Find Academic Supervisors

Janet F. WerkerView profile

Professor

• Developmental Psychology
• Language Acquisition
• Speech Perception
• +7 more

Dr. Janet F. Werker is a University Killam Professor and Canada Research Chair at the University of British Columbia , affiliated with the Faculty of Arts and Department of Psychology . She directs the Infant Studies Centre and co-founded the UBC Language Sciences initiative. Her research focuses on perceptual foundations of language acquisition , studying speech perception mechanisms in monolingual and bilingual infants, critical periods of development, and neural correlates using behavioral, ERP, and NIRS methods. Recent work extends to literacy development in multicultural contexts through an SSHRC Partnership Grant. Key themes in 15 most recent articles: Infant brain development, statistical learning, speech perception, bilingualism, musical sophistication, microbiome-brain links, sensorimotor integration, voice recognition, and cross-linguistic generalization. Studies employ EEG, NIRS, and behavioral paradigms to explore early language, social understanding, and neurodevelopmental pathways. Scientific accolades include election to the National Academy of Sciences (2020) , Benjamin Franklin Institute Medal (2024) , and multiple fellowships (AAAS, Royal Society of Canada). Her work is funded by NSERC, SSHRC, NIH, and CIFAR. Dr. Werker supervises graduate students and leads international collaborations examining language acquisition, bilingualism, and developmental disabilities. She is actively involved in pandemic-era research adaptations, emphasizing online methodologies.

Ashish KhistiView profile

Associate Professor

• Communication Systems
• Information Theoretic Security
• Machine Learning
• +4 more

Ashish Khisti is an Associate Professor at the University of Toronto's Department of Electrical and Computer Engineering (ECE), where he directs the Signals, Multimedia and Algorithms Laboratory (SMA Lab). He holds the Canada Research Chair (Tier II) and maintains affiliations with the Vector Institute for Artificial Intelligence. His research bridges communication systems, information-theoretic security, and machine learning, with a focus on real-time streaming and privacy-preserving algorithms. Research Trends: Recent publications emphasize streaming codes for latency-sensitive networks , machine learning-driven compression , and privacy mechanisms in federated learning . Scientific Recognition: Canada Research Chair (Tier II), 2012 and 2017 renewal Cisco Research Center Award, 2017 Ontario Early Researcher Award, 2012 Best Paper at NeurIPS 2021 Deep Generative Models Workshop Academic Contributions: Supervised PhD students Ahmed Badr, Farrokh Etezadi, and Si-Hyeon Lee. Served as Associate Editor for IEEE Transactions on Communications (2012-2015) and IEEE Transactions on Information Theory (2015-2018). Labs & Collaborations: Leads the Signals, Multimedia and Algorithms Laboratory, collaborating with institutions like KAUST, Texas A&M University (Qatar), and the Vector Institute. Organized workshops at BIRS and IEEE conferences.

Sean Victor HumView profile

Professor

• Electromagnetics
• Antenna Design
• Reconfigurable Antennas
• +4 more

Sean Victor Hum is a full-time Professor and the Eugene V. Polistuk Chair in Electromagnetic Design within the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto's Faculty of Applied Science and Engineering. He joined the institution in 2006 and leads the RADIANCE laboratory, focusing on cutting-edge electromagnetic design and antenna systems research. His academic background includes a BSc (1999), MSc (2001), and PhD (2006) in Electrical Engineering from the University of Calgary. During graduate studies (1997–2006), he collaborated with TRLabs on wireless and radio-over-fibre projects, establishing his technical foundation before transitioning to academia. Research interests center on advanced electromagnetic surfaces (e.g., metasurfaces for RF control), reconfigurable antennas (enabling adaptive wireless systems), and space antenna applications (for satellite communications). These areas reflect his commitment to solving real-world challenges in aerospace and telecommunications, with work bridging theoretical electromagnetics and practical hardware implementation. Hum's scientific recognition includes: Northrop Frye Faculty Award (2024) IEEE AP-S R. W. P. King Award (2015, 2017) Ontario Early Researcher Award (2012) Gordon R. Slemon Teaching Award (2011) Early Career Teaching Award (2011) Multiple Departmental Teaching Awards (2007–2017) ASTech Leaders of Tomorrow Award (2006) As an active advisor, he mentors graduate students in the RADIANCE laboratory, though specific names are unlisted. His professional service includes editorial roles at IEEE Transactions on Antennas and Propagation (2010–2016) and IEEE Antennas and Propagation Magazine (2018–present), alongside chairing the IEEE AP-S Education Committee. Grant details are absent, but the Ontario Early Researcher Award implies successful funding acquisition. The RADIANCE laboratory serves as his primary research hub, driving innovation in electromagnetic surface technologies and space antenna systems for next-generation communication networks.

David A. JohnsView profile

Professor

• Analog Integrated Circuits
• High-Speed Data Communications
• Data Converters
• +15 more

David A. Johns is a Full Professor at the Department of Electrical and Computer Engineering within the University of Toronto . His career spans academic and industrial contributions to analog integrated circuits and high-speed communication systems. Co-founder of Snowbush Microelectronics (integrated circuit IP company) IEEE and Canadian Academy of Engineering Fellow Recipient of Darlington Best Paper Award and multiple teaching/design accolades Research Interests include analog integrated circuits for digital communication, data converters, phase-locked loops, and signal processing. His work bridges theoretical concepts with hardware implementation, focusing on full-duplex coax/twisted-pair systems, optical wireless links, and MEMS sensor interfaces. Teaching Contributions cover analog/digital electronics courses like ECE331, ECE354, ECE1371, and ECE1392. He emphasizes hands-on design and simulation tools like LTSpice. Awards & Recognitions : IEEE Fellow (2001) CAE Fellow (2012) Darlington Best Paper Award (1999) University of Toronto ECE Teaching Award (1999) CMC Design Award (1993) Advising involves 19 PhD/MASc theses on topics ranging from oversampling filters to low-power ADCs. His group has produced innovations in continuous-time modulators, MEMS accelerometers, and optical interconnects.

Lacra PavelView profile

Professor

• Game Theory
• Control Theory
• Optimization
• +7 more

Lacra Pavel is a Professor in the Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto, Faculty of Applied Science and Engineering. She joined the department in August 2002 after industry experience at Nortel Networks and Solinet Systems, and remains active in the System Control Group and Photonics Group. Her educational background includes: Diploma of Engineering (with distinction) in Automatic Control, Technical University Gh. Asachi of Iasi, Romania (1989) PhD in Electrical and Computer Engineering, Queen's University at Kingston (1996) Research focuses on integrating game theory, control theory, and optimization within networked systems. She pioneered applications in noncooperative/evolutionary game theory for network control, nonlinear/robust control frameworks, and energy-efficient optical/transportation networks. Current work develops mathematical foundations for learning in games via control-theoretic approaches to enable autonomous multi-agent network optimization. Recent publications (2019-2013) reveal dominant trends: distributed Nash equilibrium seeking using passivity-based and operator-splitting methods, stability analysis for optical network power control with time-delays, and extensions to transportation systems like railway timetabling. Key subfields include graphical games, ADMM algorithms, and Lyapunov-based boundary control for distributed parameter systems. Scientific recognition includes: Fellow of the IEEE (2025) for contributions to game theory, control, and optimization for network systems Connaught New Staff Award, University of Toronto (2003) New Opportunities Infrastructure Award, CFI/OIT (2003) Award for Innovation, Solinet Systems (2001, 2002) Inventor Recognition Award, Nortel Networks (2000) She has advised over 20 graduate students including current PhD candidates and former students now at MIT, Princeton, Amazon, and Ciena. Major grants include the CFI/OIT New Opportunities Infrastructure Award (2003). Her research bridges theoretical game control with practical implementations in optical and transportation networks. As co-director of the System Control Group and member of the Photonics Group, she leads teams developing algorithms for autonomous network optimization. Current projects focus on stochastic approximation methods for multi-agent learning and energy-efficient network design.

Sarah Ben AmorView profile

Professor

• Multi-Criteria Decision Making (MCDM/MCDA)
• Operations Research
• Decision Support Systems
• +5 more

Sarah Ben Amor is a Full Professor at the Telfer School of Management , University of Ottawa, with a PhD in Business Administration specializing in Operations and Decision Support. Her academic journey includes a B.A. from the University of Quebec in Outaouais (UQO), and M.Sc. and Ph.D. from Université Laval (uLaval). Fields of Interest : Multi-Criteria Decision Making (MCDM/MCDA), Operations Research, Decision Support Systems, Uncertainty Modeling, Risk Analysis Her research focuses on handling information imperfections in decision-making processes, particularly through multi-criteria analysis and stochastic modeling . Recent works include the development of hierarchical stochastic VIKOR methods, assessment of learning methodologies, and applications in healthcare and pharmaceutical decision-making. Her publication trends reveal a strong emphasis on multi-criteria frameworks for uncertain environments, spanning sustainable manufacturing , clinical decision-making , and portfolio analysis . Collaborative works appear in journals like Applied Soft Computing and Osteoarthritis and Cartilage . She has secured significant funding including: NSERC Grant (2019-2024): $130,000 Telfer School Grants : $6,000 (2014-2018) and $4,000 (2021-2022) Her educational contributions include teaching quantitative methods and developing decision-making models for defense, healthcare, and sustainability sectors, with international collaborations spanning Canada, Brazil, and Europe.

Paul CisekView profile

Professor

• Cognitive Neuroscience
• Computational Neuroscience
• Motor System
• +5 more

Paul Cisek is a Full Professor in the Department of Neuroscience at the Faculty of Medicine, University of Montreal. His research laboratory focuses on understanding how the brain controls behavior through the integration of decision-making and motor planning processes in the cerebral cortex. His work challenges traditional models that treat perception, decision-making, and action as separate serial processes. Dr. Cisek received his Baccalauréat in Computer Science from Rochester Institute of Technology (1991), followed by a Doctorat in Neurosciences and Physiologie from Boston University (1997). He completed postdoctoral training at both Université de Montréal and Queen's University (1996-2001). His research program centers on developing a theoretical framework describing how the brain interacts with the external world, with specific focus on how decision-making and motor planning processes are integrated in the primate cerebral cortex. Through his 'affordance competition hypothesis,' Cisek proposes that the brain operates through parallel processes where potential actions compete for selection rather than following a serial perception-decision-action model. His lab conducts behavioral, neurophysiological, and computational research, often using primate models to study neural mechanisms of real-time decision-making. The analysis of Dr. Cisek's recent publications reveals a strong focus on evolutionary perspectives in neuroscience, neural mechanisms of decision-making under time pressure, and the integration of biomechanical constraints in action selection. His work bridges cognitive neuroscience, motor control, and computational modeling to develop a more comprehensive understanding of how the brain selects and executes actions in dynamic environments. Dr. Cisek has been continuously funded by major Canadian research agencies including CIHR, NSERC, and FRQS since at least 2002 for his interdisciplinary studies of decision-making and motor planning. His current projects include 'Neural mechanisms of decision-making during natural interactive behavior' (2025-2031) and 'EthoLab: A platform for neurophysiological studies of natural behavior' (2025-2028). As an educator, Dr. Cisek has supervised numerous graduate students to completion of their degrees and currently teaches courses including NSC-3003 (Perception, action et neurocomputation), NSC-3084 (Neurosciences computationnelles), and NSC-6084 (Neurosciences computationnelles). His lab currently includes doctoral students, master's students, and postdoctoral fellows working on various aspects of decision neuroscience. Dr. Cisek is affiliated with several research groups including SNC (Groupe de recherche sur la signalisation neurale et la circuiterie), GRSV (Groupe de recherche en sciences de la vision), and CIRCA (Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage). His laboratory develops sophisticated experimental platforms for studying neural mechanisms of decision-making, including virtual reality environments for neurophysiological studies of natural behavior.

• Data Mining
• Machine Learning
• Product Recommendation
• +5 more

Christian Desrosiers is a Research Professor at the Department of Software Engineering and IT, École de technologie supérieure (ÉTS), with a Ph.D. from Polytechnique Montréal. His research focuses on data mining, machine learning, and computer vision, particularly in medical imaging and optical network analysis. Research Units: Zebra Research Chair in Computer Vision for Industrial Applications, LIVE – Interventional Imaging Laboratory, LIVIA – Imaging, Vision and Artificial Intelligence Laboratory Research Axes: Intelligent and autonomous systems, Health technologies His expertise spans medical image analysis, domain adaptation, and computer vision. Recent publications highlight advancements in 3D point cloud learning, MRI harmonization, domain generalization, and real-time segmentation networks. Scientific awards include the prestigious Zebra Research Chair. He has co-supervised over 30 graduate students in topics ranging from optical network diagnostics to brain imaging and machine learning applications.

Patrick DesrosiersView profile

Adjunct Professor

• Dimensionality Reduction
• Dynamical Systems
• Mathematical and Computational Neuroscience
• +8 more

Patrick Desrosiers serves as an Adjunct Professor in the Department of Physics, Physical Engineering and Optics within Université Laval's Faculty of Science and Engineering, while conducting neuroscience research at the CERVO Brain Research Center. He co-directs Dynamica, a multidisciplinary complex systems research group, and participates in UNIQUE (neuroscience-AI integration) and CIMMUL (mathematical modeling applications). His academic training spans physics and mathematics at Université Laval, the University of Melbourne, and CEA-Saclay. Dr. Desrosiers' research centers on mathematical and computational neuroscience , with signature contributions in dimensionality reduction and network resilience analysis . His work bridges biological and artificial neural networks , zebrafish brain mapping , and neurovascular coupling using advanced techniques from spectral graph theory , random matrix theory , and dynamical systems . Current investigations focus on neural decoding under chronic stress and structural-functional relationships in brain networks. Analysis of his 2023-2025 publications reveals three dominant trajectories: (1) Low-dimensional representations for predicting cognitive decline and neural dynamics, (2) Network reconstruction methodologies applied to neuroscience and biodiversity, and (3) Development of computational tools like NeuroTorch for neural data analysis. His work consistently integrates mathematical rigor with biological relevance across species and scales. His recognition includes: Professeur étoile prize for exceptional teaching (Faculty of Science and Engineering, Université Laval, 2018) As Dynamica co-director, he mentors a research team comprising Antoine Légaré, Arthur Légaré, Benjamin Claveau, Jordan Charest, Marziyeh Pourmousavi, Pierre-Luc Larouche, Vincent Savard, Vincent Thibeault, and Zahra Yazdani. His collaborative framework connects physics, mathematics, and neuroscience to address fundamental questions in neural network organization, with funding evident through sustained publication output and lab operations. Dynamica Lab ( https://dynamicalab.github.io/ ) serves as the operational hub for his interdisciplinary research, maintaining active collaboration with CERVO Brain Research Center and international institutions.

Sylvain G. CloutierView profile

Professor

• Nanotechnologies
• Nanomaterials
• Nanostructures
• +8 more

Sylvain G. Cloutier is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS) in Montreal, Canada, where he holds the Canada Research Chair in Inkjet-Printed Materials and Flexible Hybrid Electronic Devices. He also serves as an Adjunct Assistant Professor in the Department of Electrical and Computer Engineering at the University of Delaware. His research focuses on developing novel nanomaterials and fabrication techniques for printed electronics applications. Cloutier earned his Ph.D. in Engineering from Brown University in 2006, followed by an M.S. in Physics and B.Eng. in Engineering Physics from Université Laval in 2003 and 2001, respectively. He previously held a faculty position at the University of Delaware before joining ÉTS in 2011. His research interests span nanotechnologies, nanomaterials, nanostructures, nanofabrication, optical micro-spectroscopy, and optoelectronic devices including light-emitting diodes and photovoltaic cells. He has pioneered work in inkjet-printed materials and flexible hybrid electronic devices, with applications in solar cells, light-emitting diodes, photodetectors, thermoelectric converters, and sensors. His research integrates photonic processing techniques with printed electronics to create next-generation optoelectronic devices. Analysis of his recent publications reveals a strong focus on printed electronics, particularly using perovskite materials for solar cells, photonic curing techniques for material processing, flexible sensors, and integration of machine learning for device optimization. His work bridges fundamental nanomaterials research with practical applications in renewable energy and sensing technologies. Scientific Awards: Outstanding Thesis Award from Brown University (2006) DARPA Young Faculty Award (2009) Cloutier has supervised over 25 graduate students across various projects related to printed electronics, nanomaterials, and optoelectronic devices. His research has been supported by numerous grants from organizations including NSERC, FRQNT, NSF, and DOE. He regularly serves as an examiner for major research funding agencies in Canada and the United States. He leads the Canada Research Chair in Inkjet-Printed Materials and Flexible Hybrid Electronic Devices, which focuses on developing low-cost hybrid optoelectronic nanomaterials that can be integrated into simple device architectures for various applications. His research team develops new fabrication and characterization tools for studying optoelectronic materials, with emphasis on controlled nano-fabrication, large-scale manufacturing at low cost, and contact-free 3D micro-spectroscopy techniques.

Kuljeet KaurView profile

Professor

• Cloud Computing
• Edge/Fog Computing
• Internet of Things (IoT)
• +7 more

Kuljeet Kaur is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS) in Montreal, Canada. Her research is conducted through the LACIME (Communications and Microelectronic Integration Laboratory), a renowned research unit focusing on communications and microelectronic integration. She maintains an active research program with numerous publications and student supervision activities. Professor Kaur's research spans multiple interconnected domains focused on next-generation computing and communication systems. Her primary research axes include Sensors, Networks and Connectivity; Intelligent and Autonomous Systems; and Software Systems, Multimedia and Cybersecurity. Within these broad areas, she specializes in Cloud Computing, Edge/Fog Computing, Internet of Things (IoT), Cybersecurity, Privacy, Federated Learning, and Energy Management. Her work bridges theoretical foundations with practical implementations in intelligent transportation systems, healthcare applications, and smart grid technologies. Analysis of Professor Kaur's recent publications reveals a strong focus on security and privacy challenges in emerging computing paradigms. A significant portion of her work addresses federated learning approaches that maintain data privacy while enabling collaborative AI model training. Her research also demonstrates expertise in edge computing architectures, particularly for IoT applications, with emphasis on energy efficiency and security. The publications show consistent interdisciplinary collaboration across computer science, electrical engineering, and transportation domains. Professor Kaur actively supervises multiple graduate students at various levels. Her supervision portfolio includes doctoral candidates working on topics like decentralized AI networks and secure federated learning, as well as master's students focusing on edge AI for IoT applications, sensor drift compensation, and zero trust architecture for IoT. She also guides project students working on practical implementations of AI for smart grid optimization and secure IoT protocols. Her research is conducted within the LACIME laboratory, which brings together researchers working on everything from micro- and nanofabrication processes to communication protocols and signal processing. The lab provides a transdisciplinary environment where Professor Kaur's work on cyber-physical systems and secure communications benefits from complementary expertise in integrated circuit design and microsystems.

Andy ShihView profile

Professor

• Organic semiconductor devices
• Microfabrication & nanofabrication
• Printed and flexible electronics
• +5 more

Andy Shih is a Professor in the Department of Electrical Engineering at École de technologie supérieure (ÉTS) in Montreal, Canada. He holds a B.Eng. and M.Eng. in Electrical Engineering from McGill University and a Ph.D. in Electrical Engineering from Massachusetts Institute of Technology. His research is conducted at the LaCIME (Communications and Microelectronic Integration Laboratory), where he focuses on innovative materials and advanced manufacturing. Dr. Shih's research interests span organic semiconductor devices, microfabrication & nanofabrication, printed and flexible electronics, sustainable electronic materials, organic transistors and sensors, soft MEMS, AI-enhanced sensing, and biomedical monitoring technologies. His work bridges materials science, electrical engineering, and biomedical applications, with particular emphasis on developing smart bandages, printed sensors, and flexible electronics for healthcare monitoring. His publications reveal a strong focus on organic electronics, sensor development, and biomedical applications, with increasing integration of AI techniques for sensor enhancement and data analysis. Dr. Shih teaches courses including Electromagnetism (ELE312), Microsystem Fabrication Processes (ELE676), and Photovoltaic Solar Energy Systems (ENR889). His supervision portfolio includes numerous doctoral and master's students working on diverse projects spanning printed electronics, MEMS, sensor development, AI applications in sensing, and photovoltaic systems. His research has resulted in multiple patents related to thin-film transistors, acoustic resonators, and sensor technologies.

• Elastography Imaging
• Inverse Problems
• Nonlinear Optimization
• +7 more

Elijah Van Houten is a Full Professor at Université de Sherbrooke , Canada, specializing in Biomedical Engineering and Medical Imaging . His research focuses on Magnetic Resonance Elastography (MRE) , inverse problems, and nonlinear optimization for tissue mechanical property characterization. He is affiliated with the Centre de recherche du CHUS and leads international collaborations, including the Netherlands-funded VICI project Seismology of the Brain and NIH-funded High-Resolution, Anisotropic MR Elastography of the Brain . Doctorate in Engineering Science, Dartmouth College (2001) Bachelor's in Music and Mechanical Engineering, Tufts University (1997) Van Houten’s work integrates computational modeling, finite element analysis, and advanced imaging to study brain and liver tissue mechanics. Recent publications highlight applications of transversely isotropic models , poroelasticity , and multi-frequency MRE for improved diagnostic imaging. His research has been supported by grants from NIH , NWO , CIHR , and NSERC , totaling over $7 million. Scientific awards include the ISMRM Summa Cum Laude award . He has supervised projects on diabetic foot ulcers , breast cancer detection via wearable technology , and ultrasound-based liver disease diagnostics . Van Houten collaborates with institutions in the Netherlands, USA, France, and Mexico, advancing MRE techniques for clinical applications.

Joshua M. PearceView profile

Professor

• Renewable Energy
• Open Source Hardware
• 3D Printing
• +3 more

Dr. Joshua M. Pearce is a Professor at Western University, holding appointments in the Department of Electrical & Computer Engineering and the Ivey Business School. He is the John M. Thompson Chair in Information Technology and Innovation at the Thompson Centre for Engineering Leadership & Innovation and a Fellow of the Canadian Academy of Engineering. His research focuses on open-source appropriate technology for sustainability and poverty reduction, spanning solar photovoltaics, 3D printing, distributed recycling, and policy analysis. Ph.D. in Materials Engineering from Pennsylvania State University Former Richard Witte Professor at Michigan Tech Editor-in-Chief of HardwareX Author of multiple open-source sustainability books His work integrates engineering, economics, and policy to solve global sustainability challenges. Recent projects include agrivoltaic systems, open-source medical devices, and climate-resilient food production frameworks. He leads the Free Appropriate Sustainability Technology (FAST) research group, which has produced over 200 open-access publications cited in top-tier journals like Renewable and Sustainable Energy Reviews (IF=16.3) and HardwareX (IF=2). Dr. Pearce's scientific contributions include: Fulbright-Aalto University Distinguished Chair Top 0.06% most cited scientist (Elsevier metrics) Leading open-source hardware certification frameworks Developing low-cost scientific instruments His research team includes cross-disciplinary collaborators from Mechanical Engineering, Environmental Science, and Policy Studies. The FAST group emphasizes practical open-source solutions for energy, water, and food security in both developed and low-resource contexts.

• Orthopaedic Biomechanics
• Knee Mechanics
• Ligament Injury
• +9 more

Naveen Chandrashekar is an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo. His work bridges orthopaedic biomechanics, biomedical device design, and tissue engineering with significant contributions to understanding anterior cruciate ligament (ACL) injuries. Doctorate in Mechanical Engineering (2005, Texas Tech University) Master's in Mechanical Engineering (2003, Texas Tech University) Bachelor's in Mechanical Engineering (2000, Bapuji Institute of Engineering and Technology) Research focuses on: Knee mechanics and ACL injury prevention Development of human knee simulators Sensor-integrated ligament damage measurement Virtual laboratory pedagogy effectiveness Tissue engineering applications Implant design and fixation devices Recent publications examine ACL strain mechanics, knee brace efficacy, and cervical spine dynamics. Key funding sources include: Natural Sciences and Engineering Research Council of Canada Ontario Centres of Excellence Canada Foundation for Innovation Scientific accolades include awards from Pi Tau Sigma, ASME, and Texas Tech University. Teaching portfolio covers core mechanical engineering subjects including: Mechanics of Deformable Solids (BME 281, ME 220) Finite Element Methods (ME 559) Statics (MTE 119)