Ali Hamie is a Senior Lecturer at the School of Architecture, Technology and Engineering (University of Brighton, UK), specializing in formal methods in software engineering and ontology modeling. With over 35 publications, his work bridges theoretical formalisms like UML, OCL, and JML with practical implementation validation. BSc in Pure Mathematics (Lebanese University, 1982) Postgraduate Diploma in Computing (University of Essex, 1986) MSc in Computer Science (University of Essex, 1987) PhD in Computer Science (University of Essex, 1991) His research focuses on formal aspects of software development , including specification patterns, design by contract, and translation between formal notations (OCL to JML). Recent work examines diagrammatic reasoning in ontology engineering and hybrid modeling approaches combining formal and agile methods. Studies show his publications span formal methods , ontology modeling , and constraints validation , with recurring themes in OCL-JML interoperability, diagrammatic notations, and user-centric formalism evaluation. Awards include Fellow of the Higher Education Academy (2017) . He supervises research in formal computing, with past topics covering concept diagrams and ontology modeling. His academic career includes postdoctoral roles at Newcastle University and EPSRC-funded work at Imperial College.
Tse-Hsun (Peter) Chen is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. He serves as Director of the SPEAR lab (Software Performance, Analysis, and Reliability lab), which focuses on improving the quality of large-scale software systems through research in log analysis and AIOps, software performance analysis, software testing, and mining software repositories. His research group maintains extensive collaborations with industry partners including ERA Environmental, Ericsson, Microsoft, and BlackBerry. Dr. Chen received his PhD and MSc in Computer Science from Queen's University and his BSc in Computer Science from the University of British Columbia. Dr. Chen's research addresses critical challenges in modern software engineering, including leveraging Large Language Models to assist developers with development, debugging, and maintenance; helping developers debug production systems by utilizing rich software data; providing optimization suggestions by analyzing user usage data; improving software quality assurances in DevOps environments; and mining software development history for useful developer suggestions. His work spans Software Engineering, Performance Engineering, DevOps & AIOps, Software Testing, and Mining Software Repositories, with a strong emphasis on practical applications that bridge academic research and industrial practice. His recent publications (2024-2025) demonstrate a pronounced shift toward integrating Large Language Models into various aspects of the software engineering lifecycle, particularly in log analysis, fault localization, code generation, and performance testing. This trend reflects the growing importance of AI in software engineering research and practice. Gina Cody Research award (2022) Ranked as one of the most active software engineering researchers worldwide by an independent study published in JSS Dr. Chen has successfully advised numerous PhD and Master's students, many of whom have secured prestigious academic positions. Several of his graduated PhD students now hold tenure-track assistant professor positions at institutions including York University, University of Alberta, DePaul University, and IIT Gandhinagar. His SPEAR lab has developed research tools that have been integrated into industrial practice for ensuring the quality of large-scale enterprise systems. The SPEAR lab, under Dr. Chen's leadership, has established itself as a leading research group in software engineering, with particular expertise in software performance analysis, log analysis, and AI applications for software engineering. The lab maintains strong industry connections and has produced numerous high-impact publications in top-tier software engineering venues including ICSE, FSE, ASE, and TSE.
Jean-Marc Jezequel is a Professor of Software Engineering at University of Rennes , affiliated with CNRS , Inria , IRISA , and Institut Universitaire de France (IUF) . His research focuses on Model-Driven Engineering , Software Product Lines , Dynamic Adaptation , and Executable Meta-languages . Key Contributions : Pioneering work in aspect-oriented and model-driven approaches for software evolution Foundational research on model transformations (e.g., UMLAUT framework) Advances in testing and validation of distributed systems Research Trends from his recent publications include: Intelligent modeling assistance integrating machine learning Contextual variability modeling for complex systems Runtime model execution for self-adaptive systems Formal methods and constraint resolution for UML validation Collaborations include researchers from Luxembourg, Montreal, Colorado State University, and INRIA.
Raffi Khatchadourian is an Associate Professor in the Department of Computer Science at Hunter College and the Graduate Center of the City University of New York (CUNY). His research focuses on techniques for automated software evolution, particularly automated refactoring and source code recommendation systems, with the goal of easing the burden associated with evolving large and complex software through automated tools. He also conducts research on the automated analysis of Object-Oriented programs. Ph.D., Computer Science & Engineering, Ohio State University (2011) MS, Computer Science & Engineering, Ohio State University (2010) BS, Computer Science, Monmouth University (2004) Khatchadourian's research spans multiple areas of software engineering and programming languages, with particular emphasis on automated software evolution techniques. His work addresses critical challenges in refactoring legacy systems to modern language constructs, optimizing parallel processing in Java 8 streams, and addressing technical debt in machine learning systems. His recent research has expanded into deep learning program transformation, where he develops techniques to convert imperative deep learning code to more efficient graph execution models while ensuring safety. His approach combines static analysis, program transformation, and empirical validation to create practical tools that developers can integrate into their workflows. Analysis of Khatchadourian's recent publications reveals a strong focus on bridging the gap between theoretical program analysis and practical software engineering challenges. His work increasingly intersects with machine learning systems, examining both how to improve ML code through refactoring and how to ensure safety in deep learning frameworks. The research demonstrates consistent evolution from foundational work on Java language features toward more complex systems involving concurrency, deep learning, and automated program transformation. Distinguished Paper Award at SCAM '18 for work on Java 8 stream optimization EAPLS Best Paper Award at FASE '20 for study on Java 8 stream usage EAPLS Distinguished Paper Award at FASE '25 for Deep Learning refactoring work Best Paper Award nominee at IJCAI '24 for AI safety framework Khatchadourian actively mentors graduate and undergraduate students, with several advisees going on to successful academic and industry positions. His former Ph.D. student Tatiana Castro Vélez accepted a tenure-track Assistant Professor position at the University of Puerto Rico. He has supervised numerous master's theses and undergraduate research projects, often resulting in co-authored publications at top software engineering venues. His research has been supported by various grants, though specific funding details are not prominently featured in the available information. Through his work on tools like Fraglight for aspect-oriented programming and Hybridize Functions for deep learning refactoring, Khatchadourian has established a research group focused on practical program analysis and transformation. His lab develops Eclipse plugins and other IDE-integrated tools that help developers with automated refactoring, bug detection, and code optimization. The group maintains active collaborations with researchers at other institutions and contributes to open-source projects on GitHub.
Pat Barrow is a Senior Lecturer in Business Information Systems at Norwich Business School, University of East Anglia. He holds a PhD (2000) and MA (2007) from UEA, alongside a BSc (1993). His academic background focuses on stakeholder evaluation in Rapid Application Development and organizational aspects of Information Systems. Though he transitioned to a non-research role in 2000, his past research explored requirements engineering, UML formalisms, and systems evaluation in Saudi Arabian private organizations. He teaches extensively across undergraduate and postgraduate levels, including MBA programs. Education: BSc (1993), PhD (2000), MA (2007) from University of East Anglia Research interests include IS design, supply chain digitalization, and human-centric IS challenges. Though not currently publishing, his prior work addressed system evaluation methodologies and software development patterns. He has coordinated administrative roles such as Senior Advisor for Postgraduate Students (2023–) and Workload Allocation Model coordinator (until 2021).
Dr. Sam S. Ramanujan is Professor of Computer Information Systems and Analytics at the University of Central Missouri , affiliated with the Harmon College of Business and Professional Studies . He teaches advanced object-oriented programming and software engineering courses, combining over two decades of academic expertise with substantial industry experience in complex system deployment. Doctor of Philosophy in Information Systems (University of Houston, 1995) MBA in CIS and Quantitative Analysis (University of Arkansas, 1989) PGDM in Information Systems (XLRI Institute of Management Studies, 1987) Bachelor of Arts (Hons) in Economics (University of Delhi, 1985) His research spans big data architecture , visual analytics , healthcare IT , and legal aspects of technology . He has published extensively on topics including software maintenance, e-commerce trust models, and cloud-based healthcare systems, with a focus on bridging technical and legal challenges in digital environments. Dr. Ramanujan's academic work shows a consistent focus on software engineering (1995–2017), healthcare IT (2004–2017), and legal-compliance frameworks (2000–2017). His publications demonstrate interdisciplinary expertise in merging technical systems with regulatory requirements . Best Paper Award , Journal of American Academy of Business, Cambridge (2006) He has contributed to pedagogical advancements in distributed computing curricula and collaborates with scholars like S. Kesh and S. Nerur. His industry experience informs real-world applications of his research in software maintenance and offshore operations.
Professor Robert J. Walker is a faculty member at the University of Calgary's Department of Computer Science and serves as Director of the Laboratory for Software Modification Research. His work centers on software engineering, emphasizing software evolution, reuse, and practical tools for real-world development challenges. Research areas include pragmatic software reuse, structural patterns, heuristic search, recommendation systems, collaborative software development, software dependency analysis, and technical risk estimation. Teaches courses like CPSC 499.01 Software Analysis (Fall 2025/Winter 2026) and CPSC 233, focusing on static analysis techniques and structured computer science education. Provides service as former editorial board member for ACM Transactions on Software Engineering and Methodology and Advances in Software Engineering , including a stint as Acting Editor-in-Chief.
Yvonne Dittrich is a Professor at the IT University of Copenhagen (ITU), affiliated with the Software Development Group. She holds an adjunct professorship at IIT Mandi, India, and has held roles at institutions in Sweden, Canada, and the U.S. Her research focuses on cooperative and human aspects of software engineering, including Continuous Software Engineering (CSE), use-oriented design, and end-user development (EUD). She has led projects like SAIA-Farm (sustainable irrigation via satellite analytics) and contributed to frameworks like 'Cooperative Method Development.' **Education**: PhD in Computer Science (Hamburg University, 1997), M.Sc. from TU Darmstadt. **Research Interests**: She pioneers methods bridging software engineering with human-centric practices, emphasizing sustainability and participatory design. Her work addresses challenges in global software development, agile methodologies, and software ecosystems. **Awards**: TAT-Förderpreis (1989), Best Paper Award (2018), Distinguished Reviewer recognition (2018). **Grants & Leadership**: Led projects funded by the Danish Innovation Fund, EU, and others. Served on editorial boards for IEEE Transactions on Software Engineering and Journal of Systems and Software. **Labs/Teams**: Collaborates with labs in Denmark, India, and Canada on interdisciplinary projects, including smart irrigation systems and fintech ESG data commons.
Dr. Theresa Züger is an interdisciplinary researcher leading the AI & Society Lab at the Alexander von Humboldt Institute for Internet and Society (HIIG). She investigates how AI systems can be designed to serve the common good, focusing on initiatives that promote sustainability, strengthen social inclusion, and enable technology reuse through open systems. Her work addresses societal challenges associated with artificial intelligence at political, social, and cultural levels, contributing to accurate assessment of AI's societal implications. Züger received her Ph.D. in Media Studies from Humboldt University in Berlin in 2017 with her dissertation 'Reload Disobedience,' focusing on digital forms of civil disobedience. Previously, she earned an M.A. in Theatre, Film and Television Studies as well as German and Philosophy from the University of Cologne. She also headed the office responsible for the German government's Third Engagement Report on behalf of the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth (BMFSFJ). Her research centers on Public Interest AI, examining how AI development and deployment can benefit society rather than primarily maximizing profit. Current projects include 'Impact AI' (funded by Volkswagen Foundation), which develops auditing methods to assess AI projects' impact on public interest and sustainability, and 'Human in the Loop,' investigating how automated decision-making processes should be designed for successful human-machine interaction. She previously led the 'Public Interest AI' project, developing a theoretically grounded understanding of public interest AI and creating prototypes like a web accessibility tool and fact-checking application. Analysis of her recent publications reveals a consistent focus on bridging AI technology with societal values. Her work spans technical aspects of AI implementation, ethical considerations, and practical applications that serve public interests. Key trends include human-AI collaboration frameworks, accessibility enhancements, critical examination of AI hype, and theoretical foundations for public interest-oriented AI development. Züger serves as Vice-Chair of the UNESCO Commission on Communication and Information and participates in several juries including the Deep Tech Award, Digital Places – Land of Ideas, and the Civic Innovation Fund. She is also a regular event moderator for organizations like the Berlin-Brandenburg Media Authority, re:publica, and transmediale. As project leader of Impact AI and head of the AI & Society Lab, Züger directs significant research initiatives with funding from organizations like the Volkswagen Foundation. Her work involves extensive collaboration with academic and practical partners across Europe and globally, particularly through projects addressing women in tech and international AI governance. The AI & Society Lab functions as an interdisciplinary interface for new research approaches and knowledge transfer in AI, promoting inclusive, human rights-friendly, and sustainable AI strategies in Europe.
Jinqiu Yang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. Her research focuses on improving software reliability and quality assurance, particularly in the context of machine learning systems and autonomous vehicles. She leads active research projects in software testing, automated program repair, and mining software repositories, with strong connections to both academic and industrial applications. Her research interests span software reliability, quality assurance of machine learning systems including autonomous vehicles, software testing, automated program repair, text analytics of software artifacts, and mining software repositories. She has developed novel approaches for testing deep learning libraries, evaluating robustness in autonomous driving systems, and tracking the evolution of static code warnings. Her work bridges traditional software engineering with emerging challenges in AI systems, addressing critical issues of reliability and safety in complex software environments. Yang's recent publications (2021-2025) demonstrate a clear trajectory toward AI/ML system reliability, with increasing focus on autonomous vehicles, concept drift detection, and security aspects of large language models. Her work spans both theoretical foundations and practical applications, often involving empirical studies of real-world systems and development of practical tools to address identified challenges. ACM SIGSOFT Distinguished Paper Award Dr. Yang actively mentors graduate students and is currently recruiting Master's and PhD candidates. She has secured significant research funding including NSERC Discovery Grants (2019-2025), Gina Cody Research and Innovation Fellowship (2024-2026), and participation in the NSERC CREATE Program SE4AI (2021-2026). Her research is supported by multiple grants including NOVA – FRQNT-NSERC PROGRAM (2024-2027) and Volt-Age Seed Grant (2024-2026). She leads research in the O-RISA Lab at Concordia University, focusing on reliability and security aspects of intelligent software systems. Her team collaborates with industry partners including IBM, where she previously worked at IBM Watson Research Lab and IBM CAS, bringing practical experience to her academic research.
Maryam Razavian is an Assistant Professor in the Information Systems group within the Department of Industrial Engineering and Innovation Sciences at Eindhoven University of Technology (TU/e). Her research focuses on understanding and guiding information system design processes from both business and technical perspectives. Dr. Razavian received her PhD in Computer Science from VU University Amsterdam, where her dissertation focused on knowledge-driven migration to services funded by the NWO/Jacquard SAPIENSA project. She also holds an MSc from Tehran University and has worked as a Research Assistant at Politecnico de Torino. Her research interests include information system design reasoning, human aspects of information system design, software architecture, service orientation, and increasingly focuses on ethical considerations in software systems. A common theme in her work is understanding how designers carry out design thinking as a key to developing models and approaches for guiding information system design. Dr. Razavian's publication record demonstrates consistent contributions to software engineering and information systems research, with recent work focusing on ethical values in software systems, stakeholder inclusion, and the integration of rational and intuitive thinking in design processes. Her research examines how to incorporate ethical values into architecture design decision-making, including the development of the Ethics-Aware DecidArch Game to help software architects reflect on ethical considerations. Active member of program committees for major conferences including ICSE/SEIS (2015), WICSA (2015-2017), ER (2013-2014) Reviewer for journals such as Journal of Systems and Software and IEEE Software Teaches courses in research methods and design of AI systems at TU/e Her work bridges the gap between technical design processes and their broader societal implications, positioning her at the forefront of research on ethics in software engineering.
Elisa Baniassad is a Teaching Professor in the Department of Computer Science at the University of British Columbia (UBC), within the Faculty of Science. She specializes in software engineering education and has received numerous teaching accolades including the UBC Killam Teaching Prize and CS-Can/INFO-CAN Excellence in Teaching Award. Her courses focus on software construction, engineering principles, and advanced software design. Dr. Baniassad has taught CPSC 310 (Introduction to Software Engineering), CPSC 210 (Software Construction), and CPSC 410 (Advanced Software Engineering) across multiple terms since 2000. Her research interests span educational methodologies in software engineering, aspect-oriented programming, and the design of effective learning tools. Notable contributions include studies on team dynamics in software development, automated assessment techniques, and pedagogical frameworks for large-scale programming courses. She has authored over 50 peer-reviewed articles on topics ranging from mutation analysis in student tests to the efficacy of online learning environments. Awards include recognition for teaching excellence at UBC and contributions to computer science education. Her work emphasizes practical applications of software engineering principles in academic settings, with a focus on fostering student mastery through innovative assessment strategies and feedback mechanisms.
Yasmina Abdeddaïm is an Associate Professor at Université Gustave Eiffel and affiliated with ESIEE Paris. She works within the Laboratoire d'Informatique Gaspard-Monge (Softwares, Networks and Real-time team) and serves as Head of the Master in Artificial Intelligence and Cybersecurity (AIC) program. Her research focuses on real-time systems, critical systems, and scheduling algorithms. University: Université Gustave Eiffel Role: Head of Master AIC program Laboratory: Laboratoire d'Informatique Gaspard-Monge Team: Softwares, Networks and Real-time Her research spans real-time systems , mixed-criticality scheduling , energy-harvesting systems , and probabilistic schedulability . Recent publications analyze compilation optimization impacts on timing variability and propose new models for real-time deep neural networks over GPUs. She employs formal methods like timed automata for scheduling verification. Her teaching includes courses on Real-time Systems , Model Checking , Critical Application Development , and Artificial Intelligence . She is based at Cité Descartes, Champs-sur-Marne, France, with office contact details provided.
Associate Professor Wayne Wobcke is a faculty member in the School of Computer Science and Engineering at the University of New South Wales (UNSW), where he has been employed since 2002. His academic career includes previous positions at the University of Sydney until 1998, British Telecom Labs in the UK for three years, and the University of Melbourne for one year. He holds a PhD in Computer Science from the University of Essex (1989), an MSc from the University of Queensland (1985), and a BSc (Hons) in Mathematics/Computer Science from the University of Queensland (1984). Dr. Wobcke's research spans both theoretical and practical aspects of artificial intelligence and data science. His work encompasses intelligent agents, data mining, agent-based modeling, dialogue management, personal assistants, recommender systems, and computational social science. He has collaborated extensively with industry through three Cooperative Research Centres (Smart Internet Technology CRC, Smart Services CRC, and Data to Decisions CRC), where he served as a Programme Manager and Project Leader for over 10 years. Notable achievements include developing a voice-controlled mobile application for email and calendar interaction (a precursor to Apple's Siri) and deploying a people-to-people recommender system for online dating on one of Australia's largest dating sites. His recent research focuses on data science in humanitarian contexts and machine learning applications in official statistics, conducted in collaboration with BPS (Statistics Indonesia) and STIS (Politeknik Statistika, Indonesia). His publication record shows a consistent trajectory of impactful research, with recent work concentrating on poverty targeting, domain adaptation, natural language processing for recommender systems, and political opinion mining. Scientific Awards: Best Paper Nomination, 11th Workshop on Argument Mining (2024) UNSW Arc Postgraduate Research Supervisor Award (2017, 2018) AAAI Deployed AI Application Award, Twenty-Sixth Annual Conference on Innovative Applications of Artificial Intelligence (2014) Best application paper runner up, 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (2013) Dr. Wobcke has successfully supervised numerous research students, with Irwan Rahadi currently working on 'Causal Modelling and Machine Learning for Official Statistics'. His grant portfolio includes significant funding from the Australian Research Council and various Cooperative Research Centres, totaling over $3.7 million since 2003. He teaches COMP9414 Artificial Intelligence and COMP9727 Recommender Systems at UNSW.
Professor Omar Alam is an Associate Professor in the Department of Computer Science at Trent University. His research focuses on software engineering, particularly Model-Driven Software Engineering, Aspect-Oriented Modelling, and Mining Software Repositories. Prior to Trent, he earned his PhD at McGill University, specializing in Model-Driven Engineering. He has received notable awards such as the ACM SIGSOFT Distinguished Paper Award (2019) and the Merit Award for Excellence in Research (2022). His teaching includes courses like Software Specification (COIS 3030), Software Design and Modeling (COIS 2240), and Software Architecture (COIS 3040). Key grants include the NSERC Discovery Grant (2017-2024) and past fellowships from NSERC and FRQNT. His work spans collaborative modeling, automated grading systems, and empirical studies on developer practices. Research often intersects software development methodologies, tool integration, and socio-technical aspects of computing. His recent publications explore topics like developer workplace communication, transit schedule deviations using real-time data, and three-way domain-specific model differencing. He actively contributes to journals like SoSyM and conferences such as SLE and ICSM. His teaching excellence is recognized through student awards and nominations, reflecting his commitment to pedagogy in computer science education.
