Model Checking Professors and Supervisors in Canada | ApplySharif

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جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۹۱-۱۰۵ از ۱۱۱ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Steve Easterbrookمشاهده پروفایل

استاد

University of TorontoCanada

Steve Easterbrook is a Professor in the Department of Computer Science and Director of the School of the Environment at the University of Toronto. He holds affiliations with the Sustainability Informatics research group, the Centre for Global Change Science, and the graduate faculty of the School of the Environment. His research focuses on climate informatics, applying software engineering to address climate change challenges, including the analysis of climate models and the development of systems thinking tools for sustainability education. His work spans decades, from early contributions to software verification and systems analysis to pioneering studies on climate model architectures and software quality. He has authored influential papers on topics such as multi-valued reasoning in software models and empirical methods in requirements engineering. Recent efforts include launching a new undergraduate course, Confronting the Climate Crisis , and publishing a book on climate modeling history. Research interests include climate modeling processes, interdisciplinary education, and collective decision-making tools for climate policy. His students and advisees explore themes like software for climate solutions, ethical computing, and transdisciplinary sustainability science. Easterbrook advocates for open science and ethical software practices, emphasizing the societal impacts of technological development.

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Azadeh Farzanمشاهده پروفایل

استاد

University of TorontoCanada

Azadeh Farzan is a Professor and Vice Chair in the Computer Science Department at the University of Toronto. She specializes in formal verification, program analysis, and automated reasoning. Her work focuses on decision procedures, model checking, and logic-based approaches to software reliability. She has held academic roles including postdoctoral research at Carnegie Mellon University under Edmund M. Clarke, and earned her PhD from the University of Illinois at Urbana-Champaign under José Meseguer. She teaches advanced courses such as CSC410, emphasizing formal methods and tools like Dafny for program verification. Her educational contributions include developing tutorials on verification techniques, loop invariants, and SMT solving. Farzan is actively involved in organizing academic conferences, serving as Program Committee member or Area Chair for events like CAV, POPL, PLDI, and VMCAI across multiple years. Her research interests span verification frameworks, static analysis, and the application of logical formalisms to ensure software correctness. She has contributed to the development of verification tools and pedagogical materials for teaching formal methods in CS curricula.

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Cynthia Richardمشاهده پروفایل

دانشیار

University of WaterlooCanada

Cynthia Richard is an Associate Professor (Teaching Stream) in the Faculty of Science at the University of Waterloo, serving as Associate Director of Curriculum and Assistant Dean for Undergraduate Policy. Her expertise spans pharmacology, nutrition, and natural health products, with a focus on innovative educational strategies in pharmacy and healthcare training. She holds leadership roles in curriculum design, interprofessional education, and student well-being initiatives. Dr. Richard’s research emphasizes medical education methodologies, including experiential learning, virtual clinical assessments, and burnout mitigation strategies for healthcare students. She has pioneered activities like 'Check-In' to address mental health in pharmacy education and designed interprofessional programs such as 'RnRx' for palliative care training. Her work bridges clinical practice and education, addressing both professional development and student support systems. Her scholarship spans oncology research, investigating chemotherapeutic mechanisms and cancer cell migration pathways, alongside foundational studies on malnutrition immunology and vitamin D receptor signaling in leukemia. While her recent focus leans toward educational innovation, her earlier work contributed to understanding cancer biology and drug interactions. Dr. Richard’s contributions extend to peer review systems in teaching evaluation and professionalism assessment in pharmacy curricula. She actively shapes undergraduate policy within the Faculty of Science, ensuring alignment between academic standards and evolving healthcare needs. Despite no explicitly listed awards, her role in institutional leadership underscores her impactful contributions to academic governance and curriculum development.

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Christine Purdonمشاهده پروفایل

استاد

University of WaterlooCanada

Christine Purdon is a Professor at the University of Waterloo, specializing in clinical psychology with a focus on Obsessive-Compulsive Disorder (OCD), anxiety disorders, and therapeutic interventions. Her research emphasizes understanding symptom mechanisms, family dynamics in treatment, and improving clinical outcomes through evidence-based practices. She is affiliated with the Clinical group within the university’s faculty structure. Her work spans experimental studies, psychometric tool development, and case analyses. Key areas include the role of attachment, fear of compassion, and family accommodation in OCD progression and treatment. Dr. Purdon’s research also explores comorbidity, cognitive distortions, and the impact of societal factors like the pandemic on mental health. Publications highlight innovative methods such as eye-tracking studies, diary records, and multi-family therapy approaches. She has contributed to refining assessment tools like the Treatment Concerns Questionnaire and Fear of Guilt Scale. Her research demonstrates a consistent focus on translating clinical findings into actionable therapeutic strategies, with particular attention to patient and family perspectives.

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Mehrdad Sabetzadehمشاهده پروفایل

استاد

University of OttawaCanada

Mehrdad Sabetzadeh is a Full Professor and Co-director of the Sedna Research Lab at the University of Ottawa's School of Electrical Engineering and Computer Science. He holds a PhD from the University of Toronto and has held roles at institutions like Simula Research Lab and the University of Luxembourg. His research focuses on software engineering, requirements engineering, AI applications, and legal compliance, with industry collaborations across sectors like finance, energy, and automotive. He leads over $7M in industry-funded projects and co-developed tools like PLEDGE, NARCIA, and Modus. Teaching includes graduate courses on NLP/ML in software engineering and undergraduate computing. Research emphasizes applying AI (NLP, ML) to software challenges, with a focus on IoT and safety-critical systems. Key contributions include frameworks for legal compliance simulation (e.g., GDPR), automated requirement analysis, and safety evidence management. His work bridges academia and industry, addressing real-world system certification and reliability issues. Notable achievements include 150+ publications, tool development for requirement slicing, security control analysis, and safety modeling. He actively mentors graduate students and chairs major conferences like ASE and RE. Current projects explore LLMs for requirement completeness and compliance automation, reflecting his commitment to advancing impactful software engineering practices.

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Karthik Pattabiramanمشاهده پروفایل

استاد

University of British ColumbiaCanada

Karthik Pattabiraman is a Professor and Associate Head (Graduate Affairs) in the Department of Electrical and Computer Engineering at the University of British Columbia (UBC), Canada. He holds a PhD in Computer Science from the University of Illinois at Urbana-Champaign (UIUC), an MS from UIUC, and a B.Tech from the University of Madras. His research focuses on dependable computer systems, computer security, cyber-physical systems, and software engineering. He has led the Dependable Systems Lab and other research groups like RADICAL and LERSSE. Education: PhD (UIUC, 2009), MS (UIUC, 2004), B.Tech (University of Madras, 2001). Postdoctoral research at Microsoft Research (2009). Research Interests: Dependable systems, security in cyber-physical systems, software reliability, and edge computing. His work includes fault injection frameworks (e.g., TensorFI, BinFI), resilience techniques for ML systems, and intrusion detection in robotic vehicles. Awards: Inaugural Rising Star in Dependability Award (2020), UBC Killam Research Prize (2018), IEEE/IFIP DSN Best Paper (2021), and recognition for contributions to dependability and security. Lab Activities: Dependable Systems Lab, Real-Time and Dependable Computing Lab (RADICAL), Secure Systems Engineering (LERSSE), and Software Analysis and Testing (SALT) Lab. Current sabbatical at Meta (2024-2025).

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Samantha Davisمشاهده پروفایل

استاد مدعو

University of British ColumbiaCanada

Samantha Davis is an Adjunct Professor at the University of British Columbia's School of Social Work. With a research focus on substance use stigma and community drug checking, she integrates frontline experience in family law advocacy for survivors of violence. Her teaching emphasizes critical social work applications and practical preparation for clinical practice. Professional Practice: Works at a non-profit legal center providing trauma-informed support to women and gender-diverse clients navigating family law systems. Teaching Focus: Develops training on family violence interventions and lawyer-social worker collaboration models.

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Xichen Zhangمشاهده پروفایل

استادیار

Saint Mary's UniversityCanada

Xichen Zhang is an Assistant Professor at the Department of Finance, Information Systems and Management Science within the Sobey School of Business at Saint Mary's University. His research focuses on cybersecurity, privacy-preserving techniques, federated learning, fake news detection, and machine learning applications in edge-cloud collaboration and mobile crowdsensing. He holds a Ph.D. in a relevant field and has contributed to interdisciplinary projects involving blockchain-based voting systems and IoT security solutions. His work emphasizes practical solutions to modern challenges in data privacy, misinformation detection, and distributed computing. Notable contributions include the development of the TruthSeeker dataset for real/fake content analysis and frameworks like SCORE for scalable contact tracing. His articles explore topics from adversarial machine learning defenses to temporal user credibility models in social networks. Dr. Zhang's research integrates technical innovations with societal impact areas like healthcare informatics and election security. He collaborates across disciplines to address privacy challenges in both academic and industrial contexts. Current projects investigate federated reinforcement learning for IoT systems and multimodal fake news detection using image-text consistency analysis.

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Sameer Borwankarمشاهده پروفایل

استادیار

McGill UniversityCanada

Sameer Borwankar is an Assistant Professor in the Department of Information Systems at the Desautels Faculty of Management, McGill University. His research focuses on digital platforms, human-AI interaction, and platform economics, employing empirical models and machine learning tools. He holds a Ph.D. in Management from Purdue University's Daniels School of Business, along with dual master's degrees in Economics and MBA from the same institution. Prior to academia, he worked at Cummins Inc.'s digital implementation team and as a software engineer in financial services. His research investigates content platform moderation, multi-sided platform ecosystems, and unstructured data analysis. Notable areas include misinformation dynamics on social media, crowdsourcing for fact-checking, and AI's societal impacts. He teaches courses on information systems project management, technology project management, and AI/deep learning fundamentals. Recent work explores geopolitical AI developments, including China's DeepSeek and Qwen models, and the implications of platform policies on misinformation. His interdisciplinary approach bridges technical analysis with policy implications, addressing real-world challenges like data privacy and platform governance. Dr. Borwankar maintains an active blog discussing AI ethics, platform governance, and technology policy. He advises students in McGill's MBA, MM in Analytics, and PhD in Management programs, emphasizing practical applications of theoretical concepts.

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Joanne M. Atleeمشاهده پروفایل

استاد

University of WaterlooCanada

Joanne M. Atlee is a Professor at the Cheriton School of Computer Science , University of Waterloo, Canada. Her research focuses on software engineering , particularly improving software quality through feature modeling and feature interaction management in complex systems like software product lines , systems-of-systems , and the Internet of Things . She develops theories of composition, interaction detection algorithms, coordination architectures, and proof systems for interoperability. Key research areas include Feature Interaction Management Software Product Line Engineering Model-Based Engineering Formal Verification Her recent publications explore AI-generated code detection (2024), variability-aware analysis (2024), and dynamic assertion generation (2023). Collaborations span institutions like McGill University , INRIA , and Siemens Canada , with applications in automotive software and cyber-physical systems .

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Arie Gurfinkelمشاهده پروفایل

استاد

University of WaterlooCanada

Arie Gurfinkel is a Professor at the University of Waterloo, holding a joint appointment in the Department of Electrical and Computer Engineering and the Cheriton School of Computer Science. His research focuses on automated program analysis, software model checking, automated reasoning, and abstract interpretation. He develops tools like SeaHorn, Avy, and others to enhance the verification and testing of complex computer systems. His work emphasizes formal methods, machine learning integration, and hardware/software verification. Recent publications highlight advancements in interpolation-based model checking, constrained Horn clauses, and algorithm selection for hardware verification. Gurfinkel's contributions include open-source tools and frameworks widely used in academic and industrial verification efforts. He actively seeks motivated graduate students interested in logic, automated reasoning, and formal methods. His research has been presented in top-tier conferences and journals, reflecting his expertise in formal verification and software engineering.

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Ihab F. Ilyasمشاهده پروفایل

استاد

University of WaterlooCanada

Ihab F. Ilyas is a Professor and holds the Thomson Reuters–NSERC Industrial Research Chair in Data Quality at the University of Waterloo's Department of Computer Science. His research focuses on data quality, machine learning for data enrichment, probabilistic data management, and knowledge graph systems. He leads projects like Holoclean (a probabilistic data repair system) and Data Civilizer (a data unification platform). His work bridges database systems and machine learning to address challenges in data integration, error detection, and large-scale knowledge representation. Education: PhD in Computer Science from Purdue University (2004), MSc and BSc from Alexandria University, Egypt (1999 and 1995). His publications span vector search, knowledge graph construction, and data curation techniques, with recent emphasis on adaptive indexing and scalable systems. He has contributed to open-source tools and frameworks for data cleaning and machine learning integration. Research interests include probabilistic data management, machine learning applications for data quality, and scalable systems for big data. His work often addresses real-world challenges in data integration and semantic representation, with a focus on practical, deployable solutions.

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Yang Luمشاهده پروفایل

استادیار

University of WaterlooCanada

Machine Learning
Genomics
Proteomics
+۳ مورد دیگر

Dr. Yang Lu is an Assistant Professor at the Cheriton School of Computer Science, University of Waterloo. He develops interpretable machine learning methods for genomics and proteomics, with applications in single-cell analysis and mass spectrometry. His research integrates statistical learning with biological data science to advance reproducible AI in healthcare applications.

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Florent Madelaineمشاهده پروفایل

استاد

University of WaterlooCanada

Florent Madelaine is a Professor at the Laboratoire d'Algorithmique, Complexité et Logique (LACL) at the Université Paris-Est Créteil (UPEC). His academic journey includes a PhD from the University of Leicester (2003) under Iain Stewart and Etienne Grandjean. He has held roles such as Lecturer at Clermont-Ferrand (2007–2018) and Research Associate at Durham University (2003–2007), with visiting positions at Charles University and École Polytechnique. His research focuses on theoretical computer science, particularly finite model theory, computational complexity, and constraint satisfaction problems (CSP/QCSP), with contributions to MMSNP logic and complexity dichotomy conjectures. Currently affiliated with CNRS GdR IM, his work bridges algebraic methods and logical frameworks in computational problems. Education: B.Sc. and M.Sc. in Mathematics (Caen University), M.Sc. in Computer Science (Dresden), PhD in Computer Science (Leicester). Research interests emphasize foundational aspects of computational complexity, with a focus on logical characterizations, algebraic approaches, and constraint satisfaction problem classifications.

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John Cranfieldمشاهده پروفایل

استاد

University of GuelphCanada

John Cranfield is an Associate Dean (External Relations) and Professor in the Department of Food, Agricultural and Resource Economics at the Ontario Agricultural College (University of Guelph). He holds a PhD from Purdue University and undergraduate/master’s degrees from the University of Guelph. His research focuses on consumer behavior and demand analysis in food systems, including studies on food traceability, country-of-origin labeling, and the economic impacts of food safety concerns like BSE (mad cow disease). He has also explored topics such as ethnic food markets, long-term BMI trends in settler societies, and the economic implications of animal welfare standards in poultry production. Education: Bachelor's and Master's in Agricultural Economics, University of Guelph PhD in Agricultural Economics, Purdue University Research Interests: Consumer decision-making in food purchasing Impact of information on market choices (e.g., labeling, certifications) Economic analysis of agricultural policies and trade regulations Historical trends in nutrition and body metrics Ethics in food production and animal welfare His work frequently bridges economic theory with applied policy analysis, addressing issues such as food safety perceptions, trade barriers, and the valuation of ethical production practices. Recent studies highlight trends in consumer preferences for traceable food products and the economic consequences of climate stress on livestock systems. Grant and Industry Collaboration: Cranfield collaborates with industry stakeholders on projects funded through agricultural commodity boards and government initiatives, focusing on maximizing returns from research and marketing investments. His research has informed policy debates on labeling requirements and food safety protocols. Labs/Teams: He contributes to interdisciplinary teams at the University of Guelph’s Food, Agricultural Resource Economics (FARE) research group, evidenced by publications in FARE Share newsletters.

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