جستجوی استاد راهنمای دانشگاهی

Gennaro Notomista is an Assistant Professor at the University of Waterloo, part of the Full-time faculty. His research focuses on robotics, control systems, and multi-agent coordination. Key areas include swarm intelligence, optimization of robotic tasks, and safety-critical control algorithms. He is affiliated with the Robotarium, a remotely accessible multi-robot testbed, and explores applications in autonomous vehicles, environmental monitoring, and creative robotics projects like music-driven swarm painting. His work emphasizes energy-efficient task allocation, decentralized control strategies, and safe navigation frameworks. Notable contributions include advancements in control barrier functions for ensuring safe operation and resilient task execution in dynamic environments. Recent publications address challenges in persistent environmental monitoring, long-duration autonomy, and the design of wire-traversing robots. Notomista’s research also bridges robotics with real-world applications, such as using robot swarms to model epidemiological dynamics and enhance teleoperation systems. His interdisciplinary approach combines optimization theory, machine learning, and mechanical design to tackle complex robotic systems challenges.

• Robotics
• Control Systems
• Optimization
• +۳ مورد دیگر

Madeleine Bartlett is a Research Fellow at the University of Waterloo, affiliated with the Post Doctoral Scholars and Visitors groups. Her work bridges neuroscience and artificial intelligence, focusing on biologically plausible algorithms and their applications in robotics and human-robot interaction. Her research explores how neural mechanisms inspire computational models for reinforcement learning, action representation, and social signal processing. Key areas include integrating biological constraints into machine learning systems and developing robots capable of interpreting human social cues, particularly for therapeutic applications in autism spectrum disorder (ASD). Her publications highlight contributions to continuous action representations in basal ganglia models, biologically-based memory systems for reinforcement learning, and statistical rigor in human-robot interaction studies. She has also pioneered methods for estimating engagement in social HRI using novel neural architectures like Legendre memory units. While no formal awards or grants are listed, her work demonstrates significant innovation at the intersection of neuroscience-inspired AI and socially assistive robotics. She contributes to advancing robots as therapeutic tools through validated autonomous systems that mimic human guidance patterns observed in ASD therapy contexts.

• Artificial Intelligence
• Neuroscience
• Robotics
• +۳ مورد دیگر

Stephen L. Smith is a Professor and Tier 2 Canada Research Chair in the Department of Electrical and Computer Engineering at the University of Waterloo. He serves as Co-Director of the Waterloo Artificial Intelligence Institute, leading research in robotics and AI. His work focuses on autonomous systems, multi-robot coordination, and human-robot interaction, with applications in navigation, control systems, and collaborative task planning. Smith's research explores challenges such as path planning in uncertain environments, persistent monitoring, and adaptive decision-making. His contributions include algorithms for robot navigation in ice-covered waters, real-time replanning under constraints, and optimizing multi-agent systems for efficiency and safety. Key scientific awards include the Tier 2 Canada Research Chair designation. His research also addresses human-centric aspects, such as studying user preferences in collaborative tasks and developing frameworks for learning user intent through interaction.

• Robotics
• Artificial Intelligence
• Control Systems
• +۳ مورد دیگر

Fatma Gzara is a Professor at the Department of Management Sciences, University of Waterloo, and co-founder/co-director of WANOPT (Waterloo Analytics and Optimization Lab). Her research focuses on supply chain analytics, large-scale optimization, and data-driven decision-making in logistics systems. She has led industry-funded projects with NSERC, OCE, MITACS, and collaborators like Bombardier and Unilever. Education: PhD in Management Science from McGill University (2003). Teaches courses such as MSCI 331 (Optimization), MSCI 734 (Network Models), and graduate seminars (MSCI 200A/B). Active in graduate student supervision. Research interests include optimization under uncertainty, drone delivery systems, hazmat transportation planning, and airline operations. Recent publications explore pandemic resource allocation, crowdsourced delivery economics, and urban UAV traffic management. Funding collaborations include NSERC grants for supply chain analytics and MITACS partnerships. WANOPT lab focuses on integrating analytics with optimization for large-scale systems.

• Operations Research
• Large Scale Optimization
• Supply Chain Analytics
• +۵ مورد دیگر

Houra Mahmoudzadeh is an Associate Professor at the University of Waterloo, affiliated with groups such as Data Analytics, Applied Operations Research, and Healthcare. Her research focuses on optimization techniques applied to healthcare systems, particularly radiation therapy planning, robust decision-making under uncertainty, and pandemic-era staff scheduling. She specializes in developing advanced algorithms for IMRT treatment planning and addressing challenges in healthcare operations through mathematical modeling. Her work integrates robust optimization frameworks with clinical applications, emphasizing practical solutions for radiation therapy delivery, resource allocation in healthcare, and multi-objective decision-making. Key contributions include methodologies for inverse optimization in medical contexts, Pareto robust optimization strategies, and pandemic-specific staff scheduling models. Recent publications highlight innovations in dose-based constraint generation, light Pareto robust optimization, and effective budget of uncertainty formulations. Her research bridges theoretical operations research with real-world healthcare challenges, aiming to improve treatment efficacy and operational efficiency in medical settings.

• Operations Research
• Healthcare Management
• Radiation Therapy Optimization
• +۳ مورد دیگر

Niayesh Afshordi is a Professor and Undergraduate Advisor in the Department of Physics & Astronomy at the University of Waterloo. His research focuses on fundamental questions in cosmology and quantum gravity, particularly the nature of black holes, gravitational waves, and the origins of the universe. He explores topics like black hole echoes, holographic principles, and cyclic models of the cosmos through interdisciplinary approaches combining theoretical physics with observations. His work often bridges high-energy physics, astrophysical phenomena, and philosophical implications of scientific discoveries. His research interests span quantum gravity effects on black hole horizons, observational tests of cosmological models, and theoretical frameworks such as braneworld scenarios and loop quantum cosmology. He also engages in exploring the intersection of science and cultural narratives, including the ‘Science of Religion’ and ‘Religion of Science’ themes. His contributions to gravitational wave astronomy include pioneering studies on detecting echoes using LIGO and LISA data. Advising and Grants: As an undergraduate advisor, Afshordi guides students in physics and astronomy. No specific grants or advisees are explicitly listed in the provided texts. His research is supported by affiliations with institutions like the Perimeter Institute for Theoretical Physics, inferred from his webpage and publications. Labs/Teams: Afshordi collaborates with the Astrophysics & Gravitation group and broader research networks at the University of Waterloo and Perimeter Institute. His work involves cross-disciplinary teams focusing on numerical relativity, quantum field theory in curved spacetime, and observational cosmology.

• Cosmology
• Quantum Gravity
• Black Hole Physics
• +۳ مورد دیگر

Susan T. Gardner (PhD, Concordia University, 1981) serves as a Lecturer in Philosophy within the School of Humanities at Capilano University. Holding advanced degrees from Oxford University (M.Litt and B.Phil) and McGill University (BA and BN), she brings decades of academic experience to her teaching and research. Her educational background spans philosophy, sociology, psychology, and nursing, creating a uniquely interdisciplinary perspective. Gardner's research focuses primarily on critical thinking and Philosophy for Children (P4C), with recent scholarship examining civil discourse, educational philosophy in uncertain times, and the relationship between freedom and predictability. She argues that 'a necessary condition of a well-lived life is that one learn how to think well,' emphasizing impartial evaluation of contradictory viewpoints as essential to meaningful education. Her teaching methodology transforms classrooms into 'Communities of Philosophical Inquiry' where students develop mental flexibility through structured dialogue. Her publication record shows remarkable productivity through 2025, with articles spanning educational philosophy, ethics, and political theory. Recent work addresses contemporary challenges including 'woke' culture, technological addiction, and liberal tolerance. Gardner's research demonstrates consistent engagement with both theoretical philosophical questions and practical educational applications, particularly through her P4C framework. Gardner directs the Vancouver Institute of Philosophy for Children (1995-present) and the Thinking Playground P4C camp at University of the Fraser Valley (2014-present). As Vice-President of the International Council of Philosophical Inquiry with Children (2017-present) and co-director of the North American Association of the Community of Inquiry, she maintains significant leadership roles in global P4C initiatives. Her editorial work with Analytic Teaching and Philosophical Praxis further demonstrates her commitment to advancing philosophical education. Her book Thinking Your Way to Freedom: A Guide to Owning Your Own Practical Reasoning (Temple University Press, 2009) represents a major contribution to critical thinking pedagogy. Through her institutes, summer camps, and international conference organization, Gardner actively translates philosophical theory into practical educational settings for both children and teachers.

• Critical Thinking
• Philosophy for Children
• Ethics
• +۴ مورد دیگر

Ramtin Rakhsha is a Lecturer at the School of Mechatronic Systems Engineering within the Faculty of Applied Sciences at Simon Fraser University. His research focuses on haptics, distributed control systems, nonlinear passivity-based control, unmanned systems, and underwater robotics. PhD, Mechanical Engineering, University of Victoria, 2015 M.Sc., Mechanical Engineering, University of Tehran, Iran, 2007 B.Sc., Mechanical Engineering, University of Tabriz, Iran, 2003 His teaching interests include robotics, control systems, computer-aided design, vibrations, and capstone engineering projects. He has recently taught courses such as MSE 210 (Engineering Measurement and Data Analysis), MSE 300 (The Business of Engineering), MSE 381 (Feedback Control Systems), and MSE 320 (Machine Design). Future courses listed for Summer 2025 and Fall 2025 include advanced topics in robotic system kinematics, machine design, and special topics in mechatronic systems engineering.

• Haptics
• Distributed Control Systems
• Nonlinear passivity-based control
• +۵ مورد دیگر

Yiguo Sun is a Professor of Economics and University Research Leadership Chair at the University of Guelph, Department of Economics and Finance. She specializes in econometrics, focusing on semi-/nonparametric methods for panel data, non-stationary time series, and spatial regression models. Her research addresses issues such as investment dynamics, social interactions, and threshold effects. She holds a B.Sc. and M.Sc. from Hebei Normal University, an M.A. from the University of Guelph, and a Ph.D. from the University of Toronto. Awards include the CBE Senior Research Fellow (2018-2021) and University Research Leadership Chair (2022-2025). Education: B.Sc. in Mathematics, Hebei Normal University (1993) M.Sc. in Mathematics, Hebei Normal University (1996) M.A. in Economics, University of Guelph (1997) Ph.D. in Economics, University of Toronto (2002) Research Interests: Dr. Sun’s work centers on advancing econometric methodologies, particularly in nonparametric and semiparametric frameworks. Key areas include: Threshold regression models and their applications in inflation dynamics and social interactions Spatial econometrics and panel data analysis Nonlinear estimation techniques addressing endogeneity and measurement error Economic growth and natural resource nexus Recent Contributions: Her 2024 paper on investment-uncertainty relationships introduced a novel estimator addressing endogeneity and measurement bias. The 2023 Social Threshold Regression advanced peer effect analysis through a spatial Durbin framework. Recent articles explore spatial spillovers in trade policies and Canadian inflation dynamics using threshold models. Awards: University Research Leadership Chair (2022-2025) CBE Senior Research Fellow in Spatial Econometrics (2018-2021) SSHRC Insight Grant (2022-2025) Grants & Advising: She leads SSHRC-funded projects on social networks and measurement errors in finance. Supervised students include Delong Li (investment dynamics), Chaoyi Chen (threshold estimation), and Hui Xiao (model averaging). Research teams focus on econometric theory and applied policy analysis. Labs/Teams: Active in the University of Guelph’s CBE research community, collaborating with Thanasis Stengos, Emir Malikov, and international scholars on spatial econometrics and nonlinear methods.

• Econometrics
• Theoretical Econometrics
• Applied Econometrics
• +۸ مورد دیگر

Jeff Defoe is a Professor in the Department of Aerospace Engineering at the University of Windsor's Faculty of Engineering. His research focuses on advancing aerospace and mechanical engineering through computational fluid dynamics (CFD), turbomachinery optimization, and aeroacoustics. He collaborates with jet engine manufacturers to enhance aircraft efficiency and has pioneered low-cost ventilator designs for global health applications. Defoe is a recipient of the 2016 Medal of Excellence for dedication to the Faculty of Engineering. His work integrates theoretical, numerical, and experimental methods to address challenges in fan/compressor performance, automotive thermal management, and crosswind effects on aerodynamic systems. Defoe has mentored the University of Windsor Rocketry Team, which achieved third place in an international competition in 2017. His research spans applications from aerospace propulsion systems to sustainable automotive engineering solutions. Key contributions include body-force modeling techniques for turbomachinery, nonlinear control systems for automotive air conditioning, and predictive models for gas turbine dynamics. His publications emphasize innovations in CFD algorithms, turbulence modeling, and noise reduction strategies for high-performance systems.

• Aerospace Engineering
• Fluid Dynamics
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Richard J. Caron is a Professor at the University of Windsor's College of Engineering, specializing in operational research and mathematical optimization. He has supervised students including Nooshin Nekoiemehr, Qiqi Zhang, and Anqi Chen. His team won the first practice prize at the national conference of the Canadian Operational Research Society. His research focuses on mathematical programming, constraint analysis, and optimization algorithms. Recent publications examine simplex algorithms, matrix inequalities, and probabilistic methods for extreme point identification. Dr. Caron's awards include the First Practice Prize from the Canadian Operational Research Society for developing cargo optimization tools for Air Canada. His work demonstrates consistent contributions to optimization theory and computational mathematics throughout his career.

• Operational Research
• Mathematical Optimization
• Simplex Algorithms
• +۲ مورد دیگر

Rhonda N. McEwen is a Professor at the University of Toronto's Faculty of Information and the Institute of Communication, Culture, Information and Technology (ICCIT). Her work bridges Social and new media Human-machine communication Mobile learning and cognition Special education technology domains. With a PhD in Information (University of Toronto), MSc in Telecommunications (University of Colorado), and MBA in Information Technology (City University, London), she combines technical and social science perspectives. Her research focuses on Emerging media and cognitive informatics Eye-gaze systems for communication Virtual reality perception studies Autism and technology Human-robot trust dynamics . She holds a Canada Research Chair in Emerging Media and Communication, and her work has been featured by 60 Minutes (USA/Australia) and Toronto Star . Recent publications explore VR-based gene regulation simulations and mobile device impacts on education . Notably, her team's eye-gaze technology research (2021) demonstrates how these systems enable communication for children with complex needs. She actively mentors graduate students in projects ranging from home companion robots to mobile communication in autism education .

• Social Media
• Human-Computer Interaction
• Mobile Communication
• +۱۰ مورد دیگر

Mohamed Shehata is a Professor in the Department of Computer Science, Mathematics, Physics, and Statistics at the University of British Columbia's Irving K. Barber Faculty of Science. He holds an adjunct professorship at Memorial University of Newfoundland's Computer Engineering Department. His research focuses on computer vision, biomedical applications, and intelligent camera systems. He earned his B.Sc. (Zagazig University), M.Sc. (Zagazig University), Ph.D. (University of Calgary), and P.Eng. licensure. Previously, he worked at Intelliview Technologies Inc. as Vice President of Engineering and Research. He has held roles as an assistant and associate professor at Memorial University before joining UBC in 2019. He serves as Editor-in-Chief of the IEEE Canadian Journal of Electrical and Computer Engineering and has contributed to over 70 peer-reviewed publications. His work spans video surveillance systems, domain generalization, and medical imaging applications. Education: B.Sc. (Honors), Zagazig University M.Sc., Computer Engineering, Zagazig University Ph.D., University of Calgary Research Interests: He explores cutting-edge topics like federated learning for domain adaptation, biomedical image analysis, and lightweight neural networks for embedded systems. His recent work emphasizes cross-domain generalization and few-shot learning for medical diagnostics and object tracking. Professional Contributions: Dr. Shehata has supervised graduate students and led projects in computer vision applications. His publications bridge theoretical advancements with practical systems like drone-based surveillance and IoT healthcare devices. He actively contributes to IEEE committees and academic journal editing.

• Computer Vision
• Image and Video Processing
• Biomedical Applications
• +۴ مورد دیگر

Elina Robeva is an Assistant Professor in the Department of Mathematics at the University of British Columbia (UBC), effective until July 2025, when she will be promoted to Associate Professor. She is affiliated with the Institute of Applied Mathematics, CAIDA, and holds the titles of AMII Fellow and Canada CIFAR AI Chair. Her research focuses on the intersection of mathematical statistics, machine learning, combinatorics, and applied algebraic geometry, with an emphasis on causal inference, graphical models, and tensor decomposition. Education: She earned her PhD in Mathematics from UC Berkeley (2016), advised by Bernd Sturmfels, and a BS with Honors in Mathematics from Stanford University (2011). Prior to UBC, she was an NSF Postdoctoral Fellow and instructor at MIT (2016–2019). Research Interests: Her work bridges algebraic methods with statistical problems, including causal discovery in linear models, tensor decomposition applications in machine learning, and super-resolution imaging. She employs algebraic geometry and combinatorics to uncover structural insights in statistical problems. Awards: Recipient of the Andre Aisenstadt Prize (2024), Bernard Friedman Memorial Prize (2016), and Vanier Canada Graduate Scholarship (for student Pardis Semnani). She is also a Canada CIFAR AI Chair and AMII Fellow. Advising & Mentorship: She has mentored numerous students, including PhD candidates (e.g., Pardis Semnani), MSc students, and undergraduates through programs like NSERC USRA and MITACS. Notable collaborations include work on causal inference, log-concave density estimation, and tensor networks. Labs/Teams: Active in interdisciplinary research groups at UBC and collaborates internationally through programs like the Institute for Mathematical and Statistical Innovation (IMSI).

• Mathematical Statistics
• Machine Learning
• Causal Inference
• +۶ مورد دیگر

Lele Wang is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at the University of British Columbia (UBC), Vancouver. He is affiliated with the Mathematics of Information, Learning and Data (MILD) research cluster and the Institute of Applied Mathematics. His research focuses on information-theoretic approaches to data science and machine learning, with contributions to universal compression, coding theory, statistical inference on graphs, and noisy computing. Before UBC, he held postdoctoral positions at Stanford University, Tel Aviv University, and as an NSF Center for Science of Information fellow. Education: PhD in Electrical Engineering from the University of California San Diego (2015), B.E. in Academic Talent Program from Tsinghua University (2009). Research Interests: Developing tools in information theory, coding theory, high-dimensional statistics, combinatorics, random graphs, and deep generative models for data-driven challenges. Notable works include universal graph compression for stochastic block models and coding-theoretic approaches to distributed machine learning. Awards: Recipient of the 2017 IEEE Information Theory Society Thomas M. Cover Dissertation Award and NSF CSoI Postdoctoral Fellowship. His students have won multiple awards including GSI Awards and NSERC grants. Mentoring: Prioritizes student development in critical and creative thinking, offering courses in real analysis, probability theory, and theoretical frameworks. Hosts round-robin group meetings inspired by Thomas Cover to foster concise communication and problem-solving skills.

• Information Theory
• Machine Learning
• Data Science
• +۷ مورد دیگر