جستجوی استاد راهنمای دانشگاهی

Rachael (Ré) A Mansbach is an Assistant Professor and Tier II Canada Research Chair in Computational Biophysics at Concordia University's Department of Physics. Her research focuses on computational biophysics, statistical physics, and molecular dynamics simulations applied to drug design and biomaterials. She leads the Mansbach Lab Group, collaborating with institutions such as Northeastern University and Concordia’s Zazubovits and Gauthier Labs. Research interests include antimicrobial peptide design to combat antibiotic resistance, structural studies of disulfide-rich toxins, multi-scale modeling of mucin proteins for hydrogel development, and applications of network theory in medical imaging and deep learning. She holds a PhD and supervises MSc and PhD students in Physics. Awards: Tier II Canada Research Chair (2021-). Availability: Available via email M-F, with Friday Zoom office hours. Contact via re.mansbach@concordia.ca or https://www.researchgate.net/profile/Rachael_Mansbach

• Computational Biophysics
• Statistical Physics
• Molecular Dynamics Simulations
• +۷ مورد دیگر

Doina Precup is a Canada-CIFAR AI Chair and Professor at the School of Computer Science, McGill University, and holds a Research Director role at DeepMind. She co-founded the AI4Good Lab and Eastern European Machine Learning Summer School, focusing on improving diversity and access in AI. Her research emphasizes reinforcement learning, temporal abstraction, and applications in medicine and automated control. Her work includes foundational contributions like the 'options framework' for temporal abstraction in reinforcement learning (Classic Paper Award, 2019) and the option-critic architecture (AAAI Outstanding Student Paper). She is a Fellow of the Royal Society of Canada (2022), CIFAR Senior Fellow (2017), and recipient of the Creative Destruction Lab's Ideas Award (2017). She has served as Associate Dean of Research in McGill's Faculty of Science (2015–2017), Associate Scientific Director of Healthy Brains for Healthy Lives, and leader of UNIQUE's Learning Research Axis. Her leadership roles include chairing the NSERC Discovery Grant committee and serving on CSCan-InfoCan's executive committee.

• Artificial Intelligence
• Machine Learning
• Reinforcement Learning
• +۳ مورد دیگر

Asma ul Husna is an Assistant Professor in Business Analytics at the Shannon School of Business, Cape Breton University. Her research focuses on integrating machine learning with optimization techniques to enhance supply chain management and logistics. Her work explores Machine Learning , Deep Learning , and Big Data Analytics to develop novel optimization models for supply chain processes. She has published extensively on supplier selection, order allocation, and demand forecasting. Her recent publications demonstrate expertise in applying clustering algorithms and multi-objective programming to supply chain challenges, with a focus on improving efficiency through data-driven decision-making in both retail and manufacturing contexts.

• Machine Learning
• Deep Learning
• Big Data Analytics
• +۳ مورد دیگر

Dr. Sazia Mahfuz is an Assistant Professor at the Jodrey School of Computer Science, Acadia University. She holds a Ph.D. from Queen’s University, an M.Sc. from Acadia University, and a B.Sc. from the University of Dhaka, Bangladesh. Her research focuses on Streaming IoT Data Analytics, Lifelong Machine Learning, and Medical Image Analytics, addressing challenges in real-time data processing, adaptive learning systems, and healthcare technology. Dr. Mahfuz’s work spans interdisciplinary applications including human activity recognition, vehicular sensor data classification, and diabetic retinopathy detection using deep learning. Her recent contributions emphasize hybrid architectures (CNN-RNN), transformer-based models, and frameworks for multi-level data analytics. She has published extensively on topics ranging from wearable sensor optimization to distributed data stream processing. Her research trends highlight a strong emphasis on IoT-enabled healthcare solutions and lifelong machine learning algorithms that generate synthetic examples to improve model adaptability. While no awards are listed, her articles reflect significant engagement with both theoretical and applied computer science domains. No advising or grant information is provided in the text.

• Streaming IoT data analytics
• Lifelong machine learning
• Medical image analytics

Dr. Cheryl Quenneville is an Associate Professor in the Department of Mechanical Engineering at McMaster University and an Associate Member of the School of Biomedical Engineering. She specializes in biomechanics and biomedical engineering with a focus on injury tolerance criteria, orthopaedic device design, and computational modeling. Education: B.A.Sc. (Queen's University, 2003), M.Sc. (Western University, 2005), Ph.D. (Western University, 2009) Current Role: Associate Chair, Undergraduate, Mechanical Engineering Her research program integrates experimental testing and finite element modeling to advance understanding of bone fracture mechanics, develop injury risk functions, and validate synthetic surrogates for biomechanical research. Recent work has addressed hockey neck guard safety, forearm injury limits, and hip fracture risk prediction using DXA imaging. Key trends in her publications include injury biomechanics, computational modeling, and medical imaging applications. She has received the Petro-Canada-McMaster Young Innovator Award and collaborates with industry partners like Niko Apparel Systems. Her lab emphasizes trainee development and translation of findings to clinical and industrial partners. Scientific Awards: Petro-Canada-McMaster Young Innovator Award Dr. Quenneville teaches Current Topics in Orthopaedic Biomechanics (MECHENG 717/BIOMED 717) and actively accepts graduate students. The McMaster Injury Biomechanics Lab, which she leads, develops comprehensive injury limits for understudied events and translates findings through partnerships in healthcare and safety industries.

• Biomechanics
• Biomedical Engineering
• Biomaterials
• +۸ مورد دیگر

Hao Cai is an Assistant Professor in the Department of Computer Science at St. Francis Xavier University. His research focuses on computer vision, machine learning, and image processing, with a particular emphasis on crowd counting, generative adversarial networks (GANs), and image quality assessment. He has developed innovative methods for multi-granularity crowd counting, scale-invariant feature aggregation, and disentangled representation learning in GAN frameworks. His work addresses challenges in real-world computer vision tasks such as density estimation, perceptual quality metrics, and 3D navigation for unmanned aerial vehicles (UAVs). Dr. Cai’s research spans technical domains including deep learning architectures, stochastic aggregation networks, and adaptive convolutional neural networks. His contributions to multi-view stereopsis and visual homing algorithms have advanced robotics and autonomous systems. He has also explored sparse representation techniques for image quality evaluation, combining statistical analysis with perceptual models to enhance accuracy and efficiency. His publications reflect a strong focus on practical applications of computer vision, from crowd analysis in urban environments to robust image quality assessment without reference images. Future work directions likely include further integration of adaptive learning strategies, scalable architectures, and interdisciplinary applications of vision systems.

• Computer Vision
• Machine Learning
• Image Processing
• +۳ مورد دیگر

Irina Rish is a Full Professor at the University of Montreal's Department of Computer Science and Operations Research and a core member of Mila – Quebec AI Institute. She holds the Canada Excellence Research Chair in Autonomous Artificial Intelligence and a CIFAR AI Chair. Her research focuses on machine learning, neural data analysis, and neuroscience-inspired AI. She leads the Autonomous AI Lab and has contributed to projects like the Covi contact-tracing app during the pandemic. Education: MSc and PhD in AI from University of California, Irvine; MSc in Applied Mathematics from Moscow Gubkin Institute. Awards include multiple IBM accolades and prestigious editorial roles (e.g., IEEE TPAMI Associate Editor). Research Interests: Continual Learning, Deep Learning, Sparse Modeling, Reinforcement Learning, Neuroimaging Analysis Affiliations: MILA, CIRCA (Brain and Learning Research Center), Canada Excellence Research Chair Publications span over 120 papers, 64 patents, and books on sparse modeling. Collaborates with industry leaders like IBM, Microsoft, and Samsung. Grants: Leads U.S. Department of Energy’s INCITE project on scalable foundation models. Advises over 30 students in AI and neuroscience-related fields. Labs/Teams: Directs the Autonomous AI Lab at Mila, co-founded Nolano.ai as CSO.

• Machine Learning
• Deep Learning
• Neuroscience
• +۹ مورد دیگر

Ronald Haynes is a Full Professor and Chair of the Scientific Computing Graduate Programs at the Department of Mathematics and Statistics, Memorial University of Newfoundland. He holds a PhD from Simon Fraser University (2003) and has held academic roles at Acadia University and Memorial University. His research focuses on numerical methods for partial differential equations, domain decomposition, parallel computing, and optimization, with applications in industrial mathematics. Education: B.Sc. (Hons) in Applied Mathematics (Memorial University, 1996), M.Sc. (Simon Fraser University, 1998), PhD (Simon Fraser University, 2003). Research interests include numerical analysis, scientific computing, and computational methods for PDEs. He has led initiatives such as the 25th International Domain Decomposition Conference and contributed to software libraries like RIDC-DD and DD-CPM. Dr. Haynes is an active editor for CAIMS journals and a leader in the Canadian Applied and Industrial Mathematics Society. Awards include the President's Award for Outstanding Research (2018) and the Dean of Science Distinguished Teaching Award (2017). He advises graduate students in numerical methods and optimization, and collaborates with industry on projects like drilling strength prediction and reservoir simulation. His work also emphasizes inclusive teaching practices and STEM education.

• Numerical Analysis
• Scientific Computing
• Partial Differential Equations
• +۴ مورد دیگر

Dr. Ekram Hossain is a Professor in the Department of Electrical and Computer Engineering at the University of Manitoba, serving as Associate Chair (Graduate Studies). He is a Fellow of the Canadian Academy of Engineering and the Engineering Institute of Canada, and an IEEE Fellow (2015). His research focuses on wireless communication networks, AI-driven 6G systems, and resource management. He leads the WiCoNS research group and holds editorial roles in top journals like IEEE Transactions on Mobile Computing. Education: Ph.D. in Electrical Engineering (University of Victoria, 2001) Professional Roles: IEEE Distinguished Lecturer (2012-2020), Board Member of IEEE Communications Society Research Interests span 6G networks, reconfigurable intelligent surfaces, non-orthogonal multiple access, and green radio. Notable contributions include over 20 books and numerous award-winning papers. Awards include the 2024 IEEE Education Award and Clarivate Highly Cited Researcher recognition (2017-2024). Awards & Recognition: Multiple IEEE awards, Royal Society of Canada membership, and leadership in professional organizations like IEEE Canada. Advising & Grants: Supervised over 30 graduate students. Secured funding from NSERC and industry partners for projects on heterogeneous networks and 5G/6G technologies. Active in global initiatives like the Next G Alliance Research Council. Labs/Teams: WiCoNS group focuses on AI-driven wireless systems, edge computing, and network virtualization.

• Wireless Communications
• 6G and Beyond Cellular Networks
• AI/Machine Learning
• +۵ مورد دیگر

Mohamed Ali is an Adjunct Professor at the Institute of African Studies and Dean of the College of Education at Lafoole, Somali National University. He holds a BA (Somali National), MA, and PhD (UCLA). His research focuses on Medieval and Modern African history, with emphasis on trade, religion, ethnicity, and African historiography. He has been a Fulbright scholar and was nominated for a Visiting Research Fellowship at UCLA's James S. Coleman African Studies Centre. His work includes analyzing linguistic approaches to Somali history and exploring the role of oral traditions in reconstructing the Horn of Africa's early history. Recent academic contributions span technical domains like control systems and AI, as seen in his 2023-2024 Google Scholar publications in robotics and deep learning. Awards: Fulbright Certificate for academic achievement Presentations: Keynotes on Somali crises, diaspora education, and linguistic historiography at international conferences (e.g., CAAS, Eliff Maay Fest) His administrative roles include leadership in education policy and conflict resolution initiatives, reflecting his dual expertise in academia and institutional development.

• Medieval and Modern History of Africa
• Trade in African History
• Religion and Ethnicity in African History
• +۳ مورد دیگر

Dr. Miljana Horvat is a Professor and Associate Dean of Graduate and Postdoctoral Studies at the Department of Architectural Science, Toronto Metropolitan University. Her expertise spans Energy Efficient Building Design, Solar Neighbourhood Planning, and AI-driven architectural solutions. She holds a PhD from Concordia University (2005) and advanced degrees from McGill University (MArch, 1998) and the University of Belgrade (Dipl.Ing.Arh, 1992). Her research focuses on high-performance building envelopes for cold climates, solar energy integration, and urban sustainability. She leads the International Energy Agency's solar energy guidelines initiatives and mentors graduate students in international collaborations. Courses include BL8101 (Building Envelope Systems) and BL8104 (Building Science Seminar/Studio). Her work bridges architectural design with environmental science, emphasizing AI applications for optimizing solar potential and energy efficiency. Over 30 peer-reviewed articles reflect her contributions to building envelope performance assessment, thermal comfort analysis, and machine learning in energy diagnostics.

• Energy Efficient Building Design
• High Performance Building Envelopes
• Solar Energy and Architecture
• +۵ مورد دیگر

Cheryl A. Rogers serves as an Assistant Professor in the Department of Geography and Environmental Studies at Toronto Metropolitan University, where she leads research in remote sensing applications for carbon cycle monitoring. Her work leverages satellite-derived signals including vegetation indices, chlorophyll fluorescence, and multi-spectral data to quantify carbon sequestration across diverse ecosystems from temperate forests to peatlands and urban green infrastructure. Her research program focuses on the intersection of satellite remote sensing and terrestrial carbon dynamics, with particular emphasis on developing novel methodologies to track vegetation's capacity for carbon dioxide removal. Key approaches include analyzing relationships between leaf chlorophyll content and photosynthetic efficiency, modeling carbon flux responses to climate extremes, and integrating multi-sensor satellite data (SAR, optical, LiDAR) with machine learning techniques. This work spans critical ecosystems including Canada's boreal forests, Hudson Bay Lowlands peatlands, and urban green roofs. Analysis of her recent publication record (2023-2025) reveals three dominant research thrusts: (1) advancing remote sensing techniques for biomass and carbon stock mapping through multi-sensor data fusion, (2) modeling carbon cycle responses to climate change and extreme events using process-based simulations, and (3) developing new approaches for monitoring vegetation physiological processes through chlorophyll fluorescence and spectral indices. Her work consistently addresses climate mitigation challenges with practical applications for forest management and carbon accounting. No scientific awards were documented in the provided source material. Dr. Rogers contributes to academic advising as evidenced by her co-authorship of Academic Advising: A Comprehensive Handbook (2000). While specific current advisees and grant funding details were not disclosed in the available text, her active publication record indicates ongoing research mentorship and project leadership. Her work has significant implications for nature-based climate solutions including retention forestry practices and green infrastructure planning.

• Remote Sensing
• Carbon Sequestration
• Vegetation Monitoring
• +۵ مورد دیگر

Dr. Dirk Rodenburg is an Adjunct Assistant Professor at Queen's University's Dan School of Drama and Music within the Faculty of Arts and Science. He holds cross appointments as an Educational Consultant in the Schools of Medicine and Rehabilitation Therapy (Faculty of Health Sciences) and as a Term Adjunct Professor in the Department of Chemical Engineering (Faculty of Engineering). His research focuses on human performance, real-time data analytics, ethics in technology, and wearable technology applications in healthcare and education. Education: B.A. Psychology, Queen's University M.A. Adult Education, University of British Columbia Ph.D. Faculty of Information, University of Toronto Research interests span human-computer interaction, cognitive load measurement, adaptive simulation systems, and neurotechnology ethics. He has pioneered work in wearable-based emotion recognition, stress detection using ECG, and ethical guidelines for brainwave technologies. Professional roles include Board Member of the Centre for Responsible Brainwave Technologies (CeReB), Associate Editor for International Journal of Sport and Society , and Section Editor for Technology Source . His work bridges academia and industry through 20+ years as a software entrepreneur in educational tech and biotechnology. Grants & Labs: His cross-disciplinary focus integrates engineering, medicine, and arts through collaborative research initiatives in adaptive training systems and ethics frameworks for emerging technologies.

• Human Computer Interaction
• Ethics in Technology
• Sensory Processes and Performance
• +۳ مورد دیگر

Tavian Barnes is a Sessional Lecturer at the University of Waterloo. Their research focuses on software engineering diversity, operating system design, and reinforcement learning applications in AI environments. Research interests include addressing barriers for non-traditional software engineers, optimizing single-level store systems, and developing text-based game frameworks for AI training. Recent work explores hybrid reward architectures to improve reinforcement learning efficacy. Publications span from foundational operating system research (Aurora OS projects) to AI environments (Textworld) and workforce inclusion studies. No scientific awards are explicitly listed. No advising or grant details are available. No lab affiliations are mentioned in the provided texts.

• Software Engineering
• Operating Systems
• Reinforcement Learning
• +۳ مورد دیگر

Derek Rayside is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, and serves as Associate Dean for Co-operative Education and Professional Affairs. His research spans autonomous systems, software engineering, formal methods, and construction project management. He holds a faculty position in a top-tier engineering program with affiliations to both academic and administrative roles at the university. Research interests include advancing autonomous vehicle decision-making through reinforcement learning and computer vision techniques, improving software development methodologies via formal verification and collaborative platforms, and enhancing project management practices in complex construction environments. His work integrates interdisciplinary approaches combining control theory, machine learning, and social network analysis. Recent publications focus on autonomous driving challenges (action recognition, intersection navigation), software engineering education (game-based learning), and formal methods for system validation. His contributions bridge theoretical advancements with practical applications in safety-critical systems and industrial workflows. Teaching responsibilities include the ECE351 course on signals and systems. He has led curriculum development efforts and maintains a personal research website at the University of Waterloo's ECE department.

• Autonomous Systems
• Software Engineering
• Formal Methods
• +۳ مورد دیگر