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Gregory VialView profile

Associate Professor

• Digital Transformation
• Data Governance
• Artificial Intelligence
• +4 more

Gregory Vial is an Associate Professor in the Department of Information Technology at HEC Montréal. He holds a Ph. D. in Administration and an M. Sc. in Information Technology from HEC Montréal, alongside a Bachelor of Commerce from McGill University. Education: Ph. D. in Administration, HEC Montréal M. Sc. in Information Technology, HEC Montréal Bachelor of Commerce, McGill University Research Interests: Vial’s work focuses on digital transformation, data governance, artificial intelligence project management, software reuse, and data privacy. He explores how organizations navigate challenges in adopting AI, managing data湖 governance in digital innovation, and balancing privacy with utility in data release strategies. His research also emphasizes the application of complex adaptive systems theory to software development and the ethical implications of technology adoption. Articles Trends: Recent publications highlight interdisciplinary approaches to data privacy, AI implementation barriers, and post-agile methodologies. He frequently collaborates with industry partners like Banque Nationale du Canada and Desjardins, addressing real-world challenges in data management and technology integration. Awards: No scientific awards explicitly mentioned in the text. Advising & Grants: Vial has supervised 3 Master’s theses and 33 directed projects, often co-supervised with colleagues like Ann-Frances Cameron and Jean-François Plante. His projects span industries including finance, healthcare, and e-commerce, focusing on data湖 quality, cloud infrastructure, and user experience optimization. While grants are not detailed, his research aligns with translational goals, bridging academic insights and practitioner needs. Labs/Teams: Collaborates with multidisciplinary teams on AI consulting firm case studies and data governance projects, though specific lab affiliations are not mentioned.

• Software Engineering
• Software Testing
• Software Design
• +3 more

Benoit Baudry is a Full Professor of Computer Science at the University of Montreal's Faculty of Arts and Sciences, Department of Computer Science and Operations Research. He leads the GEODES research group (Groupe de recherche sur les systèmes ouverts et distribués et l’expérimentation dans les logiciels), focusing on software engineering challenges. His teaching responsibilities include courses like Software Quality Metrics (IFT-3913), Software Project Management (IFT-3150), and Advanced Topics in Software Engineering (IFT-6251). He is actively involved in strategic initiatives like IVADO and MITACS-funded projects. Research interests span software supply chain security, dependency management, automated software engineering, and AI-driven development tools. He leads projects such as 'Safe and Transparent Software Reuse' (2025–2031) funded by NSERC and 'CLIMB: LLM-driven MLOps Interface' (2025) supported by MITACS. His work addresses critical issues like detecting bloated dependencies, ensuring reproducible builds, and mitigating supply chain vulnerabilities. Recent funding includes NSERC Discovery Grants and Apogée Canada operational funds. He has pioneered techniques for generating mocks from production data, automating test generation via runtime analysis, and applying large language models to software repair. His interdisciplinary projects bridge software engineering with digital art, such as algorithmic art generation systems. He advises multiple graduate programs including Computer Science Bachelors, Masters, and PhD tracks. Key collaborations include KTH Royal Institute of Technology and industry partnerships like Co-operators. His research emphasizes practical solutions for real-world software systems' reliability and security.

Serdar YukselView profile

Professor

• Stochastic Control Theory
• Information Theory
• Probability Theory
• +5 more

Serdar Yuksel is a Professor in the Department of Mathematics and Statistics at Queen's University, Canada, affiliated with the Faculty of Arts and Science. He holds a Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign (UIUC), and B.Sc. from Bilkent University. His research focuses on stochastic control theory, information theory, probability theory, and their applications in decentralized systems, networked control, and reinforcement learning. Yuksel's work bridges control, information, and probability, addressing challenges in stochastic stability, optimal control under partial/decentralized information, and ergodic properties of dynamical systems. Education: Ph.D. (2006) - Electrical and Computer Engineering - UIUC M.Sc. (2003) - Electrical and Computer Engineering - UIUC B.Sc. (2001) - Electrical and Electronics Engineering - Bilkent University Research Interests: Stochastic control theory, including optimization and stability of Markovian systems Information theory, particularly zero-delay coding and systems with feedback Probability theory, focusing on Markov processes and ergodic theory Decentralized and networked control systems under information constraints Reinforcement learning and approximation methods for stochastic systems Awards: 2013 CAIMS/PIMS Early Career Award in applied mathematics Teaching and Academic Leadership: Yuksel has taught courses such as Optimization and Control of Stochastic Systems, Mathematics of Engineering Systems, and served as Chair of Mathematics & Engineering at Queen's University. He advises numerous graduate and undergraduate students, mentoring projects in control theory, optimization, and applied mathematics. Labs/Teams: Leads the Stochastic Control (and Related Fields) research group, collaborating on topics like decentralized control, information structures, and mean-field games. Active in organizing seminars and international collaborations.

Stephen ThomasView profile

Assistant Professor

• Natural Language Processing
• Machine Learning
• Big Data
• +4 more

Stephen W. Thomas is an Assistant Professor & Distinguished Teaching Fellow of Management Analytics at the Smith School of Business, Queen’s University. He holds a PhD in Computer Science from Queen’s University and has expertise in Natural Language Processing (NLP), machine learning, and data analytics. His research focuses on practical and fair AI applications, including bias detection and ethical considerations in NLP models. He has held roles as Executive Director of Smith's Analytics & AI Ecosystem and directs the Master of Management Analytics and Master of Management in Artificial Intelligence programs. His work bridges academia and industry, with consulting experience in big data and AI. Education: PhD (Computer Science, Queen’s University 2012), M.S. (Computer Science, University of Arizona 2009), B.S. (Computer Science, New Mexico State University 2006). Research Interests: NLP applications in messy real-world data, fair AI, AutoML for NLP, temporal databases, and mining software repositories. He has published in IEEE Transactions journals and led initiatives like τBench for temporal benchmarking. Awards: Scotiabank Scholar, multiple Professor of the Year awards, Queen’s Graduate Award Scholarship, and Raytheon Advanced Scholarship Program recipient. He has advised over 15 students in analytics and AI projects. Teaching: Courses include Machine Learning & AI, Text Analytics, Big Data, and Mathematical Analysis across Smith’s programs. He is a frequent speaker on AI ethics and management applications.

Ying ZouView profile

Professor

• Software Engineering
• Software Maintenance and Evolution
• Empirical Studies
• +7 more

Dr. Ying Zou is a Professor and Canada Research Chair (Tier II) in Software Evolution at Queen’s University’s Department of Electrical and Computer Engineering, with a cross-appointment to the School of Computing. She is a Visiting Faculty Fellow at IBM Centers for Advanced Studies (CAS) and a member of IEEE. Her research focuses on software engineering, maintenance, empirical studies, and service-oriented computing, with notable contributions to refactoring patterns, performance analysis, and developer tooling. Education: BEng from Beijing Polytechnic University (China), MEng from Chinese Academy of Space Technology (China), and PhD from the University of Waterloo (Canada). Research interests include software evolution dynamics, code clone analysis, and optimizing developer workflows. Notable achievements include the 2014 IBM CAS Research Faculty Fellow of the Year and two IBM Faculty Awards (2007, 2008). Her work bridges empirical software engineering with practical industrial applications. Awards: Canada Research Chair, IBM Faculty Awards, IBM CAS Fellow Grants: IBM CAS collaborations, cross-disciplinary research funding Labs/Teams: Active contributor to the Software Evolution and Analysis Lab (SEAL), focusing on empirical studies and tool development for software maintenance challenges.

• Software Engineering
• Data Analytics
• Mining Software Repositories
• +5 more

**Ahmed Hassan** is a **Professor** and **Canada Research Chair (Tier 2) in Software Analytics** at the **School of Computing**, **Queen's University**, affiliated with the **Faculty of Arts and Science**. He holds the **NSERC/RIM Industrial Research Chair in Software Engineering for Ultra Large Scale Systems**. His research focuses on software systems, data analytics, and mining software repositories (MSR), leading the **Software Analysis and Intelligence Lab (SAIL)**. **Education**: PhD (2005), MMath (2001), BMath (1999) in Computer Science from the University of Waterloo, Canada. **Research Interests**: Software evolution, performance engineering, distributed systems debugging, cybersecurity, and AI-driven software solutions. SAIL explores tools for maintaining large-scale software systems, improving developer productivity, and integrating AI into software workflows. **Awards & Recognition**: ACM and IEEE Fellowships, patents in multiple jurisdictions, and leadership roles in MSR and ICSE conferences. Industrial experience includes RIM/BlackBerry, IBM Research, and Nortel Networks. **Current Projects**: Focus on foundation model-powered software (FMware), AIOps, and ethical AI applications. Teaching courses like CISC322: Software Architecture.

Michael GodfreyView profile

Professor

• Software Engineering
• Software Evolution
• Empirical Studies
• +5 more

Michael Godfrey is a Professor at the University of Waterloo's David R. Cheriton School of Computer Science, affiliated with the Department of Electrical and Computer Engineering. His work focuses on software engineering, empirical studies of software systems, code review practices, and open-source software ecosystems. He holds a Ph.D., M.Sc., and B.Sc. from the University of Toronto (1997, 1988, 1986). Research interests include software evolution, mining software repositories, provenance tracking, code duplication analysis, and program comprehension. He actively explores how developers interact with code reviews, documentation systems, and modern CI/CD pipelines. Recent work investigates app store software ecosystems, Bash scripting vulnerabilities, and deep learning API testing. Publications span empirical studies of developer communities (e.g., Stack Overflow analysis), architectural teaching methods, and automated testing techniques like documentation-guided fuzzing. His work bridges theory and practice, addressing challenges in large-scale systems maintenance and developer productivity. Leverages tools like Elasticsearch for repository mining and explores anomaly detection in software development. Engaged in curriculum development for software architecture education and has contributed to conferences like MSR and ICSE.

Meiyappan NagappanView profile

Associate Professor

• Empirical Software Engineering
• Mining Software Repositories
• Software Security
• +3 more

Academic Profile Dr. Meiyappan (Mei) Nagappan is an Associate Professor at the University of Waterloo's Cheriton School of Computer Science. He holds a Ph.D. (2011) and M.Sc. (2008) from North Carolina State University, and a B.Sc. from Anna University, India (2006). Research Focus His research spans empirical software engineering, mining software repositories, and mobile app store analysis. Current investigations focus on software security, static analysis techniques, and diversity in software engineering. Recent work critically examines AI programming assistants like GitHub Copilot, evaluating their performance, security implications, and impact on developer workflows. Key Research Areas Diversity analysis in open-source contributions and academic publishing Vulnerability detection using machine learning Bug localization and automated debugging Cross-platform app analysis Publications Research demonstrates strong focus on empirical validation of developer tools, with recent emphasis on AI-assisted programming. Work appears in top software engineering venues covering security, testing, and developer productivity.

Shane McIntoshView profile

Associate Professor

• Empirical Software Engineering
• Software Delivery
• Release Engineering
• +2 more

Shane McIntosh is an Associate Professor and Associate Director of Graduate Studies at the Cheriton School of Computer Science, University of Waterloo. He holds a Ph.D. from Queen's University (2015) and specializes in empirical software engineering, software delivery processes, and software quality improvement through data mining techniques. His research focuses on analyzing historical and operational data from large-scale software systems to derive actionable insights. Key areas include release engineering, DevOps optimization, and software quality enhancement. McIntosh employs empirical methods to study build systems, continuous integration practices, and defect prediction. McIntosh's recent publications demonstrate a strong focus on improving software development workflows through empirical analysis of build systems, CI/CD pipelines, and code quality metrics. His work frequently addresses efficiency optimization in development operations and vulnerability detection in machine learning systems.

Colin GoldblattView profile

Associate Professor

• Atmospheric Science
• Planetary Science
• Astrobiology
• +5 more

Colin Goldblatt is an Associate Professor at the University of Victoria’s School of Earth and Ocean Sciences, cross-listed in the Department of Physics and Astronomy. His research focuses on atmospheric evolution, planetary science, and astrobiology, particularly investigating Earth’s climate history and exoplanetary habitability. Education: BSc in Meteorology and Oceanography from the University of East Anglia, followed by a PhD in Environmental Sciences (UEA). He held a NASA Postdoctoral Program Fellowship at NASA Ames Research Center and was a Research Associate in the Virtual Planetary Laboratory at the University of Washington. Research interests include the Great Oxidation Event, nitrogen budget dynamics, the Faint Young Sun paradox, and climate modeling for exoplanets. His work employs tools like radiative transfer codes and biogeochemical models (e.g., EONS). Awards include the NASA Postdoctoral Program Fellowship. He advises graduate students in paleoclimate and planetary atmospheres and collaborates on initiatives like the High-altitude Aerosols mission and Project Blue (exoplanet imaging). Labs/teams: Active in the Virtual Planetary Laboratory and the UVic Victoria Schools Weather Network. His research emphasizes interdisciplinary approaches to Earth system science and astrobiology.

Falk HerwigView profile

Professor

• Stellar Hydrodynamics
• Nuclear Astrophysics
• Stellar Evolution
• +3 more

Falk Herwig is a Professor and Director of the Astrophysical Research Center (ARC) at the University of Victoria's Department of Physics and Astronomy. His research focuses on stellar hydrodynamics, nucleosynthesis, and the origin of elements. He leads the Computational Stellar Astrophysics (CSA) group, which conducts large-scale 3D hydrodynamics simulations of stellar convection and nucleosynthesis processes. The CSA group collaborates with the NSF Physics Frontier Center Joint Institute for Nuclear Astrophysics (JINA-CEE) and the NuGrid collaboration, leveraging high-performance computing resources like the Niagara supercomputer. Herwig's work includes studying convection-nuclear burning interactions in massive and binary stars, nucleosynthesis in diverse astrophysical environments, and the chemical evolution of galaxies. He has pioneered methods to model stellar yields and integrate computational models with observational data. His research spans topics from core convection in massive stars to the physics of merging white dwarfs and nova explosions. Herwig has contributed significantly to advancing computational infrastructure for astrophysics, including the development of tools like SYGMA for galactic chemical evolution modeling. His projects are supported by Compute Canada and involve collaborations with international institutions. Recent research highlights include investigating the role of neutron capture processes in element formation and refining models of white dwarf cooling and stellar evolution.

Wei WangView profile

Assistant Professor

• Leadership
• Business Ethics
• Organizational Behavior
• +3 more

Wei Wang is an Assistant Professor and The Associates Fellow in Leadership and Ethics at the Business Administration Department, Asper School of Business, University of Manitoba. His research focuses on leadership dynamics and ethics in the workplace, employing mixed-method approaches. He has been recognized with the 2019 Society of Business Ethics Emerging Scholar Award and the 2022 Anne Tsui Dare to Care Research Award for impactful work on employee well-being. His teaching expertise spans organizational behavior, negotiation, and business ethics. He leads the GLOW Lab, advancing research in leadership and ethical workplace practices. Key research interests include ethical leadership, workplace mistreatment, and the behavioral consequences of deviant coworker behaviors. His work has been published in leading journals such as Journal of Applied Psychology and Journal of Management . Beyond academia, he enjoys outdoor activities, running, and travel. Awards include the 2019 Emerging Scholar Award for contributions to business ethics and the 2022 Dare to Care Award for research prioritizing employee welfare. His lab, the GLOW Lab, drives innovative studies in leadership and ethical organizational practices.

Susan BrownView profile

Professor

• Digital Humanities
• Victorian Literature
• Feminist Theory
• +3 more

Susan Brown is a Professor at the University of Guelph, holding a Canada Research Chair (Tier 1) in Collaborative Digital Scholarship. She is affiliated with the College of Arts and the School of Theatre, English, and Creative Writing. Her research focuses on digital humanities, critical infrastructure studies, Victorian literature, and feminist theory, particularly through her leadership of the Orlando Project, a pioneering interdisciplinary initiative. She has received significant grants from the Social Sciences and Humanities Research Council of Canada and the Canadian Foundation for Innovation. Her work bridges feminist literary history with digital innovation, emphasizing collaborative knowledge production and inclusive digital infrastructure. Brown has contributed to university administration, including roles on the Senate Awards Committee, Board of Governors, and editorial boards of journals like Victorian Review and KULA . She has also served on national and international advisory boards, including Compute Canada and the Digital Research Alliance of Canada. Research interests include feminist digital methodologies, semantic technologies, and the intersection of technology with literary studies. Awards include the Society for Digital Humanities Outstanding Achievement Award (2006) and the T-REX Best New Tool Prize (2008). She has taught extensively in Victorian studies, gender theory, and digital humanities, receiving a teaching award in 1999 for integrating digital methods. Brown founded the DH@Guelph Summer Workshops and co-created the Culture and Technology Studies program. Grants and projects include funding for the Humanities Interdisciplinary Collaboration Lab (THINC Lab) and the Canadian Writing Research Collaboratory (CWRC). Her recent work explores metadata ontologies, linked open data, and the ethical dimensions of digital cultural heritage.

Lai-Tze FanView profile

Associate Professor

• Science and Technology Studies
• AI Ethics
• Critical Design
• +5 more

Lai-Tze Fan is an Associate Professor of Technology & Social Change at the University of Waterloo, Canada, cross-appointed between the Department of Sociology & Legal Studies and the Department of English Language and Literature. She holds a Canada Research Chair in Technology and Social Change (Tier 2 SSHRC) and directs The U&AI Lab, which focuses on AI ethics and research-creation methods for equity, diversity, and inclusion (EDI). Additionally, she serves as a visiting Associate Professor II (part-time) at the University of Bergen, Norway, and holds editorial roles at electronic book review and the digital review . Her interdisciplinary work spans Media Studies, Science and Technology Studies, Critical Design, and Digital Humanities, with a focus on AI ethics, gendered design, and digital narratives. She has held academic positions at Lingnan University (Hong Kong), Concordia University (Montréal), and the University of Mainz (Germany). Her research includes projects like the Global Urban Wilds locative media app, exploring environmental storytelling and urban ecology, and the Decameron 2.0 Virtual Gallery , addressing pandemic-era community making. Fan’s awards include the N. Katherine Hayles Award for Criticism and SSHRC grants. Her recent publications address AI equity, gendered technology design, and digital environmental narratives. She actively mentors students in areas like AI ethics, critical design, and electronic literature.

Ivan BeschastnikhView profile

Associate Professor

• Distributed Systems
• Software Engineering
• Cloud Computing
• +5 more

Ivan Beschastnikh is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Faculty of Science. He leads research in distributed systems, software engineering, and formal methods, with a focus on privacy-preserving technologies, blockchain systems, and machine learning. His work bridges theoretical foundations and practical system implementations, emphasizing empirical validation and real-world deployment. Research Interests: His primary areas include distributed systems (e.g., consensus algorithms, transaction processing), formal methods for system correctness (e.g., PGo compiler for verified implementations), and privacy in federated learning and blockchain. He also explores interdisciplinary topics like AI ethics, human-computer interaction for developers, and system security. Key Projects: Includes PGo (formal specification to Go compiler), Biscotti (decentralized federated learning), Erlay (Bitcoin transaction relay optimization), and Teleoscope (text corpus analysis tool). His work has practical impact in blockchain scalability, secure multi-party ML, and distributed system validation. Awards: Recognized with the ASPLOS Distinguished Artifact Award, UBC Faculty Teaching Award, and ESEM Best Paper Award. His contributions span academic excellence, pedagogy, and collaborative research. Lab Affiliations: Active in the Systopia Lab and Software Practices Lab (SPL) , and collaborates with UBC’s Data Science Institute and Blockchain@UBC. He emphasizes interdisciplinary research, mentoring students in both theoretical and applied systems work.