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Martin Weyssow is a Research Scientist (Postdoc) at Singapore Management University (SMU), affiliated with the Centre for Research on Intelligent Software Engineering (RISE). His work focuses on advancing large language models (LLMs) for software vulnerability detection, code generation, and continual learning. He holds a Ph.D. in Computer Science from Université de Montréal, where his thesis explored efficient alignment of LLMs for code generation, earning the highest distinction with an exceptional mention. Weyssow has been awarded prestigious scholarships including the Google Scholarship for Excellence and the FRQ Merit Scholarship for Foreign Students. Education : Ph.D. in Computer Science, Université de Montréal (2020–2024) M.Sc. in Computer Science & Data Science, University of Namur (2018–2020) B.Sc. in Computer Science & Mathematics, University of Namur (2015–2018) Research Interests : LLM alignment for code analysis, vulnerability detection, parameter-efficient fine-tuning, and lifelong learning systems. His work bridges deep learning, NLP, and software engineering to enhance LLM adaptability in dynamic coding environments. Grants & Awards : NSERC Alliance International Catalyst Grant (2022–2023) Google Scholarship for Excellence (2021–2022) FRQ Merit Scholarship for Foreign Students (2022–2024) Current Projects : Leading research on LLM-driven vulnerability detection and parameter-efficient techniques for code generation at RISE. Supervising students on topics like self-supervised learning and neural interface design. Active in grant-writing and international collaborations. Labs & Teams : Member of the SOftware Analytics Research (SOAR) Lab at SMU and collaborator with Prof. David Lo’s team.

• Deep Learning
• Natural Language Processing
• Software Engineering
• +5 more

Louis-Edouard Lafontant is a Lecturer at the Department of Computer Science and Operations Research (DIRO) at the University of Montreal. His research focuses on model-driven engineering, projectional editing, and software accessibility through tools like Gentleman. He is currently pursuing a Doctorate in Computer Science at UdeM under Prof. Eugène Syriani, where his work explores dynamic environments and interface design. Education: Doctoral candidate in Computer Science (UdeM). Previously involved in teaching roles for courses including IFT1015 (Programming I), IFT2255 (Software Engineering), and IFT3911 (Software Analysis & Design). Offers tutoring services through DIRO's tutoring program and personal consultations. Research Interests: Projectional editing systems, domain-specific languages (DSLs), model-driven engineering (MDE), and software accessibility. His project Gentleman aims to democratize software modeling through a lightweight web-based editor supporting multiple notations and user-specific interfaces. Publications & Projects: Published work includes studies on Gentleman's usability, integration into web applications, and DSL creation. Open-source contributions include the Gentleman editor, Zenkai JavaScript library for DOM manipulation, and educational web resources. Active in labs such as GEODES, focusing on software engineering research.

• Software Engineering
• Domain-Specific Languages (DSLs)
• Model-Driven Engineering (MDE)
• +4 more

Daniel Strüber is an Associate Professor in Software Engineering at the joint Interaction Design and Software Engineering Division of Chalmers University of Technology and the University of Gothenburg, Sweden. He is also affiliated with the Department of Software Science at Radboud University Nijmegen, Netherlands. His research focuses on model-driven engineering, AI engineering, and variability management to enhance software quality, security, and collaborative development across domains like robotics and web systems. Education : Diplom (M.Sc. equivalent) in Computer Science from Philipps University Marburg (2011, with distinction), Ph.D. (summa cum laude) from Philipps University Marburg (2016). His research bridges empirical, formal, and engineering approaches to address developer challenges in ML-enabled systems. Key trends in his work include model-driven methods for ML deployment, variability management in robotics, and empirical studies of tool usability. He has co-edited a Journal of Systems and Software special issue on software product lines. Scientific Awards : Best Reviewer Awards (SoSyM 2025, GPCE 2024), Transformation Tool Contest Awards (2017, 2020), Best Paper Awards (VAMOS 2019, ICMT 2016), and multiple conference nominations. As a supervisor, he guides current Ph.D. students like Vladislav Indykov and Weixing Zhang, while his former advisees include Shayan Ahmadian and Samuel Idowu. Grants include a VR Open Call Grant (2022-2024) for SEMLA and a DFG Individual Fellowship (2019) for EUphORia. His teaching spans courses on Software Engineering for AI Systems and Software Product Lines , often integrated with real-world projects via GiPHouse.

• Model-Driven Engineering
• AI Engineering
• Software Quality Assurance
• +12 more

Jolan PHILIPPE is a Lecturer at University of Orléans affiliated with LMV research laboratory, and currently holds a postdoctoral position at Université de Rennes in the DiverSE team under the supervision of Olivier Barais. His research focuses on Infrastructure as Code (IaC) and distributed systems reconfiguration, with particular emphasis on formal methods and model-driven approaches. His primary research interests include: Distributed Systems and Cloud Computing Infrastructure as Code (IaC) and DevOps Model Driven Engineering Formal Methods and Verification Parallel and Distributed Programming Algorithmic Skeletons Dr. PHILIPPE's work demonstrates a strong trajectory from foundational research in parallel programming models (particularly through his work on PySke) to applied research in distributed system reconfiguration. His recent publications show increasing focus on formal approaches to infrastructure management, with significant contributions to languages like Concerto-D and frameworks like Ballet for cross-DevOps reconfiguration. His research bridges theoretical computer science (formal methods, verification) with practical cloud infrastructure concerns. He is actively supervising two PhD candidates: Haitam El Hayani (Taranis project, 2024-2027) - Extending Infrastructure as Code (IaC) languages, focusing on enhancing capabilities and integration with modern cloud deployment practices Olivia Proust (For-Coala project, 2025-2028) - Towards formally verified configuration management languages Dr. PHILIPPE is deeply involved in research coordination: Coordinator of the "Défi GDR GPL" (challenge) ADDYCT (ADaptation DYnamique et ConTinue) for 2026-2030 One of the leaders of the GDR GPL's GT SyLA (Groupe de Travail - Système Logiciel Adaptable) since February 2025 Helped organize the VELVET (Verification and Software Engineering for DevOps and Reconfiguration) days in Nantes, December 2023 His service to the academic community includes: Program Committee Member for DebConf 2025, ICCS 2025, LowCode@MODELS 2025 Publicity Chair and Program Committee Member for UCC 2025 and BDCAT 2025 Reviewer for journals (COLA, SoSyM) and multiple international conferences

• Distributed Systems
• Infrastructure as Code (IaC)
• Model Driven Engineering
• +5 more

Rebekka Wohlrab is a tenure-track Assistant Professor in Software Engineering at Chalmers University of Technology (Gothenburg, Sweden) and an adjunct faculty member at Carnegie Mellon University’s Software and Societal Systems Department (S3D). Her research focuses on requirements engineering, self-adaptive systems, and robotics. She leads a research group supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP). Education: PhD in Computer Science and Engineering (Chalmers, 2020), MSc/BSc in Computer Science (Paderborn University, 2016). Postdoc at Carnegie Mellon University (2020-2022). Research interests include requirements conflicts resolution, quality attribute trade-offs, and ethical monitoring in cyber-physical systems. She has published extensively on adaptive systems, architectural tactics, and agile development practices. Notable contributions include frameworks for robot mission planning, security assurance cases, and traceability management in automotive systems. Recent awards include a pedagogical prize from students at Chalmers. She advises PhD students on topics like self-adaptive robotics and WASP-funded projects. Her work spans theoretical research and industry collaboration (e.g., Volvo Cars). Active in conferences like ICSE, RE, and ICSA as a program committee member. Labs/Teams: Leads the Self-Adaptive Systems Research Group at Chalmers, collaborating with WASP and automotive industry partners.

• Requirements Engineering
• Software Architecture
• Self-Adaptive Systems
• +4 more

Daniel Gritzner is a researcher at the Institute for Information Processing (Leibniz Universität Hannover) , specializing in computer vision, remote sensing, and scenario-based software engineering. His work bridges academic research with real-world applications in renewable energy, geospatial analysis, and automated code generation. Studied Computer Science (B.Sc. 2010, Diploma 2014) at the University of Mannheim Focus areas: Deep Learning, Semantic Segmentation, Remote Sensing, Formal Specifications His research integrates computer vision with remote sensing , applying techniques like transfer learning and domain adaptation to aerial/satellite imagery. Key projects include SegForestNet for segmentation and WindGISKI for wind turbine site selection. Recent publications highlight advancements in semantic segmentation, hyperspectral band optimization, and scenario-based controller synthesis. Collaborative work with Jörn Ostermann and others demonstrates interdisciplinary approaches across IEEE, Springer, and arXiv platforms. Technical contributions include the open-source SegForestNet framework, implementing binary space partitioning trees for geospatial analysis. This toolchain combines Python/Rust with PyTorch, emphasizing reproducibility and practical deployment in industrial/energy domains.

• Deep Learning
• Transfer Learning
• Semantic Segmentation
• +7 more

Miguel A. Redondo is a Full Professor at the Department of Tecnologías y Sistemas de Información, University of Castilla-La Mancha (Spain), since 2019. He holds a PhD in Computer Science and Engineering from the same university (awarded in 2002). Research Focus : eLearning, Human-Computer Interaction (HCI), Software Engineering, and eye-tracking assessment. Affiliation : Universidad de Castilla-La Mancha, Campus de Ciudad Real, Spain. His academic career centers on designing model-driven and AI-powered tools to enhance programming education. Key contributions include the GreedEx Tab system for algorithm learning and the COLLECE 2.0 collaborative programming environment. He has pioneered the integration of genetic algorithms for optimizing group learning dynamics and developed immersive systems for algorithmic thinking through augmented/virtual reality. His work spans educational technology , collaborative software , and adaptive learning frameworks . Recent publications emphasize m-learning usability (2024), machine learning in healthcare (2023), and personality-driven group organization (2021). He frequently collaborates with researchers like Ana I. Molina and Yoel Arroyo on topics such as educational data mining and visual modeling languages . While no formal student list or awards are provided in the source text, his leadership in model-driven development for CSCL tools has been cited in numerous works across IEEE, ACM, and Springer venues.

• eLearning
• Human-Computer Interaction (HCI)
• Software Engineering
• +5 more

Ludovic Apvrille is a Professor at Telecom Paris (Institut Polytechnique de Paris), where he leads research in the Communications and Electronics (Comelec) department and previously headed the LabSoC (Laboratory on System on Chip). His work focuses on embedded systems design , with particular emphasis on safety, security, and formal verification of complex systems including automotive applications, drones, and cyber-physical systems. Research Areas: Embedded Systems, Cybersecurity, Model-Driven Engineering, Formal Verification, AI-assisted Design Key Tools: TTool, SysML-Sec, AVATAR, SMASHUP, DIPLODOCUS His recent publications analyze security vulnerabilities in RISC-V architectures using the gem5 simulator, while his ongoing work explores AI integration in system modeling and unified verification techniques for hardware/software co-designs. He actively supervises research projects in safety-security-performance trade-offs and microarchitectural security , with applications to autonomous vehicles and critical infrastructure systems. Grants & Projects: EVITA project, PEPR-5G HISEC, MoVe4SPS, PEPR-Security ARSENE

• Embedded Systems Design
• Cyber-Physical Systems
• System-on-Chip (SoC) Modeling
• +7 more

Alessio Franconi is a Lecturer and researcher at the School of Design, Royal College of Art (RCA). He holds a PhD in Circular Design from the University Iuav of Venice, focusing on developing tools for managing product lifecycle complexity. His academic roles include teaching in AcrossRCA, Grand Challenge, and MDes Design Futures programs. He has conducted research at institutions like Brunel University London (UK), Technical University of Delft (NL), and Rochester Institute of Technology (US). His research interests revolve around circular design, business model innovation, and sustainable systems. He explores theoretical frameworks for circular design while addressing practical applications such as decentralized water harvesting and circular bike-sharing systems. As Agenda Manager for the Circular Design Forum, he collaborates with European businesses to advance circular economy transitions. Alessio’s work bridges academia and industry, with industrial design experience at Italian firms. He founded the Circular Design Tool (www.circulardesign.it) in 2020, a resource for designers and businesses. His publications span journals like Sustainability and conference proceedings, emphasizing circular economy strategies and design frameworks. Key collaborations include the Interdisciplinary Centre for Circular Metals (CircularMetal project) and École des Ponts Business School. His research addresses systemic challenges in transitioning to circular economies, particularly in metal sectors and fashion industries.

• Circular Design
• Circular Economy Transition
• Sustainable Systems
• +3 more

Kung-Kiu Lau is a Senior Lecturer at the School of Computer Science, University of Manchester , specializing in Component-based Software Development and Computational Logic . He leads the Component-based Software Development research group and has supervised 11 PhD students. Research Focus: Component models, algebraic service composition, logic program synthesis, and IoT systems scalability. Key Contributions: Development of tools like X-MAN and D-XMAN for compositional software design, exploration of formal methods in software engineering, and foundational work on steadfast programs. Publications span IoT service composition, component certification, reverse engineering, and formal verification. His work addresses challenges in scalability, reusability, and automated synthesis of software components. Awards: ICIOT 2018 Best Paper Award

• Component-based Software Development
• Computational Logic
• Software Engineering
• +12 more

William J. Giraldo is a researcher in the fields of human-computer interaction, model-driven engineering, and interactive systems design. He has published extensively from 2007 to 2019, collaborating with prominent researchers such as Manuel Ortega, César A. Collazos, Ana I. Molina, and Oscar Pastor. His work appears in journals like Software Quality Journal , Information Systems , and Journal of Systems and Software , as well as conferences including Interacción, CAiSE, and CRIWG. His research interests include: Human-Computer Interaction (HCI) Model-Driven Engineering (MDE) Usability and quality in software modeling Interactive and groupware system design Educational technology and e-learning interfaces User interface development frameworks His recent publications focus on evaluating modeling language quality, integrating technical debt into MDE, participatory design for educational systems, and creating frameworks for UI development—especially for older adults and video-based systems. The articles show a consistent trend toward improving software quality, usability, and accessibility through model-based approaches. While no scientific awards are listed in the provided text, his collaborative work indicates strong integration within academic research networks in software engineering and HCI. He has contributed to advising and research teams, particularly in projects involving model-driven development of groupware and educational systems. His work often involves empirical studies and tool development, suggesting active engagement in both theoretical and applied research. William J. Giraldo has been involved in the development of frameworks such as the Activity Taxonomy (ATx) and tools for Android code generation from conceptual models, indicating a focus on practical, implementable solutions in software engineering and HCI.

• Human-Computer Interaction
• Model-Driven Engineering
• Interactive Systems Design
• +7 more

Dr. Eugene Syriani is a Professor at the Department of Computer Science and Operations Research , Faculty of Arts and Sciences , University of Montreal . He leads the GEODES research group and teaches software engineering at undergraduate, Master's, and PhD levels. His work combines Model-Driven Engineering (MDE) and Simulation to improve software engineer productivity and cross-disciplinary system design. Research interests span two axes: (1) Software Engineering focusing on Domain-Specific Languages (DSLs) , Model Transformations , Code Generation , Collaborative Modeling , and Customizable Modeling Environments ; (2) Simulation addressing Digital Twins , Discrete-Event Simulation , and Co-Simulation for applications in agriculture, automotive, and smart systems. His recent work explores AI-assisted modeling and prompt engineering . Key projects include Digital Twins for Vertical Farming (funded by NSERC, MITACS, and industry partners) and Domain-Specific Environments (NSERC Discovery Grant). He has received multiple best paper awards at international MDE and modeling conferences. Scientific contributions include: Best Paper, ACM/IEEE International Conference on Model Driven Engineering Languages & Systems (2023, 2018) NSERC Discovery Grant (2020-2027) Visiting Professor Fellowships (University of L'Aquila, TU Wien, University Cote d'Azur) Guest Editor for Software & Systems Modeling and JOT He supervises 13 graduate students and postdocs, with expertise in DSL development , collaborative modeling , digital twin frameworks , and model consistency . His tools include Gentleman (projectional editor), ReLiS (systematic review tool), and AToMPM (cloud-based modeling environment).

• Software Engineering
• Model-Driven Engineering
• Digital Twins
• +5 more

Dr. Sergio Espana Cubillo is an Assistant Professor at Utrecht University within the Software Production research group. His work focuses on Requirements Engineering , Conceptual Modeling , and Software for Organizational Responsibility . He leads the Show your Heart project for sustainability reporting and contributes to SCENTISS (2023-2027) to support social entrepreneurship.

• Software Engineering
• Requirements Engineering
• Conceptual Modeling
• +7 more

Nelly Bencomo is an Associate Professor in the Department of Computer Science at Durham University in the UK, where she joined in September 2021. Previously, she was a Senior Lecturer at Aston University and has held research positions at Lancaster University and INRIA Paris. She is a leading researcher in software engineering for autonomous and self-adaptive systems, with a focus on uncertainty quantification and decision-making under uncertainty. Her research interests span Decision-making under Uncertainty, Software Engineering for Autonomous and Self-adaptive Systems, Bayesian Inference and Machine Learning, Requirements Engineering, Model-Driven Engineering, and runtime models. She has pioneered concepts like models@run.time and requirements@run.time, exploring how systems can maintain awareness of their requirements and models during operation. Her work increasingly addresses AI ethics, human values in software, and responsible AI. Her recent publications (2021-2025) reveal a strong focus on uncertainty representation and management in adaptive systems, with growing attention to explainability, digital twins, and LLM applications in software engineering. Her work bridges theoretical foundations with practical applications in healthcare, education, and sustainable systems. Best Paper Award at International Conference on Engineering Digital Twins 2024 (EDTconf'24) Best Software Artefact at Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS'24) Listed in Women for Innovation in Health Science in the North of England 10-year Most Influential Paper Awards 2019 for seminal work in self-adaptive systems Best Paper Award REFSQ 2013 Nelly has successfully supervised multiple PhD students to completion and currently mentors several postgraduate researchers. She leads the EPSRC-funded Twenty20Insight project and the Leverhulme Fellowship QuantUn, focusing on uncertainty quantification using Bayesian surprises. Her research portfolio includes significant contributions to European projects and UK research councils in the area of self-adaptive and autonomous systems. She is also involved in the Leverhulme Centre for Algorithmic Life as Project Lead in the Department of Computer Science and leads the Durham Strategic Research Fund project JusTN0W.

• Software Engineering
• Requirements Engineering
• Decision-making under Uncertainty
• +7 more

Esther Guerra is a Full Professor in the Department of Computer Science at the School of Engineering, Autonomous University of Madrid. She joined the university in 2010 after previously serving as a professor at the Universidad Carlos III de Madrid from 2004 to 2010. Her academic career spans over two decades with consistent contributions to software engineering research and education. Dr. Guerra's research focuses on Model-Driven Engineering (MDE), Domain-Specific Languages, and software testing. She has made significant contributions to language engineering, particularly in language product lines, metamorphic testing, and the development of tools for model-based engineering. Her work bridges theoretical foundations with practical applications, especially in chatbot development, low-code platforms, and augmented reality systems. She leads the MISo research group which actively develops tools like Merlin, MetaDepth, and Wodel-Test. Her publication record shows a consistent trajectory of high-impact research, with recent work focusing on adaptive modeling languages, chatbot engineering, and test amplification frameworks. She has published in top-tier journals including ACM Transactions on Software Engineering and Methodology, Journal of Systems & Software, and Software and Systems Modeling. As an educator, Dr. Guerra has taught numerous courses including Software Analysis and Design Project, Automated Software Development, and Model-Driven Software Development. She has supervised numerous undergraduate and master's theses focused on practical applications of model-driven techniques. Dr. Guerra is actively involved in the academic community, serving on program committees for major conferences including ASE, MODELS, ICSE, and SPLASH. She has contributed to the organization of several workshops and symposia focused on software engineering topics.

• Model-Driven Engineering
• Software Engineering
• Domain-Specific Languages
• +7 more