents for enterprise systems Data warehousing and analytics E-Banking and financial technology Integrated management information systems Key Research Trends : Matouk's recent work emphasizes the application of machine learning in environmental costing, cognitive technologies for external environment scanning, and the evolution of ERP systems toward Industry 4.0 standards. His research bridges theoretical frameworks with practical implementations in enterprise resource planning and intelligent system integration. Awards & Grants : No specific awards or grants listed in the provided texts. Labs/Teams : No dedicated lab or team structure explicitly mentioned, though his work suggests involvement in cross-departmental research initiatives focused on enterprise systems and cognitive technologies.
Anne Håkansson is a Professor of Computer Science at KTH Royal Institute of Technology, specializing in Artificial Intelligence and intelligent systems. She also holds a full professorship at UiT The Arctic University of Norway since 2018, with a guest professorship at NTNU Norwegian University of Science and Technology (2020–2022). Her affiliations include leadership roles such as Director of the Senseable Stockholm Lab and Director of Studies for Bachelor and Master Degree projects at KTH. Education : PhD and Associate Professor (Docent) in Computer Science (Uppsala University, 2004 and 2006) Current Roles : Professor at KTH (2010–present), Full Professor at UiT (2018–present), Guest Professor at NTNU (2020–2022) Her research focuses on intelligent software systems, multi-agent systems, and cyber-physical systems (CPS) for applications in smart cities, explainable AI, and environmental impact assessment. She pioneered visualization techniques for colon cancer detection and developed tools like the EIA-system and T-uck for user-centered knowledge modeling. Recent publications emphasize autonomous CPS design, ontology integration, and context-aware systems, reflecting trends in smart urban technology and trustworthy AI in transportation. She has received the KES Award (2012) and served as Uppsala City Ambassador (2009). Scientific contributions include: Supervising over 90 master’s and bachelor’s theses Advising PhD students such as Esmiralda Moradian and Dan Wu Organizing international conferences like KES-AMSTA 2009 and SEB’12 She leads projects such as DigiCityClimate and Volatile Multiple Smart Systems (VoLM2s), emphasizing sustainability and adaptability in heterogeneous environments.
Pierre Nonnon is a Full Professor in the Department of Didactics at the Faculty of Education Sciences, University of Montreal, where he serves as head of the Educational Robotics Laboratory. His office is located at Marie-Victorin local F529, and he can be reached at pierre.nonnon@umontreal.ca or by phone at 514 343-7257. Professor Nonnon has pioneered research in Computer-Assisted Experimentation (ExAO) for over 30 years, developing foundational innovations including the 'appariteur-robot' (1973), 'cognitive lens' concept (1984), and 'Scientific Gymnasium in School' (1992). His work since 1995 focuses on reengineering science laboratories through microlaboratories implemented in secondary schools and colleges. His research spans science and technology didactics, educational robotics, experimental science instrumentation, and implementation of new science programs, emphasizing competency-based learning approaches in experimental sciences. Analysis of his 15 most recent publications (2004-2009) reveals consistent focus on portable microlaboratories, adaptive learning systems, and integration of computer-assisted experimentation in science education. His work demonstrates evolution from theoretical frameworks to practical implementations, with increasing emphasis on making science laboratories more accessible through portable, user-friendly technologies that support both teachers and students in experimental learning processes. Professor Nonnon has supervised 19 graduate students (16 Ph.D. and 3 Master's) from 1989-2016, contributing significantly to science education research. His teaching includes courses such as DID2215 Didactique de la technologie au secondaire, DID3371 Didactique des maths, des sciences et des technologies, and laboratory-focused courses in science-technology didactics. He has been instrumental in developing multiple educational programs including the Microprogramme de 1er cycle de qualification en enseignement, Baccalauréat in science and technology teaching, and Master's programs in education with options in secondary and higher education. His 2017-2020 research project 'Réalisation d'une nouvelle interface du MIcroLab ExAO' funded by Univalor demonstrates continued active research engagement.
Neil Walkinshaw is a Professor in the Department of Computer Science at The University of Sheffield, Faculty of Engineering. He serves as joint PC-chair for the International Conference on Software Testing (ICST'26) and is an associate editor for the Journal of Automated Software Engineering. His research focuses on improving the trustworthiness and reliability of software and cyber-physical systems, with particular expertise in testing "hard to test" systems that have long execution times, non-determinism, limited state observability, and large input/output spaces. He has secured funding from EPSRC (CITCOM, REGI, and STAMINA projects), InnovateUK, DSTL, and the DfT. Walkinshaw's research spans three main areas: Causal Software Engineering : Applying Causal Inference to test causal input-output relationships in software and cyberphysical systems, including scientific models, automated driving systems, and cyberphysical systems. State Machine Inference and Analysis : Developing techniques to understand sequential behavior of systems when a prior model is unavailable, including Extended Finite State Machine inference and LTSDiff algorithm for comparing state machines. Second-order uncertainty in Software Engineering : Using Subjective Logic to reason about uncertainty in empirical software engineering experiments and inferred state machines. His recent publications (2023-2025) demonstrate a strong focus on causal testing methodologies, with applications to scientific software models (CovaSim, Luo-Rudy model), cyber-physical systems (Artificial Pancreas), and automated driving simulators. His work on the CITCOM Causal Testing Framework provides an open-source implementation of these approaches. His scientific achievements include: Best Research Paper Award at EASE'25 for "Using Causal Inference to Test Systems with Hidden and Interacting Variables" Development of the CITCOM Causal Testing Framework (GitHub, MIT License) Significant contributions to state machine inference and analysis Walkinshaw actively supervises PhD students and has successfully guided seven PhD students to completion. He teaches Software Reengineering and leads the Computer Science Ambassadors module, focusing on making Computer Science more inclusive. As the school lead on inclusion in Computer Science, he works to attract more diverse student cohorts into the field. He currently collaborates with Research Software Engineers Michael Foster and Farhad Allian on the CITCOM project (2020-2025), which explores causal testing approaches for hard-to-test systems.
Fouad Riane is an active researcher specializing in supply chain management and operations with significant contributions to healthcare logistics, urban mobility, and sustainable supply chain practices. His work bridges theoretical optimization techniques with real-world applications across hospital systems, agri-food networks, and city transportation infrastructure. His primary research domains include Supply Chain Management, Operations Management, Lean Six Sigma, and Data Driven Decision Making, with specialized expertise in production-distribution integration, returnable transport items management, and healthcare logistics optimization. Methodologically, he employs discrete event simulation, heuristic algorithms, agent-based modeling, and performance evaluation frameworks to solve complex logistics challenges in dynamic environments. Analysis of his 15 most recent publications (2024-2025) reveals a strong emphasis on healthcare operations, particularly automated drug distribution systems in hospitals and emergency departments. His work demonstrates consistent methodological rigor through comparative software benchmarking (FlexSim vs AnyLogic) and innovative algorithm development, including artificial-immune-system-based approaches enhanced with deep reinforcement learning. Key application areas span Belgian blood distribution networks, Casablanca urban transport systems, and agri-food sustainability initiatives, with frequent collaboration with Evren Sahin, Alain Guinet, and Christine Di Martinelly across multiple publications. Riane's research exhibits clear evolution toward more sophisticated computational approaches while maintaining practical relevance, with recent publications addressing critical challenges in supply chain resilience, resource sharing mechanisms, and sustainable logistics design across multiple continents.
Ramnatthan Alagappan is an Assistant Professor at the Siebel School of Computing and Data Science, University of Illinois. His research focuses on distributed systems, storage systems, and fault tolerance in modern datacenter environments. He leads projects investigating high-performance storage abstractions, replication strategies, and reliability engineering for distributed infrastructure. Key research areas include filesystem design, crash consistency mechanisms, and optimizing storage hierarchies for hybrid NVM environments. His work emphasizes practical implementations of theoretical models, such as the LazyLog shared log abstraction and IONIA replication framework for disk-based key-value stores. Alagappan has received the NSF CAREER Award (2024) for his research on datacenter-aware storage systems. His recent publications address challenges in disaggregated datacenters, fault tolerance for modern workloads, and automated reliability testing for cluster management systems. He collaborates extensively on projects involving distributed storage protocols, log-based systems, and performance optimization for large-scale infrastructures. His research spans theoretical contributions (e.g., consistency models) to applied systems work (e.g., implementing fault-tolerant storage stacks), with a focus on bridging gaps between hardware capabilities and software system design.
Wilma Russo is a Full Professor of Computer Engineering at the University of Calabria's Department of Computer Engineering, Modeling, Electronics and Systems (DIMES). She holds a degree in Physics from the University of Naples (1975). Her research focuses on distributed/parallel systems in heterogeneous environments, with current interests in agent-based computing, content delivery networks, and Internet of Things. Her publications demonstrate sustained innovation in IoT architectures, agent-based modeling, and edge computing solutions. Recent work emphasizes methodological frameworks for IoT integration and opportunistic service paradigms.
Raffi Khatchadourian is an Associate Professor in the Department of Computer Science at Hunter College, part of the City University of New York (CUNY). He specializes in Software Engineering, Programming Languages, and Machine Learning Systems. His research focuses on automated software evolution, secure software engineering, and refactoring techniques, with notable contributions to tools like Hybridize Functions and μAkka. He holds a PhD in Computer Science from Ohio State University, along with MS and BS degrees in Computer Science from Ohio State and Monmouth University, respectively. His educational background includes advanced training in Computer Science, with a focus on theoretical and practical aspects of software systems. His research interests span automated refactoring, program analysis, and the integration of machine learning with traditional software engineering practices. Key projects include frameworks for assessing safety in deep learning systems (ReLESS) and mutation testing for actor concurrency in Akka (μAkka). Khatchadourian’s work emphasizes tool development and open-source contributions, such as the Common-Eclipse-Refactoring-Framework and Hybridize-Functions-Refactoring. He has secured grants from the National Science Foundation (NSF) for combating technical debt in machine learning systems and improving imperative-to-graph execution migration. His teaching spans graduate courses on programming languages and software engineering, reflecting his commitment to advancing computational education. His lab, Ponder Lab, focuses on empirical studies and tool creation for software evolution and concurrency. Notable grants include SHF-funded projects addressing practical analyses and safe transformations in deep learning programs. His research has addressed challenges in migrating deep learning code to graph execution, optimizing Java 8 streams, and analyzing legacy software refactoring.
Dr. Mahmoud H. Qutqut is an Assistant Teaching Professor in the Faculty of Computer Science at the University of New Brunswick (UNB) in Fredericton, Canada since September 2023. Previously, he served as Chair of the Cybersecurity and Cloud Computing Department at Applied Science University in Jordan (July 2022–August 2023) and was promoted to Associate Professor there in December 2019. He has held academic positions since 2014, including a visiting role at Queen’s University (2017–2019) where he contributed to research and teaching. His educational background includes a Ph.D. (2014) and M.Sc. (2008) in Telecommunication Systems, and a B.Sc. (2004) in Computer Systems. Research interests focus on smart city technologies, IoT, cybersecurity, and data-driven networks. He actively publishes in top-tier venues such as IEEE Access and has served on technical committees for conferences and journals. Notable achievements include a Teaching Excellence Award nomination (2018) and founding the Cisco Academy at Applied Science University (2015). Dr. Qutqut’s academic career spans teaching roles at Queen’s University, where he instructed courses on computer networks and computing fundamentals. His research bridges theoretical advancements with practical applications in network security, machine learning, and IoT systems. He has supervised impactful student projects, such as winning entries in graduation competitions (2017).
Dr. Farjam Eshraghian is a Senior Lecturer in Digital Business at the School of Applied Management, Westminster Business School (WBS), University of Westminster. He leads modules such as Digital Business Fundamentals and Big Data Analytics and Business Intelligence, and oversees the MSc Digital Business course since 2023. His research focuses on emotional responses to AI, platformisation, data analytics, and information quality perception. He holds a PhD in Technology and Information Management from the University of Edinburgh, an MBA in Technology Management, and a BEng in Mechanical Engineering. Education: PhD: Technology and Information Management, University of Edinburgh MBA: Technology Management BEng: Mechanical Engineering (Thermo-fluids) PGCert in Higher Education, Queen Mary University of London Dr. Eshraghian’s research explores AI’s impact on work environments, digital platform dynamics, and data-driven decision-making. His work has been published in journals like Information Technology & People and presented at conferences such as Academy of Management (AOM) and EGOS. He is a Fellow of the Higher Education Academy (FHEA) and has served as a reviewer for multiple journals and conferences. His career includes roles as a lecturer and researcher at the University of Edinburgh and industry experience in information systems development across automotive, manufacturing, and healthcare sectors. Awards: Fellow of Higher Education Academy (FHEA) Dr. Eshraghian’s teaching and research emphasize practical applications of digital technologies in business contexts. He actively contributes to the Centre for Digital Business Research, focusing on innovation and organisational transformation through digital tools.
Reinhard Jung is a Full Professor of Business Engineering at the University of St. Gallen , where he also serves as Director of the IWI-HSG institute. Since 2021, he has held the role of Dean of the School of Management . Prior to this, he was a Full Professor at the University of Duisburg-Essen (2007-2009) and an Assistant Professor at the University of Bern (2002-2007). His research focuses on Digital Transformation , Blockchain Technology , Business Ecosystems , and Wearable Technology . Key areas include analyzing how technology impacts organizational processes, value creation in ecosystems, and behavioral change mechanisms driven by digital tools. His work bridges theoretical frameworks with practical applications in industries like healthcare, finance, and logistics. He advises students such as Tobias Mirsch and has contributed to over 100 publications since 2008, addressing topics ranging from social CRM to agile IT governance . His research emphasizes the intersection of technology, business strategy, and human behavior. Jung’s leadership roles include shaping the IWI-HSG as a hub for innovation in business engineering and driving strategic initiatives as Dean, focusing on interdisciplinary education and digital transformation strategies.
Dr Athar Qureshi is a Senior Lecturer at the School of Public Health within the Faculty of Health and Medical Sciences at the University of Adelaide. He holds a PhD, Master in ICT Management, and an Honours in Computer Sciences, complemented by a Certified Knowledge Manager credential. His primary affiliations include teaching and research roles focused on healthcare innovation and digital transformation. Dr Qureshi's academic journey includes over 20 years of experience across four countries in curriculum development and educational delivery. He specializes in enterprise transformation, leadership, and organisational change within healthcare contexts. His research emphasizes digital transformation strategies, knowledge management, and innovation pathways in healthcare organizations. His teaching philosophy integrates strategy and systems thinking, achieving high student outcomes through participatory learning methods. He leads interdisciplinary research on digital healthcare transformation with industry partners, supported by a dedicated research grant. Key publications address digital business frameworks, chatbot applications, and trust-based innovation models. Dr Qureshi actively engages in professional activities such as consultancies, masterclasses, and keynote speaking. His work bridges theory and practice, fostering innovation through resilience-building and boundary-pushing methodologies.
