Find Academic Supervisors

Philip FergusonView profile

Associate Professor

• Satellite guidance and control
• CubeSats
• Drone control and navigation
• +3 more

Dr. Philip Ferguson is an Associate Professor of Mechanical Engineering and Magellan Industrial Research Chair at the University of Manitoba's Price Faculty of Engineering. He leads the Space Technology and Advanced Research Laboratory (STARLab) and collaborates with the Centre for Earth Observation Science (CEOS). His work focuses on making aerospace technology accessible through low-cost, reliable solutions for Arctic communities and search-and-rescue operations. Dr. Ferguson holds a PhD from MIT and has industry experience with Magellan Aerospace and PrecisionHawk Inc. Education: PhD in Aerospace Engineering, MIT (2006) SM in Aerospace Engineering, MIT (2003) B.A.Sc. in Engineering Science (Aerospace Option), University of Toronto (2000) Dr. Ferguson's research spans satellite guidance, drone navigation, Arctic remote sensing, and machine learning. His projects include CubeSats for climate change monitoring, drones for search-and-rescue, and airships for Arctic communications. He emphasizes interdisciplinary collaboration to address challenges in Northern Canada and Indigenous communities. His recent articles explore fault detection in spacecraft systems, drone-based payload control, and innovative navigation algorithms. He actively recruits graduate students interested in advancing aerospace accessibility. Labs/Teams: STARLab (founded 2014), CEOS collaborations, and industry partnerships with Magellan Aerospace.

• Operations and Supply Chain Management
• Market Studies
• Assessment and Optimization in Management
• +4 more

Raga Gopalakrishnan is an Assistant Professor of Operations Management at the Smith School of Business, Queen's University. His research bridges game theory, optimization, and stochastic modeling to analyze strategic interactions in service systems and market environments. He holds a Ph.D. in Computer Science from the California Institute of Technology (2013), preceded by an M.S. (2010) and B.Tech. (2008) from Caltech and IIT Madras, respectively. Professional Experience: Postdoctoral appointments include the University of Colorado Boulder (2013–2015) and Cornell University (2017–2019), with visiting roles at USC Marshall School of Business and Cornell ORIE. Prior to academia, he worked at Conduent Labs India (formerly Xerox RCI) in algorithms and optimization. Research Interests: Focuses on strategic trade-offs in service systems, market dynamics, mathematical optimization, and stochastic models. Key areas include bilevel optimization, game theory applications, and algorithmic mechanisms for resource allocation. Publications: Recent work addresses strategic server behavior in queueing systems, profit optimization in ridesharing, and distributed resource allocation. His research spans operations management, transportation systems, and multi-agent systems. Grants & Advising: No specific grants or advisees listed in the provided materials. Labs/Teams: Engaged with interdisciplinary teams at Cornell, CU Boulder, and industry collaborations through Conduent Labs.

Michael SicilianoView profile

Assistant Professor

• Labor Studies
• Media Studies
• Technology and Society
• +3 more

Michael Siciliano is an Assistant Professor in the Department of Sociology at Queen's University, part of the Faculty of Arts and Science. He holds a PhD from the University of California, Los Angeles (2017), an M.A. from the University of Chicago (2010), and a B.A. in Film Studies from the University of Pittsburgh (2004). Previously, he served as a postdoctoral fellow at the University of Southern California (2018–2019). His research focuses on labor dynamics, media, and technology within cognitive capitalism. Key areas include creative industries, platform-based work (e.g., YouTube), and the interplay between managerial control and worker experiences. He explores themes such as alienation, metrics-driven labor, and the aesthetic dimensions of work environments. Siciliano’s work combines ethnographic studies with sociological theory. Recent studies include analyses of music production studios, YouTube multi-channel networks, and digital publishing analytics. His book Creative Control (2021) examines contradictions in creative labor and its exploitation under contemporary capitalism. His articles address topics like infrastructural barriers to cultural participation, platformized creative labor’s political potential, and the role of intermediaries in digital ecosystems. He emphasizes how technology shapes worker subjectivity and resistance possibilities.

• Wireless Communication Systems
• Real-Time Scheduling
• Reinforcement Learning
• +4 more

Dr. Ning Lu is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen's University, Canada, and holds a Canada Research Chair Tier II in Future Communication Networks. He specializes in real-time scheduling, distributed algorithms, and reinforcement learning for wireless communication networks, with expertise in vehicular networks, IoT, and autonomous systems. Education : PhD in Electrical Engineering (2015), University of Waterloo MEng in Electrical Engineering (2010), Tongji University BEng in Electrical Engineering (2007), Tongji University Research Focus : Dr. Lu's work bridges theoretical foundations and practical applications in wireless networks, including vehicular communication protocols, energy-efficient systems, and AI-driven network optimization. His recent efforts emphasize autonomous vehicle motion forecasting, secure federated learning, and smart infrastructure for 6G/IoT. Publications Trends : His articles focus on cutting-edge topics like vehicular networks, reinforcement learning for edge computing, and robust AI models against adversarial attacks. Notable themes include multi-agent systems, dynamic scheduling, and hybrid communication architectures. Awards : Canada Research Chair Tier II (202X) NSERC Postdoctoral Fellowship (2015) Best Paper Award at IEEE GLOBECOM 2014 2nd Place, Valeo Innovation Challenge 2014 Contributions : He leads research on network slicing, emergency communication systems, and AI-driven traffic prediction. His work has been applied to disaster response frameworks and smart city infrastructure projects. He serves on the editorial board of Springer's Encyclopedia of Wireless Networks.

Jean HutchinsonView profile

Professor

• Geotechnical Engineering
• Geomechanics
• Rock Engineering
• +5 more

Dr. Jean Hutchinson is a Professor in the Department of Geological Science and Geological Engineering at Queen's University, Canada. She previously served as Head of Department (2009-2017) and holds a cross-appointment as Research Director at the GeoEngineering Centre. Her research focuses on geohazard risk assessment, remote sensing technologies (LiDAR, photogrammetry), and rock engineering applications in transportation and mining sectors. She leads the Canadian Railway Ground Hazard Research Program, funded by NSERC, CP Rail, CN Rail, and Transport Canada. Education: PhD (1992) Rock Engineering – University of Toronto M.A.Sc (1988) Geotechnical Engineering – University of Alberta B.A.Sc (1984) GeoEngineering, Geotechnical Option – University of Toronto Research Interests: Dr. Hutchinson specializes in multi-criteria risk management for geological projects, particularly using advanced remote sensing techniques to characterize rock masses and monitor slope stability. Her work includes landslide mechanisms, mine closure planning, and railway corridor hazard assessment. She advocates for innovative applications like game-engine simulations for rockfall modeling and DAS technology for subsurface deformation analysis. Grants & Collaborations: Her research is supported by industry partnerships and national funding agencies. She is Principal Investigator on the Canadian Railway Ground Hazard Program and has pioneered integration of TLS and photogrammetry for slope monitoring. She also chairs several national committees including the NSERC Discovery Grant Selection Panel and the Canadian Foundation for Geotechnique. Labs & Affiliations: As Research Director at Queen's GeoEngineering Centre, she oversees interdisciplinary projects. She is Vice-President of the International Association for Engineering Geology and Environment (IAEG) and editorial board member for Environmental and Engineering Geoscience .

• Machine Learning
• Neural Computing
• Computer Vision
• +4 more

Hazem Abbas is a Continuing Adjunct Professor at Queen’s University’s School of Computing within the Faculty of Arts and Science. His research focuses on machine learning, neural computing, and their applications in computer vision, image processing, and natural language processing. He holds a Ph.D. in Electrical and Computer Engineering from Queen’s University and has held leadership roles, including Department Chair at Ain Shams University and Dean of Media and Engineering Technology at the German University in Cairo. Education: B.Sc. and M.Sc. in Computer Engineering, Ain Shams University, Cairo, Egypt Ph.D. in Electrical and Computer Engineering, Queen’s University, Canada Research Interests: Machine learning model development Neural computing for computer vision and NLP Evolutionary algorithms in neural network design Systems and networks optimization His recent articles explore topics like large language models, federated learning, 5G networks, and bioinformatics applications. Notable contributions include frameworks for robust visual tracking and secure vehicular networks. Scientific Awards: Senior Member, IEEE Prof. Abbas has collaborated on grants related to cloud computing optimization and neural cryptography. He chairs IEEE Signal Processing and IAPR Technical Committees, reflecting his leadership in pattern recognition research. His work spans lab initiatives in analog layout automation and cybersecurity for IoT systems.

Samer Al-KiswanyView profile

Associate Professor

• Data Center Optimization
• Cloud Computing
• Serverless Computing
• +3 more

Samer Al-Kiswany is an Associate Professor in the Department of Computer Science at the University of Waterloo. His research focuses on optimizing modern data center and cloud architectures, leveraging advancements in networking, storage, and processing to enhance system efficiency and performance. He holds a Ph.D. (2013) and M.Sc. (2008) from the University of British Columbia and a B.Sc. (2003) from Jordan University of Science and Technology. Research Interests: Dr. Al-Kiswany’s work emphasizes cloud-native paradigms (serverless, disaggregated architectures), data deduplication, network-accelerated scheduling, and fault-resilient systems. His projects include developing software stacks for efficient cloud applications and benchmarking frameworks for edge and serverless computing. Publications: His recent work spans innovations in data deduplication (e.g., VectorCDC, SeqCDC), network-accelerated scheduling (Draconis, Falcon), and fault tolerance (CASPR). Over 30 publications demonstrate expertise in storage systems, distributed computing, and networking. Awards: No awards explicitly listed in provided texts. Grants & Advising: No student advisees or grant details provided. His research is supported through university and collaborative projects. Labs/Teams: Involved in cloud systems and distributed computing research groups at the University of Waterloo.

Gladimir V. G. BaranoskiView profile

Professor

• Computer Graphics
• Biomedical Optics
• Remote Sensing
• +2 more

Gladimir V.G. Baranoski is a Professor at the University of Waterloo, Canada, with a research focus on predictive simulation of light interactions with organic and inorganic materials. His work bridges computer graphics, biomedical optics, and remote sensing, emphasizing realistic material appearance modeling. BSc, BSc, MSc (UFRGS - Brazil) MSc (Indiana) PhD (Calgary) His research spans three primary domains: Biomedical Optics (e.g., skin cancer detection, blood oxygenation monitoring), Remote Sensing (e.g., environmental impact on vegetation, Martian terrain analysis), and Computer Graphics (e.g., snow rendering, iris dynamics). Recent articles highlight interdisciplinary applications in climate science and medical diagnostics. Media coverage includes Waterloo News , NSERC Research Stories , and City News , acknowledging his work on snow modeling and ecosystem monitoring. Despite no explicit awards listed, his extensive publication record demonstrates significant contributions to computational biophysics and spectral modeling.

Yash Vardhan PantView profile

Assistant Professor

• Control Theory
• Formal Methods
• Machine Learning
• +5 more

Yash Vardhan Pant is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. He leads the Control, Learning and Logic (CL²) group, focusing on integrating Control Theory, Formal Methods, Machine Learning, and Optimization to ensure safe autonomy in robotic and cyber-physical systems. Prior to this, he was a Postdoctoral Fellow at UC Berkeley under Professors Sanjit Seshia and Rahul Mangharam, and earned his PhD in Electrical Engineering from the University of Pennsylvania under Prof. Rahul Mangharam. His research emphasizes computationally efficient solutions for real-world problems, with implementations on platforms such as quadrotors, autonomous vehicles, and hybrid powertrains. Key themes include safe autonomy, decentralized control, and human-autonomy interaction. He serves as Publicity Chair for IEEE/ACM ICCPS 2022 and has advised students including Leroy, Zhao Feng, and Soroush. His work addresses challenges in urban air mobility, mixed traffic safety, and distributed traffic management. Pant's recent publications explore topics like model predictive control for autonomous systems, learning-based collision avoidance, and formal scenario testing for autonomous vehicles. He has developed tools such as Fly-by-Logic for multi-drone fleet planning and contributed to open-source platforms like the F1/10 autonomous vehicle platform. Education: PhD in Electrical Engineering, University of Pennsylvania (2021) Postdoctoral Fellowship, UC Berkeley (2019–2021) Research Interests: Safe Autonomy, Cyber-Physical Systems, Formal Methods, Reinforcement Learning, Autonomous Vehicle Control. Labs/Teams: CL² Group, VeHICaL Project (UC Berkeley), Real-Time and Embedded Systems Lab (UPenn).

Eric BlaisView profile

Associate Professor

• Randomized Algorithms
• Sublinear-Time Algorithms
• Complexity Theory
• +3 more

Eric Blais is an Associate Professor in the Department of Computer Science at the University of Waterloo. His research focuses on randomized algorithms, sublinear-time algorithms, and complexity theory, with particular emphasis on property testing and algorithmic efficiency. He holds a Ph.D. from Carnegie Mellon University, an M.Sc. from McGill University, and a B.Math from the University of Waterloo. His work explores theoretical foundations of algorithms, including minimax theorems, VC dimension analysis, and convexity testing. Recent contributions span graph testing via container methods, randomized composition techniques, and polynomial lower bounds for monotonicity testing. His research also intersects with practical applications in graphics processing and database systems. No scientific awards are explicitly listed in the provided text. His advising record is not detailed here, but he has contributed to conference proceedings like APPROX/RANDOM and ITCS. His work often bridges theoretical insights with real-world algorithmic challenges, emphasizing both foundational results and applied system optimizations.

Catherine RosenbergView profile

Professor

• Wireless Networks
• Internet Systems
• Multimedia Communication
• +1 more

Catherine Rosenberg is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo. She holds the Cisco Research Chair in 5G Systems (since 2018) and was a former Canada Research Chair in Future Internet (2010–2024). Her career spans academia and industry, including roles at ALCATEL, AT&T Bell Labs, and Nortel Networks. She co-founded the Center for Wireless Systems and Applications (CWSA) at Purdue University and served as Chair of Waterloo’s ECE Department from 2004–2007. Education: 1986: Doctorate in Computer Science, Université de Paris XI (Orsay), France 1984: Master of Science in Computer Science, UCLA, USA 1983: Diplôme d'Ingénieur en Télécommunications, École Nationale Supérieure des Télécommunications de Bretagne, France Research Interests: Wireless Networks (5G, IoT), Internet, Multimedia, and Energy Systems. Her work focuses on optimizing network performance, energy systems integration, and bridging the digital divide through innovative communication technologies. Recent Trends in Publications: Recent articles explore hybrid beamforming, 5G standalone testbeds, distributed generation systems, and multi-user MIMO optimization. These reflect a focus on advancing next-gen wireless infrastructure and sustainable energy solutions. Awards: IEEE Fellow Fellow of the Canadian Academy of Engineering (2013) Advising & Grants: Currently advising graduate students in wireless systems and energy networks. Her research has been supported by industry and government grants, including roles in the Orange Group Scientific Advisory Board and the French IRT BCOM. Labs & Teams: Co-founded the Center for Wireless Systems and Applications (CWSA). Active in interdisciplinary projects involving smart grids, 5G testbeds, and network optimization.

• Artificial Intelligence
• Multiagent Systems
• Trust and Reputation Models
• +6 more

Robin Cohen is a Professor in the Department of Computer Science at the David R. Cheriton School of Computer Science, University of Waterloo. His research focuses on artificial intelligence, multiagent systems, trust and reputation models, user modeling, and the social implications of technology. He has held leadership roles including Associate Dean (Research) in the Faculty of Mathematics and Director of the BBA/BCS Program. Cohen has a Ph.D. (1983) and M.Sc. (1977) in Computer Science from the University of Toronto, and a B.A. in Mathematics (1975) from McGill University. His research spans trust modeling in electronic marketplaces, ethical AI, healthcare AI applications, and misinformation management. Notable contributions include frameworks for adjustable autonomy in multiagent systems and trust-based mechanisms to promote honesty in e-commerce. He has advised over 40 graduate students and supervised numerous undergraduate research assistants, contributing to a vibrant academic community. Recent work emphasizes AI ethics, healthcare innovations (e.g., CPR optimization via machine learning), and combating misinformation through multiagent trust systems. His awards include the 2023 CAN-CS Lifetime Achievement Award and the 2018 CAIAC Lifetime Achievement Award, reflecting his impactful career in AI research and education. Current research includes proactive hate speech detection using graph transformers and exploring ethical AI frameworks for autonomous vehicles. He maintains active collaborations in health informatics, social network analysis, and AI-driven educational technologies.

Toshiya HachisukaView profile

Associate Professor

• Computer Graphics
• Light Transport Simulation
• Computational Statistics
• +3 more

Toshiya Hachisuka is an Associate Professor in the Department of Computer Science at the University of Waterloo, part of the School of Computer Science. His research focuses on combining applied mathematics, computer science, and physics to address challenges in visual simulation, particularly in computer graphics, light transport, and computational statistics. He holds a Ph.D. from the University of California, San Diego (2011) and a B.Eng. from the University of Tokyo (2006). Research Interests: Hachisuka’s work spans light transport simulation , Monte Carlo rendering , numerical analysis , and fluid dynamics . He develops algorithms for efficient rendering and simulation, including methods like segment-based light transport and quantum ray marching. His techniques often integrate mathematical rigor with computational efficiency. Publications: His recent work explores advancements in Monte Carlo methods, fluid simulation, and quantum computing applications in rendering. Notable themes include denoising techniques , boundary element methods , and gradient-domain rendering . Awards: No scientific awards explicitly mentioned in the text. Advising & Grants: No specific students or grants listed, but his extensive publication record suggests active research collaboration. Labs/Teams: Involved in computer graphics research groups at the University of Waterloo, contributing to cutting-edge rendering and simulation projects.

• Power Systems Engineering
• Electrical Engineering
• Renewable Energy Integration
• +3 more

Behnam Tamimi is a Sessional Lecturer at the University of Waterloo, specializing in power systems engineering and control systems. His research focuses on microgrid interfaces, voltage stability, and hybrid power flow controllers. He contributes to IEEE standards through task forces on voltage stability analysis and security assessment. His work emphasizes practical applications of theoretical models, including prototype development and field testing of control systems for distribution networks. Key areas of exploration include unbalanced network conditions, small-signal oscillatory dynamics, and the integration of renewable energy sources into existing grids. Tamimi's contributions to benchmark systems and test models have advanced industry practices in grid reliability and resilience. His research bridges academic theory with real-world grid challenges, addressing both steady-state and dynamic system behaviors.

John ThistleView profile

Associate Professor

• Control of discrete event systems
• Formal synthesis
• Verification of discrete event systems
• +4 more

Dr. John Thistle is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, affiliated with the Waterloo Formal Methods (WatForm) research group. His research focuses on control of discrete event systems, formal synthesis/verification, and applications to software development, with emphasis on decidability and complexity of controller synthesis. He holds a PhD from the University of Toronto (1991) and has taught courses such as BME 356 (Control Systems), ECE 108/208 (Discrete Mathematics), and MTE 481/482 (Mechatronics Design Projects). Research interests include formal methods in hardware/software engineering, cybersecurity, and infrastructure integrity. His work bridges traditional control engineering with distributed software systems design. Publications span topics like parameterized network analysis (IEEE Transactions on Automatic Control, 2024) and deadlock analysis in ring topologies (2014). He currently supervises graduate students through Waterloo's formal methods research program.