Find Academic Supervisors

S.F. AsokanthanView profile

Professor

• Dynamic Systems
• Control Theory
• Flexible Structures
• +4 more

S.F. Asokanthan is a Professor in the Department of Mechanical and Materials Engineering at Western University, Canada. His research focuses on Dynamic Systems and Control with applications to Flexible Structures, Rotating/Axially Moving Systems, and MEMS/NEMS. Prior to Western, he held a faculty position at the University of Queensland, Australia, and worked as an NSERC industrial postdoctoral fellow in Canada. Research Interests: Dynamic Systems and Control Flexible Structures and Rotating Systems MEMS/NEMS for Inertial Sensing Energy Harvesting Systems Biological and Aerospace Applications Stochastic Stability Analysis Publication Trends: His recent work (2022-2017) emphasizes nonlinear dynamics of ring-based MEMS gyroscopes and energy harvesters, stochastic stability under random perturbations, and biomedical applications like magnetic seizure therapy. Keywords span Mechanical Engineering, Micro/Nano Systems, and Aerospace Engineering, with subfields including Vibratory Sensors, Uncertainty Quantification, and Nonlinear Modeling. Students: He has supervised numerous PhD and Master's students in topics such as MEMS design, dynamic stability, and biomedical devices.

Clifton van der LindenView profile

Associate Professor

• Artificial Intelligence
• Digital Technology
• Electoral Politics
• +9 more

Dr. Clifton van der Linden is an Associate Professor of Political Science at McMaster University, where he serves as Director of the Digital Society Lab and Academic Director of the Master of Public Policy in Digital Society program. He is also a Visiting Fellow at the Oxford Internet Institute, exploring the interplay between digital technologies and democratic processes. PhD in Political Science (University of Toronto, 2019) MA in Journalism (Western University, 2005) Bachelor of Arts in Economics and Political Science (McMaster University, 2004) His research centers on how digital technologies like artificial intelligence reshape democratic participation, political behavior, and public opinion. He specializes in voting advice applications (e.g., Vox Pop Labs ), electoral politics, and the ethical implications of data-driven governance. Dr. van der Linden’s scholarly output includes 15 recent articles spanning public health policy, political methodology, and transnational integration. His work has been featured in journals like Philosophy & Technology and European Union Politics , with themes ranging from pandemic behavioral analysis to Brexit trade-offs. Adel S. Sedra Distinguished Graduate Award (University of Toronto) Clarkson Laureateship for Public Service (Massey College) Arch Alumni Award (McMaster University) Toronto Region Board of Trade's Entrepreneur of the Year As a serial entrepreneur, Dr. van der Linden has founded multiple tech ventures, including Vox Pop Labs , creator of Vote Compass —a tool used in over 50 elections worldwide. He advises governments on technology policy and frequently contributes to media discussions on elections.

• Interstitial Lung Disease
• Pulmonary Fibrosis
• Lung Injury Mechanisms
• +3 more

Martin Rainer Kolb is a Professor of Medicine at McMaster University's Faculty of Health Sciences, specializing in Interstitial Lung Diseases (ILD) and General Respirology at St. Joseph's Healthcare Hamilton. He serves as Section Editor for ILD in the European Respiratory Journal, one of the top journals in respiratory medicine with an impact factor of 24.9, having previously served as Chief Editor. Dr. Kolb's research focuses on mechanisms of lung injury, repair and fibrosis, particularly in Idiopathic Pulmonary Fibrosis (IPF). His work spans pre-clinical studies of disease mechanisms, efficacy of novel drugs, and biomarker development for lung fibrosis. He actively leads international and national ILD clinical trials as Principal Investigator and Steering Committee member. His scholarly output shows a strong focus on progressive pulmonary fibrosis, with recent publications examining CT patterns, biomarkers, macrophage polarization, drug treatments like nintedanib, and patient pathways in ILD. His work demonstrates a consistent trajectory from basic mechanisms to clinical applications in fibrotic lung diseases. Dr. Kolb has received significant recognition including election to the Canadian Academy of Health Sciences and awards from the Parker B. Francis Families Foundation, Canadian Institute for Health Research, and the National Institute for Health. Parker B. Francis Families Foundation Award Canadian Institute for Health Research Award National Institute for Health Award Fellow of the Canadian Academy of Health Sciences With over 300 peer-reviewed publications, Dr. Kolb maintains an active research program that bridges basic science and clinical applications in pulmonary fibrosis. His leadership extends to journal editorial roles and multicenter clinical trials, significantly influencing the field of interstitial lung disease research and treatment.

Francis DawsonView profile

Professor

• Energy Systems
• Power Electronics
• Signal Processing in Power Engineering
• +4 more

Professor Francis Dawson is affiliated with the Department of Electrical and Computer Engineering at the University of Toronto , under the Faculty of Applied Science and Engineering . He has been active in teaching and research since 1988, focusing on energy systems, power converters, and electromagnetic modeling. PhD in Electrical Engineering (University of Toronto, 1988) MASc in Electrical Engineering (University of Toronto, 1985) BASc in Electrical Engineering (University of Toronto, 1982) BSc in Physics (University of Toronto, 1978) His research spans static power converters , energy storage systems , signal processing in power applications, and electromagnetic compatibility . Recent publications focus on fault current limiters , digital phase-locked loops , and plasma physics , with keywords indicating strong ties to Electrical Engineering and Materials Science . Scientific accolades include: IEEE Fellow Myron Zucker Student Design Project 1st Prize (2012) K. Yamamoto Best Student Paper Award (2007) F. Farahmand 3rd Best Paper Prize (2005) He has collaborated on industrial projects in power electronics and contributed to the Power Group at the University of Toronto.

Yun ZhouView profile

Associate Professor

• Operations Management
• Supply Chain Management
• Revenue Management
• +7 more

Yun Zhou is an Associate Professor in the Department of Operations Management at DeGroote School of Business, McMaster University. His research bridges theoretical operations research with practical applications in supply chain optimization, revenue management, and healthcare logistics. PhD: Rotman School of Management, University of Toronto Doctorate & B.Sc.: Tsinghua University Dr. Zhou specializes in revenue management , supply chain coordination , and dynamic pricing , particularly in on-demand delivery systems and sharing economy platforms . His work addresses uncertainty in demand , perishable product inventory , and healthcare operations challenges like vaccine allocation and surgical scheduling . Recent publications focus on robotic warehouse systems (e.g., rack-moving robots for order picking), price and matching dynamics in sharing economies , and blood supply chain coordination . These span optimization algorithms , stochastic modeling , and empirical retail analytics . SSHRC Grant: Addressing societal challenges through operations research

Pierre L'ÉcuyerView profile

Professor

• Stochastic Systems
• Random Number Generation
• Quasi-Monte Carlo Methods
• +6 more

Pierre L'Écuyer is a Full Professor in the Department of Computer Science and Operational Research at the Faculty of Arts and Sciences, University of Montreal. He holds a Canada Research Chair in Stochastic Simulation and Optimization and is a member of GERAD and CIRRELT research centers. His office is located at André-Aisenstadt building, room 3361, and he can be reached at 514 343-2143. Dr. L'Écuyer received his Baccalauréat in mathematics, Master's in operational research, and PhD in computer science with focus on operational research, all from the University of Montreal. His academic journey has led him to become one of the world's most influential researchers in stochastic simulation. His research focuses on stochastic systems modeling and simulation, with particular expertise in random number generation, quasi-Monte Carlo methods, simulation efficiency improvement, sensitivity analysis, and optimization. His work has practical applications in call centers, finance, communication systems, and revenue management. Analysis of his recent publications shows strong emphasis on randomized quasi-Monte Carlo methods, variance reduction techniques, and applications to complex optimization problems in service systems. Lifetime Professional Achievement Award from INFORMS (2020) Ranked among the most influential researchers worldwide by Mendeley/Elsevier (2019, 2020) ACM SIGSIM Distinguished Contribution Award (2016) Mercit Award from Canadian Operational Research Society (2014) Distinguished Service Award from INFORMS Simulation Society (2011) Urgel-Archambault Prize from ACFAS (2002) Dr. L'Écuyer has supervised numerous PhD and Master's students working on topics ranging from random number generation to call center optimization. His current research projects, funded by NSERC and other organizations, focus on fundamental tools for stochastic simulation, with applications extending through 2030. He leads the SIMUL research laboratory which has developed several important software tools including SSJ (Stochastic Simulation in Java), TestU01, and RNGStreams.

John C. W. LamView profile

Associate Professor

• Power Electronics
• High Frequency Power Converters
• Renewable Energy Systems
• +3 more

John C. W. Lam is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. He serves as the Graduate Program Director for MASc and PhD programs and is a Professional Engineer (P.Eng). His research focuses on power electronics, high-frequency converter topologies, renewable energy systems, and energy storage technologies. Lam directs the Advanced Power Electronics Laboratory for Sustainable Energy Research (PELSER). He is an IEEE Senior Member and an Associate Editor for multiple IEEE journals, including Transactions on Power Electronics and Transactions on Industry Applications. Education: B.Sc. (Hons.) in Electrical Engineering and BA in Economics from Queen’s University (2003), M.Sc. and Ph.D. in Electrical Engineering from Queen’s University (2006, 2010). He completed a Postdoctoral Fellowship at Queen’s ePOWER from 2010–2014 before joining York University in 2014. Research emphasizes high-frequency power converters for renewable energy integration, medium-voltage DC grids, and electric vehicle charging systems. Key contributions include modular resonant converter designs, soft-switching techniques, and fault-tolerant power electronics architectures. His publications (15 most recent listed) explore topics like MVDC distributed PV systems, high-voltage EV chargers, and grid-connected inverter control. He has developed novel topologies for electrolytic capacitor-less converters and modular power balancing techniques. Lam’s lab (PELSER) focuses on sustainable energy research, advancing efficient power conversion solutions for grid, renewable, and transportation applications. He has edited special issues in IEEE/IET journals and holds leadership roles in professional organizations.

Alex TongView profile

Assistant Professor

• Generative Modeling
• Deep Learning
• Optimal Transport
• +4 more

Alex Tong is an incoming Assistant Professor at Duke University (as of 2025) and will join Aithyra in Vienna as a Principal Investigator. Previously, he completed postdoctoral research at Mila under Yoshua Bengio and a visiting postdoc at Oxford with Michael Bronstein. Education : PhD (2021) and MPhil (2020) in Computer Science from Yale University; BS/MS (2017) from Tufts University Research Interests span generative modeling , deep learning , optimal transport , and graph signal processing applied to protein design and single-cell biology . His work bridges mathematical formalism (e.g., SE(3) flows, Wasserstein manifolds) with biological discovery. Publication Trends (2023-2025) focus on diffusion models for protein structure prediction , optimal transport in single-cell analysis , and geometric machine learning for molecular dynamics . Collaborations include labs like Mila, Oxford, and Yale. Awards : Best Paper (Gen Bio @ ICML 2025), Outstanding Paper (DELTA @ ICLR 2025), Best Student Paper (IEEE MLSP 2020)

Amine MhedhbiView profile

Assistant Professor

• Database Management
• Graph-Structured Databases
• Query Optimization
• +4 more

Amine Mhedhbi is an Assistant Professor at Polytechnique Montréal in the Department of Computer Engineering and Software Engineering. He is affiliated with the Institute for Data Valorization (IVADO) and the Software Engineering for Machine Learning Applications (SEMLA) group. His research focuses on data management systems, particularly graph-structured databases, multimodal data engineering, and AI-driven query optimization. Ph.D. in Computer Science from University of Waterloo Former technical advisor to enterprise companies Prior applied research leadership at Distyl AI and internships at Microsoft Research His recent work explores integrating large language models (LLMs) into database systems, optimizing SQL generation, and advancing graph database architectures. Key projects include GraphflowDB and FlockMTL , addressing scalability and declarative semantic applications. Scientific awards include: NSERC Discovery Grant with Discovery Launch Supplement (2025) Cheriton School Distinguished Dissertation Award (2024) Microsoft Research Ph.D. Fellowship (2020) VLDB Best Paper Award (2018) He supervises graduate students in database systems and machine learning applications and serves on program committees for top-tier conferences like VLDB and SIGMOD.

Bin GuoView profile

Assistant Professor

• Parallel and Distributed Computing
• Graph Algorithms
• Graph Mining
• +5 more

Bin Guo is an Assistant Professor at the Computer Science Department of Trent University (since Jan. 2024) and an Adjunct Assistant Professor at the Computing & Software Department of McMaster University. He holds a PhD in Computer Science from McMaster University (2023) and an MSc in Applied Computer Science from Winnipeg University (2018). His research focuses on parallel/distributed computing, graph algorithms, and computer security for data analytics, with notable contributions to federated k-core decomposition and secure distributed algorithms. He teaches courses in database systems, operating systems, and computer security at Trent University and has taught at McMaster University. Education: PhD in Computer Science, McMaster University (2023) MSc in Applied Computer Science, Winnipeg University (2018) Research Interests: Parallel and Distributed Computing Graph Algorithms and Mining Computer Security & Privacy Federated Learning Concurrent Data Structures Advising & Grants: Current advisees: Gregory Prouty, Michael Abiona, Syed Zarif Past advisees: Igor Jardim-Martins, Issec Lee Funding sources: Graduate Teaching Assistantships, Research Fellowships, Trent University Research Development Grants Labs & Teams: Leading research projects in parallel graph algorithms and federated security algorithms Collaborating with McMaster University on PhD/Master's co-supervision

• Machine Learning Systems
• Differential Privacy
• Adversarial Robustness
• +3 more

Mathias Lecuyer is an Assistant Professor at the University of British Columbia (UBC), Department of Computer Science, where he leads the Systopia research group. His research focuses on trustworthy AI systems, including differential privacy, adversarial robustness, and causal machine learning. He holds a PhD from Columbia University and was a postdoctoral researcher at Microsoft Research. Education: PhD in Computer Science, Columbia University Postdoctoral Researcher, Microsoft Research (New York) Research Interests: Privacy-preserving machine learning (Differential Privacy) Certified adversarial robustness via randomized smoothing Causal inference for model generalization Systems for privacy and security in AI Awards: SOSP Distinguished Artifact Honourable Mention (2024) Google Research Award Supervised Students: PhD: Qiaoyue Tang, Saiyue Lyu, Frederick Shpilevskiy MSc: Mishaal Kazmi, Shadab Shaikh, Shiqi He Undergrad: Alain Zhiyanov, Jessica Bator, Ryan Shar, Eric Xiong, Joel Hempel Labs/Teams: Member of UBC S&P, TrustML, and CAIDA research groups.

Mingbin FengView profile

Associate Professor

• Monte Carlo simulation
• Nested simulation
• Derivative pricing
• +7 more

Mingbin (Ben) Feng is an Associate Professor of Actuarial Science at the University of Waterloo's Department of Statistics and Actuarial Science. His research focuses on Monte Carlo simulation design, nested simulation, and applications in risk management, financial engineering, and stochastic optimization. He holds an ASA designation from the Society of Actuaries and a Certified Analytics Professional (CAP) credential. Education: Ph.D. in Industrial Engineering and Management Sciences (Northwestern University, 2016), M.Math in Actuarial Science (University of Waterloo, 2011), and B.Math with Distinction (University of Waterloo, 2010). His academic journey includes internships at AXIS Capital Holdings and The Hong Kong University of Science and Technology. Research Interests: Machine learning, green simulation, derivative pricing, systemic risk, and simulation analytics. Awards: Royal E. Cabell Fellowship, Hickman Scholarship, and Arthur P. Hurter Award. Teaching: Courses include Corporate Finance, Financial Mathematics, and Portfolio Optimization. He advises a diverse group of graduate and undergraduate students, with notable contributions to developing the vamc R package for variable annuity modeling. Key Research Contributions: Innovations in nested simulation efficiency, green simulation methodologies, and applications of machine learning in actuarial science.

Jacquelyn BurkellView profile

Associate Professor

• Cognitive Science
• Technology and Society
• Privacy Studies
• +3 more

Jacquelyn Burkell is an Associate Professor in the Faculty of Information and Media Studies at Western University and currently serves as Associate Vice-President (Research). She holds a PhD in Psychology (Cognitive Science) from Western. Her research focuses on the cognitive and social dimensions of human-technology interaction, including privacy attitudes, digital surveillance, and information behavior. She has led SSHRC partnership grants exploring AI in justice systems and youth privacy online. Notable contributions include studies on privacy policy design, court form accessibility, and the ethical implications of dark patterns in digital interfaces. Dr. Burkell has held leadership roles, including Assistant Dean of Research in FIMS and chair of the Associate Deans (Research) group. Her work spans academic governance, e-access to justice frameworks, and digital literacy advocacy. PhD in Psychology (Cognitive Science), Western University SSHRC Partnership Grants: AI in Justice Systems; Youth Equality & Privacy Key Projects: Privacy policy readability for youth; Dark patterns in digital interfaces Committee Roles: 2016 URB Task Force Steering Committee Research emphasizes empirical studies on technology-mediated interactions, with applications in health information systems, legal documentation, and public policy. Her interdisciplinary approach bridges cognitive science, law, and technology to address societal challenges such as algorithmic bias and privacy erosion. Awards: None explicitly listed in text Grants: Multiple SSHRC grants, including partnership grants Labs/Teams: Collaborates with interdisciplinary teams on AI ethics, digital justice systems, and health informatics. Engages in policy advocacy through initiatives like the Revisiting e-Justice Framework and Digital Inclusion Research.

David GossetView profile

Research Fellow

• Quantum Computing
• Quantum Algorithms
• Computational Complexity
• +3 more

David Gosset is a theoretical quantum computer scientist affiliated with the University of Waterloo and the Perimeter Institute for Theoretical Physics . He focuses on quantum algorithms, computational complexity, and the interplay between quantum many-body systems and computer science. PhD in Physics (Massachusetts Institute of Technology) BSc in Physics and Mathematics (University of British Columbia) His research investigates foundational questions about quantum computation, including the capabilities of shallow quantum circuits, classical simulation techniques, and the application of physics-inspired methods to computational problems. His work spans theoretical physics, quantum information science, and computer science. The trends in his publications emphasize quantum algorithm design, complexity theory, and the computational power of quantum systems. His awards include the Pat Goldberg Memorial Best Paper Award (2016) and the Sherman Fairchild Prize Postdoctoral Fellowship (2015-2016). Pat Goldberg Memorial Best Paper Award (IBM Research, 2016) Sherman Fairchild Prize Postdoctoral Fellowship in Theoretical Physics (Caltech, 2015-2016) Marble Presidential Fellowship (MIT, 2006-2007) Rudi Haering Medal in Physics (UBC, 2006)

• Theoretical Computer Science
• Algorithms
• Logic
• +3 more

Michael Soltys is an Adjunct Professor in the Department of Computing and Software at McMaster University. His work bridges theoretical computer science, algorithms, and practical applications in cybersecurity and education. Research interests include logic, circuit complexity, and pairwise comparisons. Publications span 2002–2021, with recent focus on cloud computing education, digital forensics, and graph theory. Active in academic service through editorial contributions (e.g., Foreword for Franco-Canadian workshop proceedings). His scholarly activity maps to subdisciplines such as Computer Systems Theory, Logic, Discrete Applied Mathematics, and Operations Research. Dr. Soltys' work on pairwise comparisons and clique covers provides foundational insights for decision systems and graph optimization. He has also contributed to cloud curriculum development and malware analysis frameworks. As an educator, he co-authored An Introduction to the Analysis of Algorithms (2018, 2012, 2009), a textbook exploring algorithmic foundations. Current affiliations include the McMaster Experts database, with collaborations across theoretical computer science and applied cybersecurity research.