Error Control Coding Professors and Supervisors in Canada

Michael Godfreyمشاهده پروفایل

استاد

University of WaterlooCanada

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.

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Shane McIntoshمشاهده پروفایل

دانشیار

University of WaterlooCanada

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.

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Liang-Liang Xieمشاهده پروفایل

استاد

University of WaterlooCanada

Liang-Liang Xie is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. His research focuses on network information theory, wireless relay networks, adaptive control systems, and systems biology. He holds a B.S. in Mathematics from Shandong University (1995) and a Ph.D. in Control Theory from the Chinese Academy of Sciences (1999). He completed postdoctoral research at Linköping University (Sweden) and the University of Illinois at Urbana-Champaign (USA). His work spans theoretical advancements in wireless communication protocols, including relay frameworks, compression techniques, and network coding. Recent articles emphasize omnidirectional relaying, throughput optimization in ad hoc networks, and information-theoretic scaling laws. He has advised over 25 graduate students, many co-supervised with senior faculty members. Current students include Shuyue Wang and Yuxi Zhang. Teaching responsibilities include courses in signals and systems, probability theory, and network information theory. His research has contributed to foundational understanding of transport capacity, channel coding, and multi-user wireless systems.

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Pooya Ronaghمشاهده پروفایل

دانشگاهی

University of WaterlooCanada

Pooya Ronagh is a Research Assistant Professor at the University of Waterloo, affiliated with the Department of Physics & Astronomy and the Institute for Quantum Computing (IQC). He also serves as a Scientific Lead at the Perimeter Institute Quantum Intelligence Lab (PIQuIL) and directs the Hardware Innovation Lab at 1QBit. His work bridges quantum computation, machine learning, and optimal control, focusing on quantum algorithms, error correction, and hybrid quantum-classical systems. Education: PhD in Mathematics (University of British Columbia, 2016), MSc in Mathematics (UBC, 2011), dual BSc in Mathematics and Computer Science (Sharif University of Technology, 2009). Awards include the Benjamin Franklin Fellowship (2009). Research Interests: Quantum algorithms for machine learning, reinforcement learning, fault-tolerant quantum architectures, cryogenic systems, and quantum control. He explores applications of quantum simulation to improve learning efficiency and robustness in AI systems. Recent work includes optimizing quantum error correction decoders, developing scalable superconducting architectures, and advancing neural network-based quantum state tomography. His contributions span theoretical frameworks (e.g., lattice surgery scheduling) and experimental methods (e.g., SFQ pulse control). Teaching: Courses like PHYS 490 (Machine Learning in Physics) emphasize practical coding and interdisciplinary projects. Grants and collaborations involve industry and academic partners in quantum hardware and software development. Labs: Hardware Innovation Lab (1QBit), IQC Quantum Control Group Future Work: Scaling quantum supercomputers, cryogenic neural decoders, quantum-enhanced generative AI

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William N. Sumnerمشاهده پروفایل

دانشیار

Simon Fraser UniversityCanada

William N. Sumner is an Associate Professor and Associate Director, Academic and Administration in the School of Computing Science at Simon Fraser University. He holds a Ph.D. in Computer Science from Purdue University (2013) and a B.Sc. in Computer Science from Hope College (2005). His research focuses on automated debugging tools, concurrency, parallelism, program analysis, and software quality. He teaches courses such as Software Development Methods, Software Testing, and Automated Software Analysis. Sumner actively recruits graduate and undergraduate students for research in improving software development processes through automation. His work emphasizes reducing repetitive tasks in software development using techniques like test case reduction and program analysis. Education: Ph.D., Computer Science, Purdue University, 2013 B.Sc., Computer Science, Hope College, 2005 Research Interests: Sumner’s research addresses challenges in software development automation, including automated debugging, test suite assessment, and program hardening. He develops tools like Pardis to optimize test case reduction and improve software reliability. His work intersects with concurrency, parallelism, and program transformation to enhance developer productivity and software quality. Recent Contributions: Recent publications include advancements in type batched program reduction (2023) and leveraging models for test case reduction in software repositories (2021). His Pardis framework (2019) improves test case reduction efficiency by addressing priority inversion in structured inputs. Teaching & Engagement: Sumner teaches courses such as CMPT 373 (Software Development Methods), CMPT 473 (Software Testing), and CMPT 479 (Automated Software Analysis). He emphasizes hands-on projects, such as the Geotagged Meeting Planner in CMPT 276, focusing on teamwork, agile methodologies, and software engineering best practices.

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George Patrickمشاهده پروفایل

مدرس

University of SaskatchewanCanada

George Patrick is an academic with a focus on geometric mechanics, differential geometry, and numerical analysis. He served as an Instructor from 2010 to 2020, teaching advanced mathematics courses including Calculus II-IV, Differential Equations, and Differential Geometry. His research emphasizes theoretical and computational aspects of dynamical systems, nonholonomic mechanics, and variational integrators. He developed CPOLYCC, a C++ library for multiprecision characteristic polynomial calculations, addressing precision challenges in numerical linear algebra. Research Interests: Geometric Mechanics, Hamiltonian Systems, Numerical Stability Analysis, Nonholonomic Dynamics, Variational Principles, and Computational Geometry. Publications: Over 15 key articles spanning 1985–2023, including foundational work on variational integrators, nonholonomic systems, and stability analysis of relative equilibria. His work bridges pure mathematics and computational methods, with applications in robotics, fluid dynamics, and dynamical systems. The CPOLYCC library demonstrates his focus on precision-critical numerical algorithms, addressing challenges in high-dimensional matrix computations.

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Reid Holmesمشاهده پروفایل

استاد

University of British ColumbiaCanada

Reid Holmes is a Professor in the Department of Computer Science at the University of British Columbia , part of the Faculty of Science . His research focuses on improving software engineering practices, particularly in end-user programming, developer tool design, and empirical software engineering. He leads the Software Practices Lab and has contributed extensively to understanding developer workflows, testing methodologies, and educational tools for programming. Education: PhD in Computer Science, University of Calgary (2008) MSc in Computer Science, University of British Columbia (2004) BSc in Computer Science, University of British Columbia (2002) Research Interests: End-user programming environments, software testing, developer productivity tools, human-centered AI, educational technology, and empirical studies on software development practices. His work emphasizes bridging the gap between theoretical advancements and practical usability for both professional developers and novice programmers. Recent Article Trends: Focus on hybrid programming environments (e.g., block-based and graph-based systems), human-AI collaboration in testing/assertion generation, and age-inclusive IDE design. His research often involves empirical evaluations of tool effectiveness and developer workflows. Awards: FSE Most Influential Paper Award ICSE Most Influential Paper Award UBC Computer Science Teaching Award CS-Can/Info-Can Outstanding Research Prize Advising & Grants: Supervised over 30 graduate students and postdocs. Noted for collaborative projects with industry partners (e.g., Mozilla, Microsoft). Active in curriculum development for software engineering education. Labs/Teams: Leader of the Software Practices Lab , collaborating with industry and academic partners on tools like CodeShovel , AutoAssert , and Devy (conversational developer assistant).

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T. Aaron Gulliverمشاهده پروفایل

استاد

University of VictoriaCanada

T. Aaron Gulliver is a Professor at the University of Victoria's Department of Electrical and Computer Engineering, holding the former Canada Research Chair in Advanced Wireless Communications (2007–2021). He earned his BSc and MSc from the University of New Brunswick and a PhD from the University of Victoria. His academic roles include membership in Engineers and Geoscientists BC and fellowships with the Engineering Institute of Canada (2002) and the Canadian Academy of Engineering (2012). His research spans wireless communications, information theory, cryptography, and signal processing, with a focus on error-correcting codes, cognitive radio, and IoT. Notable contributions include work on turbo codes, LDPC codes, and underwater acoustic systems. Gulliver has authored over 1,000 publications and actively contributes to conferences like the IEEE Pacific Rim Conference on Communications. His current teaching includes courses on Information Theory (ECE 515) and Error Control Coding (ECE 405/ECE 511). Awards include the British Columbia Advanced Systems Institute Research Fellowship (2000) and recognition for his work in green communications and network security. His research group explores cutting-edge topics like quantum field coding and AI-driven spectrum sensing.

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Ueli Rutishauserمشاهده پروفایل

استاد

York UniversityCanada

Memory
Learning
Decision Making
+۷ مورد دیگر

Ueli Rutishauser, PhD is a Professor of Neurosurgery at Cedars-Sinai Medical Center since 2020, with additional appointments in Neurology and Biomedical Sciences. He serves as Director of Human Neurophysiology Research and the Center for Neural Science and Medicine, while maintaining academic ties as Visiting Associate and Lecturer at Caltech since 2012. Caltech: Computation & Neural Systems PhD (2008), Neuroscience Postdoc (2008-2010) Max Planck Institute: Neuroscience Postdoc (2010-2012) Research Interests focus on systems neuroscience spanning: Human single-neuron mechanisms in learning and episodic memory Neural basis of social cognition and face processing Decision-making in Parkinson's and OCD Theta rhythm dynamics in memory consolidation Error monitoring and metacognition Development of OSort spike sorting toolbox Scientific Awards include: National Academy of Sciences Troland Award (2014) NSF CAREER Award (2016) Brain & Behavior Research Foundation Freedman Award (2018) Key Grant Funding from National Institute of Mental Health , National Science Foundation , and Simons Foundation supports work on human decision-making, social attribution, and neural timescales. His lab maintains active collaborations with Caltech, UT Southwestern, and Washington University in St. Louis.

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Dominique Pelletierمشاهده پروفایل

دانشیار

Polytechnic School of MontrealCanada

Dominique Pelletier is an Associate Professor in the Department of Mechanical Engineering at Polytechnique Montréal, where he has established himself as a leading researcher in computational fluid dynamics. His academic journey began with a B.Eng. and M.Sc.A. from Polytechnique Montréal, followed by advanced degrees (M.Sc. and Ph.D.) from Virginia Tech, providing him with a strong foundation in engineering and computational methods. Professor Pelletier's research spans multiple areas of fluid mechanics with particular expertise in finite element methods, turbulence modeling, and fluid-structure interaction. His work addresses both fundamental numerical challenges and practical engineering applications across aerospace, mechanical, and biofluid systems. He has developed innovative approaches to adaptive meshing, sensitivity analysis, and verification and validation of computational fluid dynamics simulations. Analysis of his recent publications reveals a continued focus on advancing numerical methods for complex flow problems, with particular emphasis on adaptive time integration techniques, model-consistent wall functions, and high-fidelity simulation of unsteady flows. His work bridges theoretical developments with practical applications in engineering design and analysis. Professor Pelletier has made significant contributions to the field through his extensive supervision of graduate students (11 PhD and 41 Master's theses) and numerous collaborations with researchers worldwide. His work on verification and validation methodologies has helped establish more rigorous standards in computational fluid dynamics practice. As a member of the Laboratoire de dynamique des fluides (LADYF), Professor Pelletier contributes to a vibrant research environment focused on advancing the understanding and application of fluid mechanics principles. His ongoing research continues to push the boundaries of computational methods for fluid flow simulation and analysis.

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