Ladan Tahvildari is a Full-time Professor in the David R. Cheriton School of Computer Science at the University of Waterloo. Her research focuses on software engineering, self-adaptive systems, cloud computing, and test case prioritization. She leads the Software Technologies Applied Research Laboratory (STAR Lab), emphasizing hands-on industry collaboration and practical software solutions. Her work spans over two decades, with notable contributions to adaptive software systems, runtime adaptation frameworks (GRAF), and cloud modeling (StratusML/Adoop). She has pioneered techniques for flaky test detection (FlaKat), spatiotemporal auto-scaling (STaleX), and POMDP-based uncertainty management for security systems. Key research areas include: Self-protecting software systems Component-based software evolution Defect detection and prioritization Autonomic computing decision models Cloud infrastructure optimization Her recent work bridges academia and industry through hands-on learning approaches and frameworks like Semeru Cloud Compiler for performance enhancement. She has served as workshop chair for ACSOS 2023 and contributed to IBM tool integration in educational curricula. Her lab focuses on transforming theoretical concepts into practical tools like StarMX for self-managing systems and ReLACK for VoIP steganography. Current efforts emphasize adaptive machine learning frameworks and scalable microservice architectures.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۱۸۱-۱۹۴ از ۱۹۴ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Yuying Li is a Professor at the University of Waterloo's Cheriton School of Computer Science. Research focuses on computational optimization algorithms for finance, including neural network approaches for leverage-constrained portfolios, benchmark outperformance strategies, and inflation-regime asset allocation. Holds a BSc from Sichuan University (1982), MMath (1985) and PhD (1988) from Waterloo. Her work bridges continuous optimization, machine learning, and financial engineering. Recent publications develop neural alternatives to dynamic programming for portfolio management, with applications to ETF leverage, decumulation strategies, and high-inflation environments. Methodological innovations address computational scalability and regime-specific modeling.
Tamer Özsu is a University Professor at the David R. Cheriton School of Computer Science, University of Waterloo, where he previously served as Director (2007-2010) and currently holds the role of Associate Dean of Research. He is also a Distinguished Visiting Professor at Tsinghua University. Professor Özsu's research spans distributed data management, graph/RDF systems, and database fundamentals. His current work focuses on: Distributed graph processing algorithms SPARQL query optimization for RDF systems Streaming graph analytics Indexing techniques for modern hardware Distributed database architectures He has authored the seminal textbook Principles of Distributed Database Systems and co-edited the Encyclopedia of Database Systems . As founding Editor-in-Chief of ACM Books, he has shaped computing literature. His recent publications demonstrate continued innovation in graph partitioning, streaming graph algorithms, and scalable RDF processing. Özsu maintains active research leadership in database systems with over 30 years of influential contributions.
Stephen Watt is a Professor at the University of Waterloo, affiliated with the Department of Computer Science within the Faculty of Mathematics. He holds a PhD in Computer Science (1986), MMath in Applied Mathematics (1981), and BSc in Honors Mathematics and Physics (1979). His research focuses on enabling computers to handle mathematics intelligently, with key areas including programming languages for mathematical software, symbolic computation algorithms, computer algebra system interoperability, mathematical knowledge management, and STEM education technology. His work spans theoretical and applied domains, such as developing algorithms for block matrices and handwriting recognition systems like the Legendre-Sobolev approach. He has contributed to initiatives like the International Mathematical Knowledge Trust (IMKT) and collaborated on projects like InkML for mathematical collaboration. Recent publications explore generative AI in STEM assessments, software portability, and GPU-optimized arithmetic operations. Dr. Watt’s research also addresses historical perspectives on symbolic computation and its evolution, alongside modern challenges in mathematical collaboration tools and digital ink compression. His contributions span conferences such as ISSAC, CICM, and SYNASC, reflecting interdisciplinary engagement with both theoretical and applied computer science.
Adrian Lupascuمشاهده پروفایل
دانشیار
Dr. Adrian Lupascu is an Associate Professor at the University of Waterloo, affiliated with the Institute for Quantum Computing (IQC) and the Department of Physics and Astronomy. He holds a cross-appointment in the Department of Electrical and Computer Engineering. His research focuses on superconducting quantum devices, including quantum annealing, quantum control, and strong light-matter interactions. Lupascu leads the Superconducting Quantum Devices Group, which explores novel architectures for quantum computing and sensing. Education: BSc in Physics (University of Bucharest, 2000); PhD in Physics (Delft University of Technology, 2005). Postdoctoral training included work at Delft University of Technology and École Normale Supérieure Paris under Professors Haroche and Raimond, supported by a Marie Curie Fellowship. Research Interests: Development of superconducting flux qubits for quantum information processing, quantum sensing, and ultrastrong light-matter interactions. Key projects include quantum annealing error suppression, qubit-qutrit gate optimization, and advanced flux qubit fabrication techniques. Awards: Alfred P. Sloan Fellowship (2011), Early Researcher Award (2011), Waterloo Nanotechnology Institute Research Leader Award (2018, 2022). His work has been funded by NSERC, MRI, and industry partnerships. Teaching: Courses include Quantum Nanophysics (PHYS 461), Nanoelectronics for Quantum Computing (QIC 880/ECE 770), and Quantum Optics Theory (QIC 895). Lab Activities: Active in developing scalable superconducting qubit systems, cryogenic microwave engineering, and quantum device fabrication. Collaborates with industry and academic partners on quantum computing hardware advancements.
Pooya Ronaghمشاهده پروفایل
عضو هیئت علمی
Pooya Ronagh is a Research Assistant Professor at the University of Waterloo, affiliated with the Department of Physics & Astronomy and the Institute for Quantum Computing (IQC). He also serves as a Scientific Lead at the Perimeter Institute Quantum Intelligence Lab (PIQuIL) and directs the Hardware Innovation Lab at 1QBit. His work bridges quantum computation, machine learning, and optimal control, focusing on quantum algorithms, error correction, and hybrid quantum-classical systems. Education: PhD in Mathematics (University of British Columbia, 2016), MSc in Mathematics (UBC, 2011), dual BSc in Mathematics and Computer Science (Sharif University of Technology, 2009). Awards include the Benjamin Franklin Fellowship (2009). Research Interests: Quantum algorithms for machine learning, reinforcement learning, fault-tolerant quantum architectures, cryogenic systems, and quantum control. He explores applications of quantum simulation to improve learning efficiency and robustness in AI systems. Recent work includes optimizing quantum error correction decoders, developing scalable superconducting architectures, and advancing neural network-based quantum state tomography. His contributions span theoretical frameworks (e.g., lattice surgery scheduling) and experimental methods (e.g., SFQ pulse control). Teaching: Courses like PHYS 490 (Machine Learning in Physics) emphasize practical coding and interdisciplinary projects. Grants and collaborations involve industry and academic partners in quantum hardware and software development. Labs: Hardware Innovation Lab (1QBit), IQC Quantum Control Group Future Work: Scaling quantum supercomputers, cryogenic neural decoders, quantum-enhanced generative AI
Mihaela Vlaseaمشاهده پروفایل
دانشیار
Mihaela Vlasea is an Associate Professor at the University of Waterloo, specializing in additive manufacturing (AM) and materials science. Her research focuses on advancing AM processes such as laser powder bed fusion (LPBF), electron beam powder bed fusion (EB-PBF), and binder jetting. She explores topics including microstructural evolution, process optimization, material characterization, and defect detection using machine learning and advanced testing techniques. Her work addresses challenges in AM such as surface roughness prediction, pore formation, and mechanical property enhancement through data-driven frameworks. She also investigates novel applications like auxetic structures in orthopaedics and lightweight functional materials. Key areas of interest include the interplay between process parameters, material properties, and final component performance. Dr. Vlasea’s research often employs nondestructive evaluation methods (e.g., phased array ultrasonic testing) and computational modeling to improve AM process control and part quality. Her contributions span both metallic and ceramic materials, with a focus on industrial applications in aerospace, automotive, and biomedical fields. She leads the Multi-Scale Additive Manufacturing Lab , where she develops innovative AM methodologies for complex architectures and functional materials. Her work bridges fundamental materials science with applied manufacturing engineering, emphasizing sustainability and cost-effective solutions for AM processes.
- Sustainable Energy Systems
- Polymer Electrolyte Membrane Fuel Cells
- Microfluidic and Nanofluidic Devices
- +۳ مورد دیگر
Erik Kjeang is a Professor and Graduate Student Supervisor in the School of Mechatronic Systems Engineering at Simon Fraser University. He specializes in sustainable energy systems, polymer electrolyte membrane (PEM) fuel cells, and microfluidic/nanofluidic energy conversion. His research focuses on improving fuel cell durability, material design, and system performance through advanced characterization and modeling. Educations: Ph.D. in Mechanical Engineering, University of Victoria (2007) M.Sc. and B.Sc. in Energy Engineering, Umea University, Sweden (2004) Teaching: Courses include MSE 210 (Engineering Measurement), MSE 223 (Fluid Mechanics), and MSE 422/722 (Fuel Cell Systems). Recent course offering: MSE 210 D100 in Fall 2025. Research Interests: Fuel cell durability under extreme conditions (freeze-thaw, high temperature), membrane degradation mechanisms, hydrogen storage materials, and advanced manufacturing techniques for energy systems. His work integrates experimental and computational methods to address real-world challenges in sustainable energy. Advising & Grants: Supervises graduate students in fuel cell technology and material science. Active in securing research funding for energy innovation projects. Labs & Teams: Involved in SFU's energy research labs focusing on fuel cell durability, microfluidic systems, and sustainable material development.
Jennifer Fisher is a Professor in the Department of Visual Art and Art History at York University's School of the Arts, Media, Performance & Design (AMPD). She holds a BFA from NSCAD University, and MA and PhD degrees from Concordia University. Her academic work integrates curatorial practice with research in contemporary art, sensory aesthetics, and feminist theory. Research Focus Fisher's research explores interdisciplinary intersections including: Exhibition studies and archival reinterpretation Affect theory and non-visual sensory aesthetics Feminist performance and display practices Curatorial methodologies and artist archives Professional Recognition Contemporary Art Fellow at the National Gallery of Canada Research affiliations at Cornell University and NYU Tisch School of the Arts Co-founder of the Journal of Curatorial Studies Founding member of DisplayCult curatorial collective Notable Projects Fisher co-curated 'Archives by Artists' (2024) at the Archives of Ontario, featuring 18 international artists who reconceptualize archival practice through interactive multiples. The exhibition engaged AMPD students in hands-on curation and will travel to Québec in 2025. Her work frequently integrates academic research with public-facing curation.
Mark-David Hosale is an Associate Professor and Chair of Computational Arts at York University's School of the Arts, Media, Performance & Design (AMPD). He holds a BA in Music Composition from UC Santa Barbara. His work bridges computational art, performance, and architecture, focusing on worldmaking through interdisciplinary collaborations. Education: BA - Music Composition (UC Santa Barbara) Key Roles: Chair of Computational Arts, nD::StudioLab Director Research Labs: nD::StudioLab Research interests include the intersection of virtual and physical worlds, using digital fabrication and hardware/software integration to create immersive art. His theoretical practice centers on worldmaking —artworks that propose ontological alternatives through sensory experiences. Notable collaborations include the IceCube Neutrino Observatory and the PACIS project. His exhibitions span venues like SIGGRAPH, Dutch Electronic Art Festival, and Venice Biennale. Labs/Teams: nD::StudioLab, PACIS collaboration Grants: Multiple undisclosed research grants Labs include the nD::StudioLab, an experimental space for ArtScience research-creation.
Youcef Derbalمشاهده پروفایل
دانشیار
Dr. Youcef Derbal is an Associate Professor in the Department of Information Technology Management at Toronto Metropolitan University's Ted Rogers School of Information Technology Management. With a Ph.D. in Electrical and Computer Engineering from Queen's University, he brings extensive industry experience from robotics, telecommunications, and software sectors to his academic work. His research focuses on Complex Adaptive Systems, particularly in modeling cancer dynamics through agent-based simulations, machine learning applications for oncology, and computational frameworks for biological processes. Key research areas include tumor dynamics, cell signaling pathways, and tumor-infiltrating lymphocyte recruitment. Dr. Derbal teaches undergraduate courses in business information systems, programming, system analysis, database design, and client-server applications, along with graduate-level advanced project management. His publication record shows consistent output in computational biology, cancer modeling, and grid computing since 2006. Professional affiliations include: Association for Computing Machinery (ACM) Institute of Electrical and Electronics Engineers (IEEE) International Society for Computational Biology (ISCB) Administrative contributions include service on University Senate, chairing multiple departmental committees, leading the Business Technology Management curriculum development (2009-2014), and serving as School Director during 2013/2014.
François-Raymond Boyer is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal. He holds a B.Sc. and Ph.D. from Université de Montréal and teaches courses in programming and digital audio. His research spans: Computer architecture and VLSI systems Network processing and traffic management Digital audio signal processing Hardware acceleration and optimization He is affiliated with ReSMiQ (Strategic Cluster for Microsystems) and OICRM (Music Research Observatory). Recent publications focus on 5G network processing, modular programming frameworks, and high-speed traffic management architectures, primarily in IEEE Access and IEEE Transactions on VLSI Systems. Professor Boyer has supervised 3 PhD and 6 Master's students, with research topics including network architecture, audio processing, and hardware design. No scientific awards are mentioned in the available records.
Claudiane Ouellet-Plamondon is a Full Professor in the Department of Construction Engineering at École de technologie supérieure (ÉTS), where she holds the Canada Research Chair on Sustainable Multifunctional Construction Materials. She directs research at the Pavements and Bituminous Materials Laboratory (LCMB) and collaborates with the Interdisciplinary Research Centre for Sustainable Development (CIRODD) and Water Engineering Laboratory (LGEPE). Her credentials include a Ph.D. from the University of Cambridge and postdoctoral training at ETH Zurich. Her research encompasses: Sustainable Materials: Geopolymers from industrial waste, bio-based composites, functionalized clays. Advanced Manufacturing: AI-optimized 3D concrete printing, robotic fabrication. Circular Economy: Valorization of bauxite residue, dredged sediments, and agricultural byproducts. Environmental Impact: Life cycle assessment, urban ecological footprint modeling, decarbonization strategies. She has received significant recognition, including the Mercator Fellowship (2024), France-Quebec Science Ambassadorship (2022), and Royal Society of Chemistry Award (2023). Her work integrates computational methods like neural networks for material design and machine learning for construction automation. Professor Ouellet-Plamondon supervises a large cohort of graduate students working on projects ranging from self-sensing alkali-activated materials to mycelium-based insulation. She maintains robust industry partnerships, particularly in aluminum recycling and sustainable infrastructure, and teaches courses on materials science and specialized engineering topics.
- Aeronautics and Aerospace
- Intelligent and Autonomous Systems
- Industrial Internet of Things
- +۳ مورد دیگر
Tony Wong is a Professor in the Department of Systems Engineering at École de technologie supérieure (ÉTS), specializing in aeronautics, autonomous systems, and industrial automation. He holds affiliations with three key research laboratories: the Control and Robotics Laboratory (CoRo), LARCASE (Aeronautical Research), and SYNCHROMEDIA (Multimedia Communication). His work bridges theoretical optimization and practical applications, particularly in UAV design, renewable energy, and blockchain logistics. Research interests span: Aeronautics/Aerospace : Morphing wing optimization, computational fluid dynamics, UAV performance enhancement. Intelligent Systems : Robotic automation, machine learning for predictive maintenance, low-code industrial solutions. Sustainable Technologies : Hybrid energy systems, IoT for resource optimization, edge computing deployments. Dr. Wong mentors 47+ graduate students, with recent projects including wind-tunnel validations of morphing wings, AI-driven supply chains, and solar energy forecasting. His publication record (31+ journal articles since 2021) demonstrates consistent contributions to aerodynamic design and computational intelligence. While no awards are documented, his leadership in collaborative labs underscores institutional recognition. Laboratory engagements focus on experimental validation and industrial partnerships, utilizing ÉTS facilities like the Price-Païdoussis Wind Tunnel and advanced flight simulators. Current projects prioritize sustainability, including aerodynamic drag reduction and blockchain-enabled cost optimization.