جست‌وجوی استاد و پژوهشگر

Shurui Zhouمشاهده پروفایل

استادیار

• Software Engineering
• Open-Source Collaboration
• Fork-Based Development
• +۴ مورد دیگر

Shurui Zhou is an Assistant Professor at the University of Toronto , with primary appointment in the Department of Electrical & Computer Engineering and cross-appointments in the Department of Computer Science and the Department of Mechanical & Industrial Engineering . She is also affiliated with the Schwartz Reisman Institute and a member of the Data Sciences Institute . Zhou directs the FORCOLAB , focusing on enhancing collaboration in distributed software teams, especially in open-source and AI-enabled systems development. Her research integrates software engineering principles with human collaboration insights from organizational behavior, aiming to improve collaboration efficiency through tooling and interdisciplinary methods. Recent publications (2023-2025) explore LLM integration in software development , sustainability in scientific open-source communities , and collaborative challenges in computer-aided design . Education: PhD (2020) from Carnegie Mellon University's Software and Societal Systems Department , MSc from Peking University , BSc from Xi'an Jiaotong University Scientific Awards: Gordon Slemon Teaching of Design Award (2022) Grants: Collaborator on NSERC Alliance-Mitacs Accelerate Grant (2025) for LLM analysis in political data Her lab, FORCOLAB, develops tools like forks-insight.com to analyze GitHub forks and Redundant PR detection bots . Zhou organizes events like the Responsible LLM-Human Collaboration Hackathon (2024) and actively serves on conference committees including ICSE 2025 and ICSME 2024 .

Salma Emaraمشاهده پروفایل

استادیار

• Machine Learning
• Computer Networking
• Natural Language Processing
• +۳ مورد دیگر

Salma Emara is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Toronto within the Faculty of Applied Science & Engineering. Her academic journey includes a B.Sc. in Electronics and Communications Engineering from the American University in Cairo (2018) and a Ph.D. in Computer Engineering from the University of Toronto (2022), supervised by Professor Baochun Li. Her research spans two domains: (1) technical work in reinforcement learning for computer networking , including adaptive bitrate selection, edge caching, and congestion control; and (2) pedagogical work focused on debugging skill development for beginner programmers and leveraging natural language processing in engineering education . She emphasizes hands-on learning through in-class activities and problem-solving assignments. Publication trends reveal a focus on reinforcement learning in networking (2018–2023) and a parallel interest in educational technology (2024). Her recent work (e.g., TextCraft ) explores NLP-driven resource recommendation for textbooks, while earlier projects (e.g., Cascade , Pareto ) address network optimization through machine learning. Scientific awards include: Faculty of Applied Science & Engineering Early Career Teaching Award (2025) Departmental Teaching Awards (2022–2024) Shortlisted for TATP Teaching Assistant Excellence (2022)

Barry C. Sandersمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Information Theory
• Quantum Algorithms
• +۳ مورد دیگر

Barry C. Sanders is a Professor and Director of the Institute for Quantum Science and Technology at the University of Calgary. He holds additional roles as Lead Investigator of the Alberta Major Innovation Fund Project on Quantum Technologies, a Thousand Talents Chair at the University of Science and Technology China, and Vajra Visiting Faculty at the Raman Research Institute. His research focuses on quantum computing, quantum algorithms, and optical implementations of quantum information tasks. Sanders has a PhD from Imperial College London (1987) and has held faculty positions at Macquarie University and the Australian National University. Education: BSc (University of Calgary, 1984), PhD (Imperial College London, 1987) Affiliations: Institute for Quantum Science and Technology, Alberta Major Innovation Fund Project His research interests include quantum-limited measurement, nonclassical light, quantum cryptography, and quantum algorithm development. He has pioneered work on Schrödinger cat states, qudit systems, and quantum error correction. Awards include Fellowships from the Institute of Physics, Optical Society of America, and Royal Society of Canada. His work bridges theory and application, with contributions to quantum technology commercialization and interdisciplinary collaborations. Editor-in-Chief, New Journal of Physics Past leadership roles: President of the Australian Optical Society, Founding Co-Chair of the Canadian Association of Physicists Division His recent publications explore quantum speedup in machine learning, topological quantum walks, and fault-tolerant quantum computing architectures.

Chen Fengمشاهده پروفایل

دانشیار

• Information Theory
• Coding Theory
• Blockchain Technology
• +۴ مورد دیگر

Chen Feng is an Associate Professor in the Department of Electrical Engineering at the School of Engineering, University of British Columbia (UBC), Okanagan campus. He holds the Tier-2 Principal's Research Chair in Blockchain and serves as the Co-Cluster Lead for Blockchain@UBC. Dr. Feng joined UBC in July 2015 after completing postdoctoral fellowships at Boston University and EPFL. Dr. Feng received his B.Eng. degree from Shanghai Jiao Tong University in 2006, and his M.A.Sc. and Ph.D. degrees from the University of Toronto in 2009 and 2014, respectively. Dr. Feng's research focuses on the intersection of information theory, coding theory, and blockchain technology. His work spans several key areas including: Information and Coding Theory for wireless communications Blockchain and distributed ledger technologies Quantum communications and cryptography Cloud computing optimization and analysis Stochastic analysis of distributed systems His recent research output demonstrates a strong trajectory in blockchain consensus protocols, private information retrieval, and the application of information theory to distributed systems. Dr. Feng has been actively publishing in top-tier venues with a focus on improving the performance, security, and scalability of blockchain systems. Dr. Feng has received several prestigious awards including: Best Paper Award at IEEE MSN (2021) Tier-2 Principal's Research Chair Award (2020) Visiting Fellow Scholarship at the University of Melbourne (2019) Emerging Professor Award from UBC-Okanagan School of Engineering (2017) Teaching Excellence Award (2017/18) As a graduate student supervisor, Dr. Feng teaches a range of courses from undergraduate to graduate levels, with a particular emphasis on blockchain technologies, wireless communications, and advanced engineering topics. He serves as a Senior Research Consultant for Subspace Labs and a Scientific Consultant for Creative Destruction Lab, bridging academic research with industry applications. Dr. Feng leads the Blockchain@UBC initiative, which focuses on advancing blockchain research and applications across multiple domains including clean energy, distributed systems, and secure communications.

David Novogمشاهده پروفایل

استاد

• Nuclear Reactor Physics
• Thermal Hydraulics
• Computational Fluid Dynamics (CFD)
• +۴ مورد دیگر

David Novog is a Professor in the Department of Engineering Physics at McMaster University . His work bridges nuclear reactor physics, thermal hydraulics, and computational modeling, with a focus on safety analysis and advanced reactor designs like small modular reactors (SMRs). Research Interests: Nuclear reactor safety, computational fluid dynamics (CFD) in reactor systems, neutron tomography, uncertainty quantification in nuclear data, and energy transition strategies. Teaching: Courses include Thermal Systems Design (ENGPHYS 2NE3), Numerical Methods for Engineering (ENGPHYS 3NM4), and Computational Methods for Engineering Physics (ENGPHYS 2CE4). Grants: Co-leader of a $2.6M project on SMR research, with ongoing contributions to OECD/NEA benchmarks and nuclear safety frameworks. Labs: Active at the McMaster Nuclear Reactor , where experiments on neutron flux and heat transfer are conducted.

François Rivestمشاهده پروفایل

دانشیار

• Artificial Intelligence Engineering
• Machine Learning Systems
• Computational Neurosciences
• +۳ مورد دیگر

Dr. François Rivest is an Associate Professor at Queen’s University, affiliated with the Department of Biomedical and Molecular Sciences (School of Medicine, Faculty of Health Sciences). He also holds cross-appointments in the School of Computing (Faculty of Arts and Science) and is a member of the Centre for Neuroscience Studies. His research focuses on machine deep reinforcement learning and animal interval timing, aiming to bridge computational neuroscience insights with advanced AI systems. He leads the Natural and Artificial Adaptive Intelligent Systems Laboratory. Education: PhD in Computer Science (Computational Neuroscience/Machine Learning) – Université de Montréal (2010) MSc in Computer Science – McGill University (2002) BSc in Mathematics and Computer Science – McGill University (2000) Research Interests: Dr. Rivest’s work integrates principles of animal learning, particularly reward-based systems and temporal cognition, into machine learning algorithms. Key areas include: Reinforcement learning frameworks inspired by dopamine signaling Drift-diffusion models for interval timing Adaptive representation construction in real-time systems Applications in smart homes, robotics, and neuroscience Publications: Over 20 peer-reviewed articles (2001–2022) span computational neuroscience, reinforcement learning, and machine learning systems. Recent work includes modeling interval timing dynamics and applying reinforcement learning to smart home systems. Lab & Affiliations: As Principal Investigator of the Natural and Artificial Adaptive Intelligent Systems Lab, he explores interdisciplinary AI applications. Collaborations include the Royal Military College of Canada (2010–present) and Queen’s University’s Center for Neuroscience Studies (2011–present).

Joseph Schmidtمشاهده پروفایل

استاد

• Talent Acquisition
• Team Effectiveness
• Employee Turnover
• +۴ مورد دیگر

Joseph Schmidt is a Professor and Edwards Enhancement Chair in Business at the Edwards School of Business, University of Saskatchewan. He holds a PhD in Industrial/Organizational Psychology (University of Calgary), an MSc in Industrial/Organizational Psychology, and a BA in Psychology, all from the University of Calgary. His research focuses on talent acquisition, team effectiveness, employee turnover, judgment errors, and bias reduction in organizational contexts. Dr. Schmidt’s academic contributions span top-tier journals such as the Journal of Applied Psychology , Personnel Psychology , and Psychological Bulletin . His work bridges theory and practice, addressing real-world challenges in HR management and organizational behavior. Notable themes include the impact of personality on workplace outcomes, the dynamics of team performance, and the design of effective selection systems. Before academia, he worked at Hay Group (global consulting) and in HR for an engineering firm. His courses include Human Resource Management , Leadership , and Organizational Dynamics . Media outlets like the Wall Street Journal and CBC Radio have featured his research insights. His publications analyze trends in performance appraisals, team variance in ratings, and the role of dynamic behavioral trends. He emphasizes methodological rigor, particularly in addressing selection bias and causal inference. While no specific awards are listed, his prolific and influential work underscores his academic standing.

Amy Finnمشاهده پروفایل

دانشیار

• Developmental Cognitive Neuroscience
• Learning and Memory Systems
• Child Development
• +۳ مورد دیگر

Amy Finn is an Associate Professor and Director of the Finn Learning and Neural Development Lab (LAND Lab) at the University of Toronto. Her research investigates how brain and cognitive development shape learning outcomes in children, focusing on memory systems, neural plasticity, and environmental influences. The LAND Lab explores developmental cognitive neuroscience, emphasizing age-related learning patterns, critical periods, and brain-environment interactions. Current research areas include implicit memory development, attentional modulation of learning, socioeconomic impacts on neural systems, and computational models of cognition. Notable publications span topics like attention-memory dynamics, scene perception in children, and socioeconomic status effects on hippocampal development. Collaborations involve institutions such as MIT, Emory University, and international labs. Developmental Cognitive Neuroscience Learning and Memory Systems Neural Plasticity Environmental Influences on Learning

Michael W. Godfreyمشاهده پروفایل

استاد

• Software Engineering
• Program Comprehension
• Mining Software Repositories
• +۵ مورد دیگر

Affiliations & Roles Michael W. Godfrey is a Professor in the David R. Cheriton School of Computer Science at the University of Waterloo . He holds the David R. Cheriton Faculty Fellowship and has served as an associate director of Cornell's M.Eng. program. His roles include: General Chair for ICPC 2025 (IEEE Program Comprehension) Member of steering committees for ICSME, MSR, SCAM, and SWAN Course coordinator for CS138/CS246 and instructor for advanced topics courses Research Focuses on software evolution , program comprehension , and mining software repositories . His work addresses challenges in code clone analysis, developer productivity, and empirical software engineering. Notable contributions include: Advocating for intentional cloning as valid design practice Pioneering studies on code review quality and anomaly detection Developing tools like JavaDUCK (educational project) and mel (model extraction) Awards & Recognition Recipient of: Best Paper Awards at WCRE 2006, 2011, 2013 Most Influential Paper Award at SANER 2016 Outstanding Reviewer Awards (ICSME 2019/2020) Service & Outreach Active in: Program committee roles for ICSE, ICSM, MSR, and 30+ conferences University service: Undergraduate Recruitment Committee (2016–present) Industry collaborations with CWI (Amsterdam), Sun Microsystems, and automotive software teams

Raymond Laflammeمشاهده پروفایل

استاد

• Quantum Computing
• Quantum Error Correction
• Quantum Simulation
• +۳ مورد دیگر

Raymond Laflamme serves as Advisory Committee Chair at the University of Waterloo's Institute for Quantum Computing and holds a Canada Research Chair in Quantum Information Science since 2002. A leading theoretical physicist, he has shaped foundational quantum computing research globally. His academic credentials include: PhD in Applied Mathematics and Theoretical Physics from University of Cambridge BS in Physics from Université Laval Laflamme's research pioneers quantum error correction methodologies , quantum simulation techniques , and experimental implementations using spin/photon systems . His work bridges theoretical frameworks with physical quantum device construction, notably influencing Stephen Hawking's reversal of time-direction theories as documented in A Brief History of Time . Current efforts focus on heat-bath algorithmic cooling and fault-tolerant gate architectures for scalable quantum processors. Publication trends (2006-2016) reveal progressive specialization from textbook foundations to experimental thermodynamics in quantum systems, with increasing emphasis on error-resistant architectures and algorithmic cooling techniques essential for practical quantum computing. Major recognitions include: Officer of the Order of Canada (2017) CAP-CRM Award (2017) Honorary Degree from Université de Sherbrooke (2012) Canada Research Chair (2002–present) AAAS Fellowship (2011) Ontario Premier's Discovery Award (2008) FRSC and APS Fellowships (2008) As Canada Research Chair, Laflamme directs substantial federal funding toward quantum information science infrastructure. His textbook co-authorship and Nature review article demonstrate exceptional knowledge dissemination, while ongoing PRL publications validate continuous research leadership. Though student advising isn't explicitly documented, his institute role implies mentorship of next-generation quantum scientists through the Institute for Quantum Computing's extensive training programs. Laflamme operates within Waterloo's Institute for Quantum Computing—a globally recognized hub housing 150+ researchers across quantum hardware, software, and communication domains—where his advisory leadership shapes strategic research directions and international collaborations.

• Ocular Movements
• Attention
• Cognitive Functions
• +۵ مورد دیگر

Dr. Aarlenne Khan is an Associate Professor at the School of Optometry, University of Montreal, and holds the Canada Research Chair in Vision and Action. Her research focuses on interactions between attention, ocular movements, and cognitive functions in healthy and neurological populations (e.g., Parkinson’s disease, parietal lobe lesions, ataxia). She employs behavioral, neurophysiological, and neuroimaging techniques, including transcranial direct current stimulation (tDCS). Education: Bachelor’s in Psychology (2000), York University Master’s in Psychology (2002), York University Ph.D. in Psychology (2006) and Neuroscience (2006) from York University and Université Claude Bernard, France Postdoctoral training at The Smith-Kettlewell Eye Research Institute (2006–2009) and Queen’s University (2009–2013) Research Interests: Ocular movements, spatial attention, motor control, and cognitive deficits in neurological disorders. Her work bridges basic neuroscience and clinical applications, emphasizing translational outcomes. Grants & Awards: Canada Research Chair in Vision and Action (2014–present) CIHR and NSERC grants for studies on attention-motor interactions and vision rehabilitation Leading roles in networks like RRSV (Vision Health Research Network) and REPAR (Adaptation-Rehabilitation) Advising: Supervised over 10 graduate theses, including work on Parkinson’s cognitive functions, spatial inhibition mechanisms, and optic ataxia. Labs & Teams: Member of the GRSV (Vision Sciences Research Group), CIRCA (Brain and Learning), and the Interdisciplinary Vision and Action Lab at the School of Optometry.

Petr Lisonekمشاهده پروفایل

استاد

• Cryptography
• Error-Correcting Codes
• Quantum Codes
• +۵ مورد دیگر

Petr Lisonek is a Professor in the Department of Mathematics at Simon Fraser University (SFU), part of the Faculty of Science. His research focuses on applications of algebraic and combinatorial methods in cryptography, error-correcting codes, steganography, and computer algebra. Education: Ph.D. in Computer Science from Johannes Kepler University (1994). Research Interests: Non-linear functions in symmetric cryptography and their algebraic/combinatorial constructions. Design of error-control codes for classical and quantum channels using finite fields and finite geometries. Steganographic schemes leveraging linear codes for secure information hiding. Algorithmic aspects of cryptography and coding theory in computer algebra systems. Recent Research Trends: Recent work emphasizes quantum code construction, cryptographic APN permutations, and foundational results in quantum contextuality (Kochen-Specker sets). Publications span topics like twisted codes, maximal nonassociative quasigroups, and minimal magic sets in quantum mechanics. Affiliations: Editor for Advances in Mathematics of Communications . Maintains a research website at CECM .

Alexandre Blaisمشاهده پروفایل

استاد

• Quantum Information Science
• Quantum Computing
• Superconducting Quantum Circuits
• +۳ مورد دیگر

Professor Alexandre Blais is a leading researcher in quantum information science at the University of Sherbrooke's Faculty of Science, where he leads the Superconducting Quantum Circuit Theory research group (TheSQuaD) within the Quantum Institute. His work focuses on understanding quantum states of mesoscopic devices and applying quantum optics tools to these systems, with particular expertise in circuit QED with superconducting qubits. Blais' research spans multiple areas of quantum computing, including superconducting circuits, quantum error correction, quantum measurement, and quantum control. His group develops theoretical frameworks for quantum information processing using superconducting quantum circuits, with applications to quantum computing and quantum optics. They collaborate extensively with experimental groups worldwide to bridge theory and practice in quantum information science. His recent publications demonstrate continued leadership in advancing quantum computing technologies, with research spanning transmon qubits, quantum error correction, quantum measurement techniques, and quantum control methods. Blais' work shows a consistent focus on solving practical challenges in building scalable quantum computers, particularly through innovative approaches to qubit design, control, and measurement. Fellow of the American Physical Society (2018) Rutherford Memorial Medal of the Royal Society of Canada (2018) Prix Urgel-Archambault, Association francophone pour le savoir (2014) Herzberg Medal from the Canadian Association of Physicists (2011) NSERC E.W.R. Steacie Memorial Fellowship (2010) Professor Blais has mentored numerous students who have gone on to prominent positions in academia and industry, including faculty positions at Yale, MIT, University of Sydney, and research scientist roles at Google Quantum AI, Microsoft Quantum, and Rigetti Computing. His group operates within the state-of-the-art Quantum Institute building at the University of Sherbrooke, fostering a collaborative environment for theoretical and experimental quantum research.

Simon Dayمشاهده پروفایل

استاد مدعو

• Reactor Physics
• Safety Analysis
• Criticality Safety
• +۴ مورد دیگر

Simon Day is an Adjunct Professor in the Department of Engineering Physics at McMaster University. Since 1998, he has led the Reactor Analysis group at the McMaster Nuclear Reactor, focusing on experimental and computational nuclear reactor analysis. His research interests include: Reactor physics and safety analysis methodologies Code benchmarking against experimental data Positron beam-line design and optimization Criticality safety and reactor operations Computational simulations of nuclear systems His publications (2010-2024) demonstrate strong focus on reactor physics validation through experimental measurements and simulations. Recent work emphasizes computational fluid dynamics (CFD), gamma heating analysis, fuel depletion calculations, and code benchmarking. The research consistently integrates experimental data with simulation tools like Serpent-2, OSCAR-4, and PARET-ANL for reactor safety and optimization. He leads the Reactor Analysis group at McMaster Nuclear Reactor, conducting research in nuclear instrumentation, safety validation, and reactor operations. No awards, grants, or student advising details are mentioned in available sources.

Michalis Famelisمشاهده پروفایل

استادیار

• Software analysis
• Software design
• Empirical software engineering
• +۳ مورد دیگر

Michalis Famelis is an Assistant Professor at the Department of Computer Science and Operations Research , affiliated with the Faculty of Arts and Sciences at Université de Montréal . He leads research in the GEODES Software Engineering Research Group , focusing on formal yet practical methods for software development. His work integrates formal verification, model-driven engineering, and empirical methods to address challenges in software design and uncertainty management. Educated at the University of Toronto (PhD 2016, MSc 2010) and the National Technical University of Athens (DiplEng 2008), he completed a postdoctoral fellowship at the University of British Columbia . He teaches courses such as IFT1025 Programming 2 and IFT6755 Software Analysis . His research projects include a Wellcome Trust-funded platform for climate-sensitive disease modeling and CRSNG grants for formal software design support. He has supervised 6 master’s students, focusing on topics like design uncertainty, API usage verification, and software product lines. Notable collaborations involve Climate-Sensitive Infectious Disease Modelling and Formal Support for Software Design . His work emphasizes improving developer workflows through tool development and empirical studies.