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Nandini DendukuriView profile

Associate Professor

• Biostatistics
• Diagnostic Test Accuracy
• Bayesian Inference
• +5 more

Nandini Dendukuri, PhD is a Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) at the 5252 de Maisonneuve site. She holds dual affiliations with the Infectious Diseases and Immunity in Global Health Program and the Centre for Outcomes Research and Evaluation (CORE). Academically, she serves as an Associate Professor in the Department of Medicine, Faculty of Medicine and Health Sciences at McGill University, specifically within the Division of Clinical Epidemiology at the MUHC. Dr. Dendukuri's research program centers on the development of advanced statistical methodologies for diagnostic test accuracy evaluation in the absence of perfect reference standards. Her work spans Bayesian inference, latent class modeling, and meta-analysis techniques specifically designed for diagnostic accuracy studies. She has made seminal contributions to addressing methodological challenges such as conditional dependence between diagnostic tests, verification bias, and limitations of composite reference standards. Her research bridges theoretical statistical methodology with practical applications in infectious disease diagnostics, particularly tuberculosis where perfect reference tests are often unavailable. An analysis of Dr. Dendukuri's extensive publication record reveals consistent innovation in diagnostic test methodology with increasing sophistication in statistical modeling approaches. Her recent work (2024-2025) demonstrates expansion into diverse application areas including cardiovascular disease, emerging infectious diseases like COVID-19, and novel diagnostic technologies, while maintaining her core methodological focus. Her publications show particular strength in applying latent class models to complex diagnostic scenarios across multiple disease domains. Dr. Dendukuri actively collaborates with researchers across multiple disciplines, particularly in epidemiology, infectious diseases, and technology assessment. Her work with hospital-based technology assessment units has directly contributed to translating scientific evidence into healthcare policy. She maintains strong connections between statistical theory and practical healthcare applications, frequently developing software implementations (particularly rjags programs) of her methodological innovations to facilitate adoption by the research community.

Alexandre Campeau-LecoursView profile

Associate Professor

• Robotics
• Rehabilitation Engineering
• Biomedical Robotics
• +4 more

Alexandre Campeau-Lecours is an Associate Professor in the Department of Mechanical Engineering and Industrial Engineering at Laval University. He specializes in robotics and rehabilitation engineering, with affiliations at the Interdisciplinary Research Center for Rehabilitation and Social Integration (Cirris) and the Research Center for Robotics, Vision and Machine Intelligence (CeRVIM). His work focuses on developing assistive technologies using robotics and AI, with a focus on co-creation with clinical partners and end-users. Education: Ph.D. in Robotics from Laval University (2012), B.Sc. in Mechanical Engineering/Mechatronics from École Polytechnique de Montréal (2008). Professional certifications include PMP (Project Management Professional) and P.Eng (Professional Engineer). Research interests include rehabilitation robotics, biomechanical engineering, mechatronics, and assistive technologies for individuals with disabilities. Notable projects include the JACO wheelchair-mounted robotic arm and development of real-time wearable sensors for movement analysis. Awards include repeated Teaching Star recognition (2016–2025). Active in grants including projects funded by Fonds de recherche du Québec and Innovation, Sciences et Développement économique Canada, focusing on voice-controlled interfaces, EMG-based assistive devices, and music-based rehabilitation systems. Led the Rehabilitation Engineering Laboratory and collaborates with industry partners like Kinova. Research emphasizes interdisciplinary approaches to create customized assistive solutions, with over 69 publications in peer-reviewed journals.

Keith VanderlindeView profile

Associate Professor

• Cosmology
• Radio Astronomy
• Instrumentation Development
• +3 more

Keith Vanderlinde is an Associate Professor at the David A. Dunlap Department of Astronomy & Astrophysics and the Dunlap Institute at the University of Toronto. His research focuses on cosmology and long-wavelength instrumentation, particularly large-scale structure studies and the expansion history of the universe. He leads projects like CHIME/FRB, CHORD, and HIRAX, developing radio telescopes to detect fast radio bursts (FRBs) and map cosmic evolution. Education: PhD in Physics (University of Chicago, 2008); BS in Physics with EE (MIT, 2002). Awards include CIfAR Junior Fellow (2011-2012) and McGill Trottier Fellow (2009-2011). Research interests span cosmological instrumentation, dark energy probes, and transient astronomy. Key projects include the CHIME radio telescope (studying 21cm emission and FRBs), the CHORD observatory, and international collaborations like HIRAX in South Africa. His work emphasizes instrument design, data analysis pipelines like kotekan, and multi-messenger astronomy. Lab involvement includes the Algonquin Radio Observatory and contributions to SPT-3G. Active in graduate/undergraduate training, mentoring students in cosmology and radio instrumentation.

Andriy MiranskyyView profile

Associate Professor

• Applied Machine Learning
• Big Data
• Blockchain
• +4 more

Dr. Andriy Miranskyy is an Associate Professor in the Department of Computer Science at Toronto Metropolitan University. His research focuses on applied machine learning, quantum computing, cloud computing, and software engineering, with notable contributions to anomaly detection in cloud systems and quantum software engineering. He leads the AMiR Lab, exploring risk mitigation and software development challenges in emerging technologies. Education: Ph.D. in Computer Science from The University of Western Ontario (2011). Research Interests: He investigates quantum software engineering methodologies, cloud-native systems governance, and big data applications. His work bridges theoretical advancements with industrial-scale implementations, such as IBM Db2 quantum safety case studies and cloud monitoring tools like CloudHeatMap. He emphasizes practical solutions for flakiness detection in quantum programs and sustainable software development practices. Awards: Recognitions include the Rogers Cybersecure Catalyst Fellowship (2023-2024), IBM CAS Best Project (2021), and a Guinness World Record for pioneering a 3Pb data warehouse (IBM DB2 team). Teaching: Teaches courses like CPS 840 (Quantum Computing), CPS 847 (Software Tools for Startups), and CPS 731 (Software Engineering). Labs/Teams: Directs the AMiR Lab, focusing on risk-aware software engineering in quantum and cloud domains.

Shahram PayandehView profile

Professor

• Robotics
• Geometrical Robotics
• Networked Dynamical Systems
• +4 more

Shahram Payandeh is a Professor of Engineering Science at Simon Fraser University (SFU), affiliated with the School of Engineering Science within the Faculty of Applied Sciences. He holds a Ph.D. from the University of Toronto (1990), M.A.Sc. (1986), and B.Sc. (1981). His research focuses on robotics, geometrical robotics, networked dynamical systems, and medical robotics, with emphasis on haptic devices, multi-view tracking, and multi-modal interaction in serious games. Education: Ph.D., University of Toronto, Canada, 1990 M.A.Sc., University of Toronto, Canada, 1986 B.Sc., University of Akron, United States, 1981 Research Interests: Robotics and medical robotics applications Geometrical robotics and sensor networks Multi-view tracking and haptic rendering Networked dynamical systems and decision support His work spans visual tracking algorithms, sensor calibration, and teleoperation systems, with practical applications in healthcare and elderly care technology. Teaching: ENSC 482: Introduction to Decision Making in Engineering ENSC 890: Advanced Robotics: Mechanics and Control Labs & Facilities: Associated with the Engineering Science Research Lab (erl.ensc.sfu.ca) Office: ASB 10829

William W.L. WongView profile

Associate Professor

• Pharmacoeconomics
• Pharmacoinformatics
• Health Technology Assessment
• +5 more

William W.L. Wong is an Associate Professor and the CIHR Applied Public Health Chair in HIV and STBBI Research at the University of Waterloo. His work focuses on pharmacoeconomics, pharmacoinformatics, and health technology assessment, with a particular emphasis on infectious diseases like hepatitis C, HIV/AIDS, and public health policy. He has contributed to studies evaluating cost-effectiveness of treatments, healthcare resource allocation, and interventions targeting marginalized populations. Specializes in cost-utility analyses of novel therapies (e.g., CAR T-cell treatments, antivirals). Expert in hepatitis C elimination strategies, screening programs, and disparities in healthcare access. Leads research on opioid overdose prevention (e.g., naloxone distribution) and pandemic healthcare resource use. His recent work highlights trends in hepatitis C care cascades, maternal healthcare gaps, and the economic impact of expanding access to treatments. Wong collaborates with policymakers to design evidence-based public health interventions, particularly for immigrant and high-risk populations. Key areas include: viral hepatitis epidemiology, healthcare cost-benefit analysis, and global health equity. Publications span over 70 peer-reviewed articles, emphasizing methodological rigor in health technology assessment.

Ali ElkamelView profile

Adjunct Professor

• Process Systems Engineering
• Energy Systems
• Environmental Engineering
• +5 more

Ali Elkamel is an Adjunct Professor Emeritus at the University of Waterloo's Department of Chemical Engineering, Faculty of Engineering. His research focuses on Process Systems Engineering, Energy Systems, Environmental Engineering, and Carbon Management. He specializes in applying machine learning to optimize complex systems such as energy production, waste management, and material science. His work spans sustainability initiatives, including hydrogen production methodologies, municipal waste valorization, and eco-friendly grid modernization. He has also contributed to advancements in CO2 capture technologies and renewable energy integration. Elkamel's research often intersects with industrial applications, addressing challenges in petrochemical operations, membrane technology, and process modeling. Elkamel has published extensively on topics ranging from AI-driven education tools to novel materials for gas adsorption. His recent articles highlight trends in machine learning applications for process optimization, energy-water nexus solutions, and sustainable infrastructure design. Despite his prolific output, no formal awards or student advisement records are noted. His academic profile reflects a commitment to bridging theoretical research with practical industrial solutions, particularly in the energy and environmental sectors. Collaborations likely extend to interdisciplinary teams given his diverse research portfolio.

Derek J. KoehlerView profile

Professor

• Judgment and Decision Making
• Cognitive Psychology
• Behavioral Economics
• +3 more

Derek J. Koehler is a Professor and Cognitive Research Area Head, specializing in judgment and decision-making processes. His research focuses on uncertainty assessment in everyday planning, prediction, and decision-making, including studies on scenario generation, self-prediction accuracy, and behavioral economics intersections. He holds a BS from the University of Wisconsin and a PhD from Stanford University. Koehler has been recognized with the Premier's Research Excellence Award and is a Fellow of both the Association for Psychological Science and the American Psychological Association. His research interests span cognitive psychology, behavioral economics, and the psychology of decision-making. He has investigated topics such as the illusion of explanatory depth, the impact of linguistic framing on perceptions, and the role of cognitive reflection in moral judgments. Koehler is actively involved in the Southern Ontario Behavioural Decision Research (SOBDR) community and contributes to initiatives like the Ideas 42 Behaviorally Informed Organizations project. Recent work includes studies on interventions to mitigate cognitive biases during public health crises, the effects of partisan language in polarized environments, and the application of icon arrays to reduce gambling appeal. His research bridges theoretical psychology with practical applications in policy, communication, and behavioral economics. Awards: Premier's Research Excellence Award, APS Fellow, APA Fellow Key Research Themes: Judgment under uncertainty, behavioral economics, cognitive bias mitigation Professional Affiliations: SOBDR Conference organizer, contributor to Journal of Behavioral Decision Making

Robert HunterView profile

Assistant Professor

• Medical Diagnostics
• Nanotechnology
• Biomedical Engineering
• +3 more

Robert Hunter is an Assistant Professor at the University of Waterloo, specializing in the development of advanced biosensors and analytical platforms for medical diagnostics and biomedical applications. His research focuses on integrating nanotechnology and surface-enhanced Raman scattering (SERS) for the early detection of diseases such as ovarian cancer, bacterial infections, and viral pathogens. He has pioneered work on exosome-based biosensors, light-triggered antimicrobial surfaces, and optofluidic diagnostic systems. Key research interests include the application of machine learning algorithms to biomedical spectral data, the design of electrochemical sensors for on-farm livestock health monitoring, and the use of C. elegans as a model organism for drug discovery. His interdisciplinary approach bridges engineering, chemistry, and biology to address challenges in precision medicine and rapid diagnostics. As a Full-time Faculty member, Dr. Hunter contributes to teaching and research in cutting-edge technologies, with a focus on translating laboratory innovations into practical clinical and agricultural solutions.

Igor IvkovicView profile

Professor

• Information Systems
• Software Engineering
• Knowledge Engineering
• +3 more

Igor Ivkovic was a Professor in the Department of Systems Design Engineering at the University of Waterloo, Canada. His work focused on integrating theory and practice in complex information systems, emphasizing system modeling, process modeling, and data modeling to bridge technical and business stakeholder needs. He taught courses such as Data Structures and Algorithms, Algorithms and Data Structures, and Digital Systems in recent years. Education: Holds a Doctorate in Electrical and Computer Engineering (2011), along with advanced certificates in university teaching (Certificate in University Teaching, 2011) and instructional skills (ISW, 2015). Earlier degrees include a Master of Mathematics in Computer Science (2003) and a Bachelor of Mathematics in Operations Research (2001), both from the University of Waterloo. Research Interests: Specialized in Information Systems, Software Engineering, and Knowledge Engineering. His work addressed challenges in model synchronization, software evolution, and architecture recovery, leveraging formal methods and model-driven approaches to enhance system consistency and interoperability. Notable Contributions: Authored influential papers on model synchronization for software evolution (2011) and improving the Gnutella protocol (2001), the latter earning a prize-winning award. He also pioneered educational innovations like Design Days Boot Camps (2017–2021), integrating remote learning and augmented reality into engineering education. Awards: Recognized for his 2001 research on the Gnutella protocol, which won a prestigious award through the LimeWire contest.

• Robotics
• Biomechanics
• Human-Machine Interaction
• +3 more

Jonathan Lin is an Adjunct Assistant Professor at the University of Waterloo, specializing in robotics and biomechanics with a focus on human motion analysis and assistive technologies. His research spans rehabilitation engineering, human-robot interaction, and sensor systems for clinical and mobility applications. Key research areas include real-time pose estimation for assistive robots, motion segmentation for rehabilitation monitoring, and humanoid robotics learning from human demonstrations. He has contributed to projects like the SkyWalker mobility aid robot and Segway-riding humanoid systems. His work bridges robotics, biomechanics, and healthcare, emphasizing practical applications in aging populations and clinical settings. No scientific awards are listed, but his publications reflect interdisciplinary innovation in motion analysis and assistive technologies. Advising and grants details are not explicitly provided, though collaborations with robotics and biomedical engineering teams are implied through his research outputs. His lab or team affiliations remain unspecified in the provided texts.

Michael FisherView profile

Assistant Professor

• Control Systems
• Nonlinear Dynamics
• Power Systems
• +3 more

Michael Fisher is an Assistant Professor at the University of Waterloo, affiliated with the Faculty of Engineering. His research focuses on nonlinear systems theory, control systems design, and vulnerability assessment in power systems. He explores topics such as system-level synthesis, stability analysis under perturbations, and optimization techniques for distributed control. His work bridges applied mathematics and engineering applications, with a particular emphasis on resilience and safety margins in complex systems. Key research areas include trajectory sensitivity analysis, region of attraction boundary stability, and sparsity-promoting control design. He has contributed to advancements in H2/H∞ control, adaptive divide-and-conquer strategies for virtual power plants, and geometric programming approaches for natural gas networks. His publications often intersect nonlinear dynamics, optimization, and practical engineering challenges. Fisher’s recent studies emphasize parameterized system analysis, Hausdorff continuity in region of attraction boundaries, and approximation methods in Hardy spaces. His work addresses both theoretical control system advancements and real-world applications in power grids and distributed energy systems.

Mateja ŠajnaView profile

Professor

• Graph Theory
• Combinatorics
• Hypergraphs
• +6 more

Mateja Šajna is a Full Professor in the Department of Mathematics and Statistics at the University of Ottawa. She holds a B.Math from the University of Ljubljana (1992), an MSc, and a PhD (1999) from Simon Fraser University. Her research focuses on graph theory and combinatorics, particularly cycle decompositions, hypergraphs, and the Oberwolfach Problem variants. She has supervised numerous graduate and undergraduate students in areas like combinatorial design, fuzzy cognitive maps, and algorithmic graph theory. Her work bridges theoretical and applied graph theory, including applications in public health and educational research. She teaches courses ranging from introductory linear algebra to advanced topics in graph theory and combinatorics. Active in academic service, she has co-organized conferences and contributed to combinatorial enumeration and design theory. Her research group explores hypergraph symmetries, Eulerian properties, and graph applications in interdisciplinary contexts.

Benjamin EzeView profile

Adjunct Professor

• Big Data Analytics
• Cloud Data Warehousing
• Health Data Analytics and Integration
• +8 more

Benjamin Eze is a part-time and adjunct professor at the School of Engineering Design and Teaching Innovation within the University of Ottawa . He holds a PhD in Digital Transformation and Innovation, an MSc in Electronic Business Technologies, and a BSc in Computer Engineering. Professionally, he serves as Lead Architect at Next Pathway Inc. and Business Intelligence Partner with Champlain Ontario Health at Home. Education: PhD – Digital Transformation and Innovation (University of Ottawa) MSc – Electronic Business Technologies (University of Ottawa) BSc – Computer Engineering Benjamin specializes in Big Data Analytics , Healthcare Data Privacy , Cloud Computing , and AI in Software Engineering . His work bridges technology and healthcare, focusing on secure data integration and digital transformation. Scientific Awards: Holds two patents in Canada and the United States Benjamin's research spans healthcare data governance, cloud infrastructure (DevOps, DevSecOps), and privacy-preserving technologies. His publications emphasize systematic approaches to data anonymization, cloud-based healthcare monitoring, and ethical AI frameworks. He teaches in upskilling programs at the University of Ottawa’s Professional Development Institute, FxInnovation, and CENGN CloudCampus DevOps programs, while collaborating with organizations like Cisco, Montfort Hospital, and Accreditation Canada.

Hanifeh ImanianView profile

Adjunct Professor

• Application of artificial intelligence in climate prediction
• Hydrodynamics
• Computational fluid dynamics
• +3 more

Hanifeh Imanian is an Adjunct Professor of Water Resources Engineering at the Department of Civil Engineering, University of Ottawa, since 2022. She holds a PhD in Civil Engineering from Amirkabir University of Technology (Iran, 2012), focusing on numerical modeling of oil spill dispersion in marine environments. With over a decade of experience as a faculty member and department head in Iran, she conducted a sabbatical at the University of Ottawa in 2018, collaborating on AI-driven rail infrastructure monitoring with government partners. Her research interests span AI applications in climate prediction, computational fluid dynamics, hydro-environmental modeling, oil spill transport, and sediment dynamics. Over 20 peer-reviewed articles reflect her work on AI for soil moisture, soil temperature prediction, and spill modeling. Her 15+ years of teaching and research include supervising/co-supervising over 5 graduate students. Recent publications emphasize AI-driven environmental modeling, including soil temperature prediction under extreme conditions and oil spill dispersion analysis. Her collaborations bridge academic and industrial sectors, particularly in infrastructure and environmental monitoring systems.