جست‌وجوی استاد و پژوهشگر

Steven H. H. Dingمشاهده پروفایل

استادیار

• Cybersecurity
• Machine Learning
• Data Mining
• +۷ مورد دیگر

Dr. Steven H. H. Ding is an Assistant Professor at McGill University's School of Information Studies, specializing in cybersecurity, machine learning, and data mining. His research focuses on AI-driven solutions for malware detection, software vulnerability analysis, and reverse engineering. He holds a PhD from McGill University and has been supported by BlackBerry Cylance and DRDC. His work bridges theoretical advancements with practical applications in military systems and avionics cybersecurity. Dr. Ding earned his PhD in 2019 with notable awards including the FRQNT Doctoral Research Scholarship and McGill's Dean’s Graduate Award. His educational background includes degrees from McGill, Concordia University, and the University of Shanghai for Science and Technology. His research interests span cybersecurity domains such as zero-day malware identification, code obfuscation countermeasures, authorship verification for digital forensics, and AI applications in avionics anomaly detection. He actively contributes to open-source tools like the Kam1n0 MapReduce-based assembly clone search system. Recent work emphasizes adversarial machine learning for evasive malware generation, transformer-based anomaly detection in avionics, and automated SBOM generation for firmware analysis. His publications reflect a focus on real-world cybersecurity challenges in both civilian and defense sectors. Dr. Ding leads the L1NNA Lab and collaborates with industry partners on cutting-edge projects. His contributions include novel techniques for phishing detection leveraging large language models and innovative approaches to reverse engineering software composition in JavaScript applications.

• Computer Architecture
• Interconnection Networks
• Approximate Computing
• +۵ مورد دیگر

Natalie Enright Jerger is a Professor in the Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. She holds the Canada Research Chair in Computer Architecture and serves as Director of the Division of Engineering Science (2023-2028). Previously, she was the Percy Edward Hart Professor (2016-2019). She received her B.S. in Computer Engineering from Purdue University (2002), and M.S./Ph.D. in Electrical Engineering from University of Wisconsin-Madison (2004/2008). Her research focuses on: Multi/many-core architectures and on-chip networks Cache coherence protocols and memory hierarchy optimization Approximate computing and sustainable systems Intermittent computing for energy-harvesting devices Hardware acceleration for machine learning Her publications demonstrate strong emphasis on networks-on-chip (NoC) innovations, including routing algorithms, deadlock handling, power-efficient designs, and topology optimizations. Recent work expands into approximate computing, mobile architectures, and ML-driven hardware design. Major Awards: Fellow of Engineering Institute of Canada (2023) McLean Senior Fellow (2019) IEEE Micro Top Picks (2016) ACM/IEEE Microarchitecture Hall of Fame (2015) Sloan Research Fellowship (2015) Canada Research Chair (current) Distinguished Scientist, ACM Fellow, IEEE She leads the NEJ research group and collaborates with industry partners including Intel, AMD, Qualcomm, and IBM. Her work is funded by NSERC, CFI, and industrial grants. She co-chaired ASPLOS 2023 and HPCA 2014, and actively promotes diversity through WICARCH and ACM initiatives.

Guy-Vincent Jourdanمشاهده پروفایل

استاد

• Software Security
• Cybersecurity
• Distributed Systems
• +۶ مورد دیگر

Professor Guy-Vincent Jourdan is affiliated with the School of Electrical Engineering and Computer Science at the University of Ottawa. He holds a Ph.D. from Université de Rennes/INRIA (France, 1995) focusing on distributed systems analysis. Prior to academia, he served as CTO and CEO of Decision Academic Graphics, an Ottawa-based firm. His research interests span software security, cybersecurity (including cybercrime prevention), distributed systems modeling, formal methods, mobile applications, and rich internet applications. Specific technical emphases include phishing detection systems, blockchain fraud analysis, and adversarial machine learning. Professor Jourdan has pioneered tools like D-ForenRIA for reconstructing user interactions in Rich Internet Applications and contributed to cybersecurity frameworks such as HEART for log anomaly detection. His work integrates machine learning techniques with domain-specific challenges in network security and software verification. His publications (2023-2025) reflect advancements in AI-driven vulnerability analysis, blockchain fraud detection, and automated phishing detection systems. Notable projects include SV-TrustEval-C for source code vulnerability analysis and Intellitweet for social media threat detection. While no scientific awards are explicitly listed, his prolific publication record and industry-academia transition highlight sustained contributions to computer science and cybersecurity domains.

Yuan Tianمشاهده پروفایل

استادیار

• Data Mining
• Software Engineering
• Social Network Analysis
• +۳ مورد دیگر

Yuan Tian is an Assistant Professor in the School of Computing at Queen's University, Faculty of Arts and Science. She holds a PhD in Information Systems from Singapore Management University (2017) and a B.Sc. in Computer Science from Zhejiang University (2012). Her research focuses on integrating heterogeneous data sources to enhance software engineering practices, including data mining, recommender systems, and social network analysis. Prior to Queen's, she was a data scientist at Living Analytics Research Centre (LARC), SMU. She has held visiting positions at Carnegie Mellon University, INRIA Paris, and SAIL Canada. Research Interests: Data Mining Software Engineering Social Network Analysis Information Retrieval Recommender Systems Computer Security Recent Research Trends: Her work emphasizes AI-driven solutions for software bug management, code translation, vulnerability detection, and developer behavior analysis. Notable contributions include leveraging LLMs for technical debt repayment and enhancing code vulnerability detection via Graph Neural Networks. Awards: SMU Presidential Doctoral Fellowship (2015-2016) Best Paper Award at SANER 2017 Grants & Advising: No formal advisees listed, but active in collaborative projects with industry and academic partners. Labs/Teams: Previously associated with SOAR Group at SMU and currently leads research in Queen's School of Computing.

• Software Engineering
• Reverse Engineering
• Program Understanding
• +۷ مورد دیگر

Ken Wong is an Associate Professor in the Department of Computing Science at the University of Alberta's Faculty of Science. He also serves as Associate Chair within the same department. Holding a PhD in Computer Science from the University of Victoria (1999), his research focuses on software engineering challenges such as reverse engineering, program understanding, and software visualization. He emphasizes improving software evolution through tools like architecture recovery and root cause analysis, with applications in web/mobile platforms and diverse system understanding. Teaching highlights include developing Massive Open Online Courses (MOOCs) via Coursera, including the 'Software Product Management Specialization' and courses on Agile practices, client needs analysis, and software metrics. His recent publications (2023–2025) span AI-driven healthcare innovations (e.g., medical imaging, photoacoustic tomography) and advanced computer vision techniques (e.g., diffusion models, video inpainting). Notable collaborations include EVAREST studies on heart failure management and lung transplantation outcomes. His work bridges software engineering theory and practical applications in healthcare technology, with contributions to federated learning frameworks (e.g., FedLPPA) and AI-augmented clinical decision support systems. Research also extends to autonomous driving (DriveGPT4-V2) and 3D human avatar generation (DreamAvatar), showcasing interdisciplinary impact.

Roozbeh Razavi-Farمشاهده پروفایل

استادیار

• Machine Learning
• Cybersecurity
• Federated Learning
• +۵ مورد دیگر

Roozbeh Razavi-Far is an Assistant Professor at the Faculty of Computer Science and the Canadian Institute for Cybersecurity at the University of New Brunswick. His research focuses on machine learning, big data analytics, and cybersecurity of cyber-physical systems and IoT devices. He has authored/co-authored over 150 publications and is listed by Stanford as among the top 2% of most cited researchers (2022). His work spans federated learning, transfer learning, quantum machine learning, and dependable AI systems. He serves as an Associate Editor for Neurocomputing, Machine Learning with Applications, and IEEE Transactions on Industrial Cyber-Physical Systems, among others. As an IEEE Senior Member, he chairs IEEE Computational Intelligence and Systems, Man, and Cybernetics Societies. Previously, he directed the Learning System and Cybernetics Group at the University of Windsor (2016–2022). His research interests emphasize security in non-stationary environments, adversarial machine learning defenses, and real-time analytics for smart grids. Awards include NSERC-DG, NSERC-ECR, and USRG grants. He has mentored students who received NSERC Alexander G. Bell, MITACS, and Ontario Graduate Scholarships. His recent publications highlight advancements in privacy-preserving split learning, blockchain-based federated learning security, and graph-based malware detection. He also explores quantum computing applications in AI and cybersecurity frameworks for cyber-physical systems.

• Software Engineering
• Video Game Development
• Artificial Intelligence for Software Engineering (AI4SE)
• +۴ مورد دیگر

Cristiano Politowski is an Assistant Professor in the Department of Computer Science at Ontario Tech University’s Faculty of Science. His research focuses on applying software engineering principles to video game development, with particular emphasis on software testing, artificial intelligence for software engineering (AI4SE), deep reinforcement learning, and empirical software engineering. Education includes a PhD in Computer Science and Software Engineering from Concordia University (2022), supervised by Professors Yann-Gaël Guéhéneuc and Fabio Petrillo. Prior to his current role, he held postdoctoral positions at Université de Montréal and École de Technologie Supérieure in Montréal, Canada. Research interests span game engine architecture analysis, automated testing methodologies for games, and bridging gaps between academic theory and industry practices in software engineering. His work often involves empirical studies on software quality, framework impacts, and event-driven systems. Publications reflect a focus on game development challenges, including studies on API compatibility, subsystem coupling visualization, and AI-driven game balance assessment. He actively contributes to the understanding of software processes in the video game industry through surveys and dataset curation initiatives like PlayMyData.

Ignacio Castilloمشاهده پروفایل

استاد

• Facility Location
• Operations Research
• Supply Chain Management
• +۳ مورد دیگر

Ignacio Castillo is a Professor and Associate Dean of Business (Graduate Academic Programs) at the Lazaridis School of Business and Economics, Wilfrid Laurier University. His expertise spans facility location optimization, supply chain management, and sustainable operations. He holds a leadership role in graduate academic programming and teaches courses in operations and statistics. Research focuses on optimizing facility layouts, material handling systems, and closed-loop supply chains. He has developed frameworks for multi-objective facility design and advanced packing optimization algorithms. His work bridges theoretical models with real-world applications in manufacturing and retail sectors. Publications emphasize nonlinear optimization techniques, packing problems, and supply chain coordination strategies. Recent work explores irregular object configurations and retail category space optimization. His textbooks include Business Statistics for Contemporary Decision Making and Operations Management , emphasizing practical decision-making tools. Office: LH4001M | Languages: English, Spanish

Matt Amyمشاهده پروفایل

استادیار

• Quantum Computing
• Programming Languages
• Compilers
• +۳ مورد دیگر

Dr. Matt Amy is an Assistant Professor in the School of Computing Science at Simon Fraser University (SFU), holding the Canada Research Chair in Quantum Computing. His research focuses on quantum compilers, programming languages, and formal verification of quantum programs. He also explores quantum circuit optimization and models of quantum computation. Education: PhD in Computer Science (University of Waterloo, 2019), M.Math in Quantum Information (2013), and B.Math in Computer Science (2011), all from the University of Waterloo. Research Interests: Quantum compilers and languages, circuit optimization, formal verification, and quantum computation models. His work bridges theoretical foundations with practical implementations, emphasizing efficient quantum software development. Recent research trends include advancing quantum compilation techniques, exploring NP-hard optimization problems in quantum circuits, and developing formal methods for quantum program analysis. His work on symbolic synthesis and equational theories for quantum circuits demonstrates a focus on foundational algorithmic challenges. Scientific Awards: Canada Research Chair (2025–present) Advising and Grants: While no current advisees are listed, his research is supported by grants focused on quantum computing and formal methods. He collaborates with industry through SFU’s School of Computing Science. Labs and Teams: Involved with the Tangent Lab, a research group exploring quantum algorithms and software systems at SFU.

Yann-Gaël Guéhéneucمشاهده پروفایل

استاد

• Software Engineering
• IoT Systems
• Static and Dynamic Analyses
• +۴ مورد دیگر

Yann-Gaël Guéhéneuc is a Professor at Concordia University's Department of Computer Science and Software Engineering. He leads the Ptidej Team, focusing on software engineering methodologies, IoT systems, and game engine architecture analysis. His research emphasizes static/dynamic analyses, service-oriented architectures, and machine learning design patterns. Current Affiliations: Concordia University (Full-time Professor) Ptidiej Team Lead Research Interests: Specializes in IoT system testing, microservices architecture, game engine design patterns, and anti-pattern detection in multi-language systems. His work bridges theoretical software engineering principles with practical industrial applications, particularly in legacy system modernization and machine learning system design. Recent Trends in Publications: Focuses on IoT testing methodologies, machine learning architecture patterns, and service-oriented system transformations. His 2025 works advance IoT system taxonomy and game engine analysis techniques. Advising: Supervises MASc and PhD programs in Software Engineering and Computer Science Labs/Teams: Ptidej Team develops software tools for system analysis (e.g., Magnet, SyDRA)

M Reza Kholghyمشاهده پروفایل

دانشیار

• Industrial Decarbonization
• Hydrogen Production
• Carbon Dioxide Conversion
• +۷ مورد دیگر

Dr. M Reza Kholghy is an Associate Professor and Canada Research Chair in Particle Technology and Combustion Engineering at Carleton University's Department of Mechanical and Aerospace Engineering. He directs the Energy and Particle Technology Laboratory (EPTL) where he focuses on sustainable industrial solutions. His academic credentials include a BASc in Aerospace Engineering from Sharif University of Technology, and MASc/PhD degrees in Mechanical Engineering from the University of Toronto, followed by postdoctoral work at ETH Zurich. Research interests center on: Industrial decarbonization through metal fuel combustion (aluminum/iron) and carbon management Hydrogen production via methane pyrolysis and metal-water reactions Advanced material synthesis including flame spray pyrolysis for catalytic films and alumina production Nanoparticle engineering with focus on soot formation dynamics and optical properties His publications predominantly explore nanoparticle synthesis mechanisms, soot formation modeling, and sustainable fuel technologies, with recent emphasis on hydrogen cogeneration and metal combustion. Experimental and computational approaches are equally represented across combustion diagnostics, reactor design, and molecular dynamics simulations. Major scientific recognitions include: Canada Research Chair (Tier 2) Vanier Canada Graduate Scholarship NSERC Postdoctoral Fellowship He leads the Energy and Particle Technology Laboratory with industry partnerships focused on sustainable technology development. The lab specializes in flame spray pyrolysis reactors, nanoparticle characterization (surface area, porosity, composition), and high-pressure reaction systems. Dr. Kholghy actively mentors students through capstone projects and research positions, though specific PhD/Master's advisees aren't named in available sources.

Steven Dingمشاهده پروفایل

استادیار مدعو

• Artificial Intelligence
• Data Analytics
• Security
• +۴ مورد دیگر

Steven Ding is an Adjunct Assistant Professor and Lab Director at the School of Computing, Queen's University , leading the L1NNA Artificial Intelligence and Security Lab. His research focuses on the intersection of machine learning, data mining, and cybersecurity with applications in malware analysis, reverse engineering, and authorship attribution. Education: PhD in Information Studies (McGill University, 2019), M.A.Sc. in Information Systems Security (Concordia University), B.S. in Information Systems (University of the Fraser Valley), B.S. in Computer Science (University of Shanghai for Science & Technology) Research Interests: His work integrates artificial intelligence and security systems to develop solutions for malware phenotype decomposition, neural malware analysis, binary provenance, and explainable AI in cybersecurity. He explores data analytics for assembly code evolution and authorship analysis using machine learning and differential privacy . Publication Trends: His peer-reviewed work (IEEE Transactions, ACM conferences) emphasizes binary code analysis , neural networks , and cybersecurity , with a focus on static malware characterization , authorship attribution , and cross-architecture code similarity . Scientific Awards: FRQNT Doctoral Research Scholarship (2017-2018) Dean’s Graduate Award at McGill University (4 years, 2014-2018) NSERC Alliance Grant (2021-2024) Best Poster Award, SERENE-RISC Research Showcase (2016) Second Prize, Hex-Rays Software Plug-in Contest (2015) ACM SIGKDD Student Travel Award (2016) Advising & Grants: Dr. Ding has supervised numerous Ph.D. and Master’s students (e.g., Li Tao Li, Mark M. Adams) and secured significant funding from BlackBerry Cylance , DRDC , and NSERC , including a 1.24M CAD NSERC Alliance Grant (50%) and 1.5M CAD DRDC Contract (50%). Labs & Teams: The L1NNA lab collaborates with DRDC Canada, NVIDIA, and IEEE Security & Privacy, focusing on AI-driven security tools (e.g., Kam1n0 assembly clone search engine) and neural malware analysis . The lab is located in Goodwin Hall, Queen's University, and emphasizes practical software development and industrial partnerships .

Ali Ghorbaniمشاهده پروفایل

استاد

• Cybersecurity
• Machine Learning
• Network Security
• +۳ مورد دیگر

Dr. Ali Ghorbani is a Professor and Tier 1 Canada Research Chair in Cybersecurity at the University of New Brunswick's Faculty of Computer Science, where he served as Dean from 2008-2017. He is the founding Director of the Canadian Institute for Cybersecurity (CIC), established in 2016. Ghorbani holds BSc (Tehran), MSc (George Washington University), and PhD (UNB) degrees. With 42+ years in academia, his research spans cybersecurity, machine learning, adaptive systems, and critical infrastructure protection. Ghorbani has co-founded three cybersecurity startups (Sentrant Security, EyesOver Technologies, Cydarien Security) and co-invented four awarded patents. He has published 300+ peer-reviewed papers and supervised 250+ researchers. Professional roles include co-founding the National Cybersecurity Consortium (NCC) and serving as co-editor-in-chief of Computational Intelligence journal. Awards & Honors: Canada Research Chair in Cybersecurity Startup Canada Senior Entrepreneur Award (2017) RBC Top 25 Canadian Immigrants (2019) CAIAC Lifetime Achievement Award (2024)

Elisa Baniassadمشاهده پروفایل

استاد آموزشی

• Software Engineering
• Educational Technology
• Aspect-Oriented Programming
• +۳ مورد دیگر

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.

Marinko Sarunicمشاهده پروفایل

استاد مدعو

• Biomedical Imaging
• Optical Coherence Tomography
• Microscopy
• +۲ مورد دیگر

Marinko Sarunic is an Adjunct Professor at the School of Engineering Science , Simon Fraser University . He holds a PhD in Biomedical Engineering from Duke University and has been recognized as a Michael Smith Foundation for Health Research Scholar . His research focuses on biomedical imaging , particularly optical coherence tomography (OCT) , microscopy , and low-coherence interferometry , with applications in diabetic retinopathy , Alzheimer’s disease , and age-related macular degeneration . Dr. Sarunic's work spans adaptive optics , deep learning , and sensorless OCT systems , emphasizing clinical translation and open-source software development (e.g., OCTAVA ). His Google Scholar publications highlight multimodal imaging , vascular heterogeneity analysis , and AI-driven diagnostics for retinal diseases. His contributions include the Michael Smith Foundation for Health Research Scholar award. Though not currently teaching courses, his collaborations and leadership in retinal imaging and medical device innovation are pivotal for advancing non-invasive diagnostics in neurodegenerative and diabetic conditions .