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Joey PaquetView profile

Associate Professor

• Design and implementation of programming languages
• Context-driven computing
• Demand-driven computing

Dr. Joey Paquet is a Tenured Associate Professor and Department Chair in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. He holds a PhD and specializes in research areas including Design and Implementation of Programming Languages, Context-Driven Computing, and Demand-Driven Computing. His work focuses on advancing programming paradigms and their applications in cybersecurity, distributed systems, and autonomic computing. Dr. Paquet is actively involved in thesis supervision across Computer Science and Software Engineering programs at both master's and doctoral levels. Research interests are centered around programming language design, particularly in demand-driven and context-aware systems. His contributions include frameworks like GIPSY and OpenISS, enabling scalable data processing and forensic computing. Recent work explores autonomic intent-driven networking, real-time gesture recognition, and IoT forensics. These efforts highlight his expertise in both theoretical constructs and practical implementations. His advising role supports students in MCompSc, MASc, and PhD programs. While specific grants are not detailed, his projects often involve interdisciplinary collaboration. Dr. Paquet is affiliated with platforms like LinkedIn and ResearchGate, reflecting an active academic presence. Key technical contributions include pioneering work on forensic computing backends, intent expression languages, and multimodal interaction systems. His research addresses challenges in cybersecurity, distributed systems, and service composition, with a focus on resilience and scalability.

Xujie SiView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Software Engineering
• +5 more

Xujie Si is an Assistant Professor in the Department of Computer Science at the University of Toronto. He is also a faculty affiliate at the Vector Institute and an affiliate member at Mila - Quebec AI Institute, holding a Canada CIFAR AI Chair. Previously, he served as an Assistant Professor at McGill University's School of Computer Science. Education: Ph.D., Computer and Information Science, University of Pennsylvania (advised by Mayur Naik) M.S., Computer Science, Vanderbilt University B.E. (with Honors), Nankai University Research Focus: His work bridges AI and program reasoning, emphasizing the integration of statistical and logical methods. Key areas include: Static analysis and verification using deep learning/reinforcement learning Neuro-symbolic systems for urban simulation (e.g., LogiCity) Automated theorem proving via LLMs and symbolic reasoning Program repair and compiler fuzzing Recent Article Trends: Recent work focuses on synergizing LLMs with symbolic reasoning (e.g., Olympiad inequality proving), advancing SAT solving with graph neural networks, and applying neuro-symbolic methods to Euclidean geometry formalization. Awards: Canada CIFAR AI Chair (2023) Lab/Teams: Leads research teams exploring program analysis, neuro-symbolic AI, and formal verification at the University of Toronto and Vector Institute.

• Welding Metallurgy
• Physical Metallurgy
• Additive Manufacturing
• +10 more

Leijun Li, PhD, P.Eng., is a Professor in the Department of Chemical and Materials Engineering at the University of Alberta, where he also serves as Chair. With a career spanning institutions including Rensselaer Polytechnic Institute, University of Northern Iowa, and Utah State University, he specializes in physical metallurgy , welding metallurgy , and additive manufacturing . His research focuses on microstructure characterization, mechanical properties, and modeling of non-equilibrium phase transformations during welding and AM processes. Current affiliations: University of Alberta, American Welding Society, ASM International Research themes: Additive manufacturing of alloys, Corrosion science, Pipeline metallurgy, Phase transformations, Welding robotics He has received multiple AWS Hobart Awards (4 times) and Savage Awards (2 times) for his work on pipeline welding and metallurgy. His group has published extensively on topics including delta-ferrite retention in Grade 91 steel, inverse bainite transformations , and welding defect analysis . Recent projects include NSERC Alliance Missions Grant for rare earth mineral recovery and Alberta Innovates Ecosystem Program for advanced manufacturing. Key collaborators: Dr. Tom Lienert, Dr. Xiaoying Fang, Dr. P-Q Xu Labs: Rooms 2-158/3-133 (CME Building), Office 12th Floor DICE Building

Meng XuView profile

Assistant Professor

• System Security
• Software Security
• Automated Program Analysis
• +4 more

Meng Xu is an Assistant Professor in the Cheriton School of Computer Science at the University of Waterloo, Canada. He is affiliated with the Cryptography, Security, and Privacy (CrySP) group and the Cybersecurity and Privacy Institute (CPI). His research focuses on system and software security, emphasizing secure-by-design languages (e.g., Rust, Move), automated program analysis, and runtime defense techniques. Education : Ph.D., Computer Science (2020), Georgia Institute of Technology B.Eng. and B.Business (First Class Honors), Nanyang Technological University (2014) Research Interests : Secure-by-design languages Automated security analysis (fuzzing, symbolic execution) Runtime defense mechanisms (moving target defense, secure hardware) Key Awards : EAPLS Best Paper Award (2022) USENIX Security Distinguished Paper Award (2018) Grants & Funding : BlackBerry Research Grant (CAD $200,000) Amazon Research Award (USD $60,000) NSERC Discovery Grant (CAD $170,000) Labs & Collaborations : CrySP (Cryptography, Security, and Privacy Group) Cybersecurity and Privacy Institute (CPI)

Tushar SharmaView profile

Assistant Professor

• Software Engineering
• Software Quality
• Code and Design Quality
• +10 more

Tushar Sharma is an Assistant Professor in the Faculty of Computer Science at Dalhousie University, Canada. His research focuses on software engineering, particularly software quality, refactoring, technical debt, and the application of machine learning in software engineering (ML4SE). He leads the SMART Lab and is actively involved in projects related to Green AI and sustainable software development. PhD : Software Engineering, Athens University of Economics and Business, Greece (2019) MS : Computer Science, Indian Institute of Technology-Madras, India His research interests span software design and architecture, code and design quality, refactoring, technical debt, mining software repositories, and applied machine learning for software engineering. He is particularly interested in sustainable AI, green software engineering, and the use of large language models for code. His work bridges empirical studies with practical tool development to improve software maintainability and quality. His recent publications highlight a strong trend in code smell detection, refactoring automation, energy-aware AI, and the reliability of large language models in software engineering. He has developed tools like Designite and DPy and contributed datasets such as MaRV and DACOS, emphasizing empirical validation and reproducibility in software engineering research. Dean's Research Excellence Award Best Artifact Award, SCAM 2023 IEEE Senior Member Tushar Sharma has secured significant research funding, including an NSERC Discovery Grant for DevQOps, Mitacs Accelerate grants with industry partners, and contributions to the $154M Canada First Research Excellence Fund project. He actively mentors students and collaborates with industry. He leads the SMART Lab at Dalhousie and has organized workshops such as SATToSE 2018. He is also a founding developer of Designite, a widely used software design quality assessment tool.

• Trustworthy AI
• Software Testing & Verification
• Requirements Engineering
• +5 more

Prof. Lionel C. Briand is a leading academic in software engineering and trustworthy AI, holding appointments at the University of Ottawa (EECS Department, Nanda Laboratory) and the University of Limerick (Lero - National Software Research Centre). He serves as Director of Lero and Scientific Director of the SnT software verification lab in Luxembourg. His research focuses on software testing, model-driven engineering, AI-driven quality assurance, and regulatory compliance. He has held the Canada Research Chair (Tier 1) since 2003 and led major institutions like Simula Research Laboratory (Norway) and Fraunhofer Institute (Germany). Education & Career: Full Professor at Carleton University (2008–2012) Head of Software Quality Engineering at Fraunhofer IESE (2000–2008) Research Scientist at NASA Software Engineering Lab (1990s) Research Interests: His work spans secure AI systems, automated legal compliance (e.g., GDPR), metamorphic testing, search-based software engineering, and safety-critical systems. He emphasizes practical applications, collaborating with industry partners globally. Awards & Recognition: IEEE Fellow (2010), ACM Fellow (2020) Harlan Mills Award (2012), ERC Advanced Grant (2016) Fellowships from Royal Society of Canada (2023) and Academia Europaea (2025) Grants & Labs: PEARL grant from Luxembourg FNR for SnT lab ERC Advanced Grant for software testing research Leadership roles in Lero and Nanda Lab Publications: Over 500+ papers on testing methodologies, AI ethics, and regulatory compliance. Notable tools include CompAI (GDPR compliance) and Teasma (DNN test adequacy).

W Robert J FunnellView profile

Associate Professor

• Middle-ear mechanics
• Biomedical Modelling
• Finite Element Modeling
• +6 more

W Robert J Funnell serves as Associate Professor at McGill University with dual appointments in the Department of Biomedical Engineering and Department of Otolaryngology – Head and Neck Surgery. His research addresses critical clinical challenges in hearing loss through integrated experimental and computational methodologies, focusing on translational applications for infant diagnostics and surgical interventions. His expertise spans middle-ear mechanics, three-dimensional modeling of biological structures, and development of interactive medical education tools. Core methodologies include finite-element analysis, laser Doppler vibrometry, and haptic-enabled virtual reality systems. Current priorities involve improving newborn hearing screening accuracy, designing middle-ear repair techniques, and creating 3D anatomical models for surgical training – particularly in endoscopy simulation using force feedback technology. Analysis of his 2015-2024 publications reveals persistent innovation in finite-element modeling of auditory systems, with increasing emphasis on newborn ear mechanics and optical coherence tomography applications. His work bridges biomedical engineering, otolaryngology, and medical education, demonstrating consistent progression from fundamental biomechanics toward clinical implementation – notably in Quebec's newborn hearing screening programs and endoscopic sinus surgery training models.

Peter BodorikView profile

Professor

• Blockchain Technology
• Smart Contract Development
• Business Process Model and Notation (BPMN)
• +7 more

Peter Bodorik is a Professor in the Faculty of Computer Science at Dalhousie University, where he conducts cutting-edge research in blockchain technology, smart contract automation, and distributed systems. He is affiliated with the Blockchain Lab and leads research in systems, focusing on transforming business processes into secure and scalable blockchain applications. PhD in Computer Science – Carleton University (1985) MEng in Computer Systems – Carleton University (1977) BSc in Computer Science – University of Calgary (1974) His research interests lie at the intersection of blockchain, business process modeling (BPMN), and automated software generation. He specializes in creating frameworks that transform BPMN models into smart contracts using multi-modal modeling (DE-HSM and FSM), enabling privacy, scalability, and interoperability in distributed applications. His work supports long-term collaborative transactions and off-chain computation to enhance performance and reduce costs. His recent publications (2021–2025) demonstrate a consistent focus on automating smart contract development, improving transaction management, and enabling enterprise adoption of blockchain. Key themes include BPMN-to-smart-contract transformation, sidechain integration, privacy-preserving execution, and model-driven engineering for blockchain systems. System and Methods for Automated Generation of Smart Contracts from BPMN Models Using DE-HSM Multi-modal Models (USPTO Patent Application 17968047) System and method for tracking of provenance and flows of goods, services, and payments in responsible supply chains (US Patent US-11461775-B2) Apparatus, system, and methods for a blockchain identity translator (US and Canada patents) System and Methods for Tracking of Provenance and Flows of Goods in Responsible Supply Chains (Canada Patent 3,073,459) Peter Bodorik has supervised over 80 graduate students and has published more than 100 peer-reviewed papers. He has held key academic leadership roles including Associate Dean (Academic), Acting Associate Dean (Research), and Director of the Master of Electronic Commerce program. He is actively involved in research funding, student mentorship, and advancing blockchain technology through both academic and industrial collaboration. He leads the Blockchain Lab at Dalhousie University, fostering innovation in secure and scalable distributed systems.

Jinqiu YangView profile

Associate Professor

• Software Engineering
• Automated Program Repair
• Software Testing
• +4 more

Jinqiu Yang is an Associate Professor in the Department of Computer Science and Software Engineering at Concordia University. His research focuses on software reliability, automated program repair, software testing, and quality assurance of machine learning systems, particularly in autonomous vehicles. He holds a PhD and MASc from the University of Waterloo and a B.Eng. from Nanjing University. Yang has been a tenure-track faculty member at Concordia since 2018, following research roles at IBM Watson and IBM CAS. Research Interests: Automated Program Repair Software Testing Machine Learning Systems Text Analytics of Software Artifacts Mining Software Repositories Autonomous Systems Quality Assurance Key Contributions: His recent work includes detecting concept drifts in ML systems (ICSE-25) and investigating social bias in LLM-generated code (AAAI-25). He leads the O-RISA Lab and has authored over 50 peer-reviewed publications, including distinguished papers at MSR-2018. Yang currently holds grants such as the NOVA FRQNT-NSERC Program (2024-2027) and the NSERC Discovery Grant (2019-2025). Service & Awards: Editorial Board Member of the Empirical Software Engineering Journal (EMSE) and active PC member in top venues like ICSE and FSE. Recipient of the IBM CAS Fellowship and ACM SIGSOFT Distinguished Paper Award. Teaching & Students: He mentors students in Master's and PhD programs, with funding available. His lab focuses on cutting-edge topics like secure code generation and autonomous vehicle reliability.

Jialu ZhangView profile

Assistant Professor

• AI for Programming
• LLM-Powered Software Development
• Automated Debugging
• +4 more

Jialu Zhang is a Tenure-Track Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. Her research focuses on AI-driven solutions for programming challenges, including LLM-powered software development, automated debugging, and program repair. She holds a PhD in Computer Science from Yale University (2023) and a BS in Electrical and Computer Engineering from Shanghai Jiao Tong University (2017, IEEE Honor Class). Her work emphasizes practical applications like Gmerge (merge conflict resolution), PyDex (automated code repair), and Clef (AI-assisted competitive programming). She collaborates with Microsoft Research’s RiSE and PROSE teams, exploring industry partnerships in AI-assisted software engineering. Recent projects include productizing Gmerge for Microsoft Edge and developing educational tools like PyDex for AI-driven tutoring systems. Zhang actively seeks students (Masters/PhD/interns) and industry collaborations to advance AI’s role in programming and software engineering. Her research bridges foundational AI capabilities with real-world software development challenges, emphasizing both technical innovation and educational impact.

Saba AlimadadiView profile

Assistant Professor

• Human-centred software engineering
• Program analysis
• Program comprehension
• +7 more

Saba Alimadadi is an Assistant Professor in the School of Computing Science at Simon Fraser University, located in Burnaby, BC, Canada. She holds a PhD from the University of British Columbia (2017). Her research focuses on software engineering, particularly program analysis, debugging, and testing of dynamic languages like JavaScript, TypeScript, and Python, aiming to enhance developer productivity through semi-automated techniques. She teaches courses such as CMPT 276 (Introduction to Software Engineering), CMPT 479 (Special Topics in Computing Systems), and CMPT 982 (Special Topics in Networks and Systems). Her research interests include human-centred software engineering, program comprehension, and web engineering. She actively contributes to the academic community, serving on program committees for ICSE, ASE, ISSTA, and organizing conferences like SPLASH/ISSTA and SCAM. Her work bridges theoretical insights with practical tools for improving software development practices. Dr. Alimadadi oversees research opportunities for SFU students, including USRA and work-study positions. She is affiliated with the university’s research groups and labs, though specific lab names are not explicitly mentioned. No scientific awards are cited in the provided materials.

Zhenhao LiView profile

Assistant Professor

• Software Engineering
• Artificial Intelligence
• Software Reliability
• +2 more

Zhenhao Li is an Assistant Professor at York University's School of Information Technology specializing in AI-powered software engineering tools. His research focuses on improving software development processes through artificial intelligence, with publications in premier venues including ICSE, ASE, TSE, and TOSEM. Education PhD in Computer Science, Concordia University (2022) BEng in Software Engineering, Harbin Institute of Technology (2017) Research Focus Dr. Li develops innovative AI techniques for software engineering challenges including code generation, program repair, vulnerability detection, and logging optimization. His work integrates machine learning with software development practices to enhance reliability and efficiency. Publication Trends Recent articles demonstrate a consistent focus on large language model applications in software engineering, particularly for code generation, logging optimization, and vulnerability management. Methodologies include empirical studies, tool development, and literature reviews. Awards ACM SIGSOFT Distinguished Paper Award (ICSE 2024) FRQNT Doctoral Research Scholarship

Ali BashashatiView profile

Associate Professor

• Machine Learning
• Cancer Genomics
• Computational Biology
• +3 more

Dr. Ali Bashashati is an Associate Professor at the University of British Columbia (UBC), affiliated with the School of Biomedical Engineering and the Department of Pathology and Laboratory Medicine. He leads the Artificial Intelligence in Medicine (AIM) Lab, focusing on advancing healthcare through AI-driven solutions in computational pathology and omics data integration. His research combines machine learning, signal processing, and software engineering to address challenges in cancer diagnosis and treatment, particularly in breast, ovarian, and lymphoid cancers. Dr. Bashashati’s work emphasizes multi-modal data analysis, including histopathology imaging and genomics, to improve cancer subtyping and treatment stratification. He has pioneered frameworks like VOLTA for context-aware cell representation learning, enhancing AI models’ performance in histopathology analysis. His contributions to cancer genomics include studies on clonal evolution, tumor heterogeneity, and genomic instability mechanisms. He is the principal investigator of the NSERC CREATE MUSIC training program, a $1.65M initiative fostering next-generation biomedical engineers skilled in AI, biotechnology, and disease biology. This program integrates courses on medical imaging data analysis, applied machine learning, and multi-scale computing for healthcare innovation. Awarded the NSERC CREATE Grant, Dr. Bashashati’s lab collaborates with industry and academia to translate AI innovations into clinical practice, with over 200 peer-reviewed publications in top-tier journals like Nature and Nature Genetics. His team’s work spans from fundamental research to applied tools for precision oncology.

Jeremy BradburyView profile

Associate Professor

• Software Engineering
• Software Quality Assurance
• Testing and Analysis
• +7 more

Jeremy Bradbury is an Associate Professor in the Faculty of Science at Ontario Tech University, where he has served as Undergraduate and Graduate Program Director for Computer Science and as a member of the Board of Governors. His research focuses on software testing, analysis, and quality assurance, with a particular emphasis on human-centered approaches, empirical methodologies, and concurrency issues in software systems. He leads the Software Quality Research Lab (SQRLab) and develops tools like PIE for visualizing software design patterns and GidgetML for adaptive educational gaming. Education: PhD in Computer Science from Queen's University (2007). Research interests include software visualization, open-source software analysis, flaky test detection, and the application of machine learning to software engineering challenges. His work spans both academic contributions (e.g., combinatorial testing frameworks) and practical innovations like the Run, Llama, Run game for computational thinking education. Recent work explores AI-driven bug prediction, data augmentation bias in ML models, and cybersecurity for connected autonomous vehicles. He has organized workshops on testing configurable systems (ToCaMS) and challenges in parallel computing.

Milica RadisicView profile

Professor

• Organ-on-a-Chip Engineering
• Tissue Engineering
• Biomaterials
• +8 more

Milica Radisic is a Professor at the University of Toronto , holding appointments in the Institute of Biomaterials and Biomedical Engineering and the Department of Chemical Engineering and Applied Chemistry . She is the Canada Research Chair (Tier 1) in Organ-on-a-Chip Engineering and a Senior Scientist at the Toronto General Research Institute. Dr. Radisic earned her B.Eng. from McMaster University (1999) , Ph.D. from MIT (2004) , and completed post-doctoral training at the Harvard-MIT Division of Health Science and Technology (2005) . Research Interests: Dr. Radisic pioneers organ-on-a-chip engineering , developing platforms like Biowire , AngioChip , and inVADE to model human physiology for drug discovery and disease research. Her work spans biomaterials synthesis (e.g., bioelastomers , immunomodulatory polymers ), 3D bioprinting , and biofabrication automation . She focuses on cardiovascular and renal organ models , integrating iPSC and patient-derived organoids to study fibrosis, inflammation, and organ rejection. Publication Trends: Her recent work emphasizes multi-organ integration , macrophage-cardiac tissue interactions , and sex-specific disease modeling , with a strong focus on 3D printing and vascularized tissue platforms . Collaborative efforts with institutions like Columbia University highlight translational applications in regenerative medicine and COVID-19 research . Scientific Awards: 2024 Fellow, National Academy of Inventors 2023 Humboldt Research Award 2022 Acta Biomaterialia Silver Award 2021 Safwat Zakay Research Leader Award 2019 Engineering Medal for Research and Development 2017 Royal Society of Canada Fellow 2016 Canadian Academy of Engineering Fellow Grants & Leadership: She has secured over $92 million in grants , including Canada Research Chairs and NSERC funding. Dr. Radisic directs the NSERC CREATE Training Program in Organ-on-a-Chip Engineering and co-chairs major international symposia. Her lab has trained 114 researchers , many of whom now hold academic and industrial leadership roles. Laboratory & Collaborations: Based at the Laboratory for Functional Tissue Engineering (Room MB317, University of Toronto), her team collaborates with Columbia University , Hospital Partners , and industry. The lab is central to the CRAFT Microfluidics Collaboration Centre and has spun out companies like TARA and Quthero .