Panagiota (Nota) Klentrou is a Distinguished Professor and Dean of the Faculty of Applied Health Sciences at Brock University, specializing in Kinesiology. Her research focuses on exercise physiology , bone development , and the health implications of sport training in youth , particularly examining cellular mechanisms linking exercise, diet, and lifelong bone health. Supported by NSERC, CIHR, Osteoporosis Canada, and the International Gymnastics Federation Education: PhD, FCSEP (Fellow of the Canadian Society of Exercise Physiology) Her work spans bone physiology , inflammatory responses to exercise , and sclerostin-mediated tissue cross-talk , with recent studies exploring the impact of obesogenic diets , acute exercise , and nutritional interventions on skeletal growth and adaptation. Key findings include the role of sprint interval training in modulating adipose tissue Wnt signaling and the effects of dairy consumption on bone turnover markers. Scientific Awards & Distinctions Fellow, Canadian Society for Exercise Physiology (CSEP), 2020 Marilyn Rose Graduate Leadership Award, 2017 TVO's Best Lecturer nominee, 2010 Chancellor’s Chair for Research Excellence, Brock University, 2009 Award for Distinguished Research & Creative Activity, Brock University, 2006 Dr. Klentrou actively supervises graduate and undergraduate students in projects related to bone physiology , inflammation , and exercise adaptation , and collaborates with organizations like Osteoporosis Canada and the International Gymnastics Federation.
Minyi Huang is a Professor in the School of Mathematics and Statistics at Carleton University. His research focuses on Mean Field Stochastic Control, Stochastic Algorithms in Multi-Agent Systems, and Wireless Networks. He holds a Ph.D. from McGill University (2003) and has held postdoctoral positions at the University of Melbourne and the Australian National University. Dr. Huang is a Fellow of IEEE and a Member of SIAM. Education: Ph.D. in Electrical and Computer Engineering, McGill University (2003) M.Sc. in Systems and Control, Chinese Academy of Sciences (Beijing) B.Sc. in Mathematics, Shandong University (Jinan, China) Research Interests: Huang's work centers on stochastic control, mean field games, and multi-agent systems. His contributions include theoretical advancements in mean field social optimization, graphon-based control frameworks, and applications in wireless networks and economic models. He has organized workshops on Mathematical Cybernetics and Stochastic Processes, fostering interdisciplinary collaboration. Scientific Awards: Fellow of the IEEE Advising & Grants: Huang has advised numerous graduate students on topics in stochastic control and mean field theory. His grants include funding for international PhD students through Carleton's initiatives. He collaborates on projects involving mean field models for production output and social dynamics. Labs/Teams: Associated with the Ottawa-Carleton Institute for Mathematics and Statistics (OCIMS), contributing to collaborative research in control theory and applied mathematics.
Gabriela V. Cohen Freue is an Associate Professor in the Department of Statistics at the University of British Columbia (UBC), Vancouver Campus, and holds a Canada Research Chair (CRC Tier 2). She leads an interdisciplinary research program focusing on developing robust statistical methodologies for analyzing high-dimensional data in genomics and proteomics, with applications in medical sciences. Her work addresses challenges such as outliers, collinearity, and measurement errors, with applications in biomarker discovery for diseases like multiple sclerosis, cardiovascular disorders, and asthma. Her academic journey includes collaborations across disciplines, including with the BC Cancer Agency, PROOF Centre of Excellence, and iCAPTURE. She has pioneered methods like the Penalized Elastic Net S-Estimator (PENSE) and contributed to proteomic data analysis tools such as the Protein Group Code Algorithm (PGCA). She also co-developed the MDQC quality control method for microarrays. Research interests include robust regression, biomarker development, and statistical methods for big data. Her team includes postdocs, PhD, and MSc students, with a focus on training in both statistical rigor and interdisciplinary collaboration. Notable grants include a CANSSI Collaborative Research Team Project (CRT) award for robust causal inference and prediction modeling. Teaching responsibilities span statistical consulting, high-dimensional biological data analysis, and generalized linear models. She emphasizes active learning and real-world problem-solving in her courses. Her lab’s work is supported by grants from the Data Science Institute (DSI) and collaborations with institutions like the PROOF Centre. Alumni of her group hold positions in academia (e.g., George Mason University) and industry (e.g., Merck, BC Cancer Research Centre).
Michael Krisinger is an Associate Professor of Teaching in the Department of Biochemistry & Molecular Biology at the University of British Columbia . He began his teaching career in 2010, transitioning to full-time in 2013. He lectures Biochemistry 202 (Introductory Medical Biochemistry) and Biochemistry 303 (Molecular Biochemistry) while serving as a tutor in the Faculty of Medicine's Case Based Learning program. Krisinger co-developed the department's two-course summer program for international students and mentors postdoctoral fellows in teaching. He also manages the department's CANVAS digital learning platform. Krisinger's research focuses on the molecular mechanisms of coagulation and complement system regulation , particularly their evolutionary relationship and functional interplay. His work has explored thrombin's role in complement activation, polyphosphate-mediated complement suppression, and nanoparticle surface interactions with proteolytic cascades. He previously co-supervised graduate students at UBC's Centre for Blood Research before prioritizing education. Publications highlight his expertise in protease-substrate dynamics , lipoprotein-phospholipid interactions , and hemostasis-immunity crosstalk . He remains engaged in public science through community environmental initiatives and local outreach activities.
Mohammad Hamdaqa is an Associate Professor in the Department of Computer Engineering and Software Engineering at Polytechnique Montréal, where he leads the Laboratory of Software and Emerging Technologies. His academic journey includes a Ph.D. in Electrical and Computer Engineering from the University of Waterloo (2016), a Master's in Electrical and Computer Engineering from Concordia University, an MBA from the New York Institute of Technology, and a Bachelor's in Computer Engineering from Jordan University of Science and Technology. His research focuses on the intersection of software engineering and emerging technologies, particularly examining how software engineering approaches can be adapted for complex new platforms like cloud computing and blockchain. His work spans model-driven software engineering, cloud application architecture, smart contract development, and infrastructure as code. He investigates both how traditional software engineering practices can evolve to address the challenges of modern distributed systems and how emerging technologies can transform software development processes themselves. Analysis of his recent publications reveals a strong emphasis on blockchain technologies (particularly smart contracts), cloud-native applications, and the application of AI to software engineering tasks. His work shows a consistent thread of empirical research combined with practical tool development, with increasing focus on sustainability aspects of software systems in recent years. Much of his research bridges theoretical foundations with practical implementation concerns. Professor Hamdaqa serves as a thesis supervisor for multiple graduate students, with recent completed Master's theses focusing on smart contract auditing, prompt engineering for OCL generation, model-driven epidemiology, and security practices in infrastructure as code. He actively recruits students for research projects in his laboratory. He is a member of both the IEEE Computer Society and the Association for Computing Machinery (ACM), has served on program committees for major software engineering conferences, and is on the editorial board of Service Transaction on Internet of Thing. His laboratory, the Laboratory of Software and Emerging Technologies, serves as the hub for his research activities in blockchain, cloud computing, and model-driven engineering.
Raouf Boutaba is a Professor at the University of Waterloo , serving as Director of the David R. Cheriton School of Computer Science since July 2020. He holds prestigious fellowships including FRSC , FIEEE , FIEC , and FCAE . 2024: Inaugural Rogers Chair in Network Automation 2024: Ontario Research Fund–Research Excellence (ORF–RE) $2M grant for next-gen mobile networks 2021: University Professor title, University of Waterloo Research Interests span network automation, resource management in wired/wireless networks, network function virtualization (NFV), software-defined networking (SDN), cloud computing, blockchain, future Internet architecture, and cybersecurity. His work focuses on zero-touch networks, 5G/B5G slicing, and AI-driven orchestration. Scientific Contributions include 15+ recent publications on topics like reinforcement learning for RAN slicing, encrypted traffic classification, quantum network optimization, and self-driving infrastructure. His projects 5G LEAP and 5G ELITE explore network isolation and Open RAN principles. 2024: IFIP/IEEE CNOM Test of Time Paper Award 2024: Graduate Supervision Excellence Award 2021: Kenneth C. Sevcik Outstanding Student Paper Award (advisor) Teaching includes co-developing the NSERC CREATE Network Softwarization program, offering courses like Network Softwarization: Principles and Foundations (Winter 2024) and Technologies and Enablers since 2018. He emphasizes hands-on training in SDN, NFV, Open RAN, and 5G. Students and Collaborations : Supervised PhD students such as Shihabur R. Chowdhury (2021), Nashid Shahriar (2020), and undergrad Leni Aniva (2022 Gov. Gen. Silver Medal ). His team includes researchers working on 5G, blockchain, and AI-driven network management. Professional Leadership : Organized Rogers TEP Workshops (2024-2025), delivered keynotes at IEEE Globecom, ColCom, and BalkanCom, and served on expert panels for AI orchestration and 5G cybersecurity at major symposia.
Dr. Mahesh Tripunitara is a Professor in the Department of Electrical and Computer Engineering at the University of Waterloo, serving as Associate Chair for Undergraduate Studies. He holds a PhD (2005) and Master's (1995) in Computer Science from Purdue University, along with a BSc (1993) in Computer Science from Dalhousie University. His research focuses on information security, authorization mechanisms, cryptographic key management, and hardware security, with industry experience at Motorola's R&D labs and Silicon Valley. His work spans theoretical advancements like access control policy analysis and practical applications such as secure payments systems and IoT device reliability. Notable awards include the Best Student Paper at Usenix Security 2013 and Best Paper at ACM SACMAT 2013. He actively serves on program committees for major security conferences including CCS, CODASPY, and SACMAT. Recent publications highlight innovations in cellular security (SUCI-Catchers defense), role-mining optimization, and blockchain smart contract auditing. Teaching includes advanced algorithm design courses (ECE 406/606) and digital computation (BME 121). His research emphasizes balancing security rigor with usability in authorization systems and hardware protection mechanisms.
Manolis Savva is an Associate Professor in the School of Computing Science at Simon Fraser University and holds the Canada Research Chair in Computer Graphics. He specializes in 3D scene analysis, generative methods for 3D content, and computer graphics for AI. His research bridges computer graphics, vision, and robotics. Education: Ph.D. (Computer Science, Stanford University, 2016), MS (Computer Science, Stanford, 2012), B.A. (Physics & Computer Science, Cornell, 2009). Research Interests: Human-centric 3D scene analysis, generative 3D content creation, AI-driven rendering, and applications in robotics. Key projects include Habitat (Embodied AI platform), ScanNet , and ShapeNet datasets. Recent Articles: Focus on articulated object modeling, 3D scene synthesis, and AI-driven visualization. Notable work includes SceneMotifCoder (generating object arrangements) and R3DS (panoramic scene understanding). Awards: CHCCS Early Career Award (2022), ICLR 2023 Outstanding Paper Award, ICCV 2019 Best Paper Nomination, and SGP 2020 Dataset Award (ScanNet). Lab/Teams: Leads research groups in 3DLG (3D Learning and Graphics) and GrUVi (Graphics and Vision). Collaborates on projects like AI Habitat and HomeRobot .
Dr. Luke Fleming is an Associate Professor in the Department of Anthropology at the University of Montreal's Faculty of Arts and Sciences. His research focuses on comparative linguistic anthropology, particularly the typology of honorific systems, kinship-related linguistic avoidance practices, and sociolinguistic dynamics in indigenous and small-scale societies. He has authored over 20 peer-reviewed publications and led numerous research projects funded by the Social Sciences and Humanities Research Council of Canada (SSHRC) and international institutions. Teaching responsibilities include courses on sociolinguistics, linguistic anthropology, and language and culture. He supervises graduate students engaged in interdisciplinary research spanning from Sri Lanka to the Amazon basin. Current projects investigate honorific pronoun systems across Theravada Buddhist communities and Tamil language usage in South Asia. Lead researcher for SSHRC-funded projects studying honorific systems and small-scale sociolinguistics Published in Journal of Linguistic Anthropology , Language in Society , and Anthropological Linguistics Advisor to 9 graduate students since 2018 Research networks include collaborative projects with Patagonian language speakers and ongoing comparative studies linking Southeast Asian honorifics to African avoidance practices. His forthcoming book On Speaking Terms examines kinship-related linguistic avoidance worldwide. Active in program development for interdisciplinary anthropology degrees, contributing to 15 academic programs at undergraduate and graduate levels.
Soosan Beheshti is a Professor and Program Director in the Department of Electrical, Computer, and Biomedical Engineering at Toronto Metropolitan University. She holds a B.S. from Isfahan University of Technology and M.S./Ph.D. from MIT. Her research focuses on signal processing, statistical learning, and information theory, with applications in biomedical systems, data denoising, and system modeling. She has received awards such as the Dean's Teaching Award (2010) and the EECS Carlton E. Tucker Award (1998). Education: B.S., Electrical Engineering, Isfahan University of Technology (1996) M.S. & Ph.D., Electrical Engineering, MIT (2002) Research Interests: Statistical Signal Processing Information Theory Data Denoising & Compression System Modeling & Control Machine Learning Applications Awards: Dean's Teaching Award (2010) Gold Paper Award (PacRim 2009) Best Paper Award (Remote Sensing 2008) MIT Teaching Excellence Award (1998) Teaching: Courses include Signals and Systems, Control Systems, and Statistical Inference. She has supervised numerous graduate students and postdocs in her Signal and Information Processing (SIP) Lab. Labs/Teams: Director of the SIP Lab, conducting research in signal processing, information theory, and biomedical applications. Collaborates with industry partners like Myant Inc. and Huawei Technologies.
Dr. Saman Razavi is an Associate Professor at the University of Saskatchewan, holding dual appointments in the School of Environment and Sustainability (SENS) and the Department of Civil, Geological and Environmental Engineering in the College of Engineering. He is a member of the Global Institute for Water Security and leads the Razavi EnviroFutures Lab. His research focuses on hydrological modeling, water resources management, climate change impacts, and the integration of machine learning with environmental science. Dr. Razavi has earned a PhD in Civil and Environmental Engineering from the University of Waterloo. Education: PhD in Civil and Environmental Engineering, University of Waterloo MS in Civil and Environmental Engineering, Amirkabir University, Iran BS in Civil Engineering, Iran University of Science and Technology Research interests include hydrologic model development, optimization, uncertainty quantification, climate change analysis, and socio-hydrological modeling. He emphasizes interdisciplinary approaches to address water challenges through integrated frameworks that bridge natural science, engineering, and socio-economic factors. Award: Walter L. Huber Civil Engineering Research Prize from ASCE (2024) Advising & Grants: Dr. Razavi leads the Integrated Modelling Program for Canada under Global Water Futures, focusing on transboundary water systems. His work involves developing decision-support tools for flood/drought management and climate adaptation. Labs/Teams: The Razavi EnviroFutures Lab advances research on water-human systems, leveraging AI and big data to enhance resilience against water-related hazards. Current projects include flood-prone area mapping, drought prediction, and socio-hydrological modeling in transboundary basins.
Ben Bloem-Reddy is an Assistant Professor in the Department of Statistics at the University of British Columbia (UBC), Vancouver Campus. His research focuses on statistical theory and applications in machine learning, particularly in causal inference, Bayesian methods, neural networks, and probabilistic models. He advises current students Quanhan (Johnny) Xi, Kenny Chiu, and Gian Carlo Diluvi. His work bridges foundational statistical theory with practical machine learning challenges, including causal discovery, model identifiability, and uncertainty quantification. Recent research explores topics such as latent variable models, generative processes, and symmetry in data and algorithms. His contributions span interdisciplinary areas like particle physics applications and information theory-based compression techniques. Ben’s research trends emphasize advancing theoretical guarantees for modern machine learning systems while addressing real-world problems. His publications frequently intersect with algebraic topology (e.g., cocycles in causal inference) and nonparametric methods. He maintains an active lab within the Department of Statistics, fostering collaborations across UBC’s academic ecosystem. No scientific awards are explicitly listed in the provided information. His advising and grant activities focus on statistical methodology development, as evidenced by his student supervision and published work. His office is located in ESB 3168, and he can be reached at benbr@stat.ubc.ca.
Stephen L. Bearne is a Professor in the Departments of Biochemistry and Molecular Biology and Chemistry at Dalhousie University, affiliated with the Faculty of Medicine. He has been a department member since 1996 and served as Department Head from 2012 to 2022. His research focuses on enzymology, enzyme catalysis, and protein engineering, with a particular emphasis on transition state analogues, enzyme inhibition mechanisms, and the chemical basis of disease-associated enzymes. His work integrates organic synthesis, biophysical techniques, and computational modeling to explore enzyme function and design inhibitors for therapeutic applications. Dr. Bearne holds a PhD from the University of Toronto and an MDCM from McGill University. His lab is part of the Protein Assembly Research Team and the BioActives CREATE Training Program. Current research themes include understanding carbon acid substrate catalysis in mandelate racemase, developing inhibitors for CTP synthase and racemases involved in diseases like cancer and neglected tropical infections, and proteomic tools for enzymatic activity profiling. His research leverages advanced techniques such as site-directed mutagenesis, isothermal titration calorimetry, NMR spectroscopy, and macroion mobility spectrometry. His lab supports equity, diversity, and inclusivity and has been funded by NSERC, CIHR, and other agencies. Recent publications highlight advancements in enzyme inhibition strategies, allosteric regulation mechanisms, and enzyme filamentation roles in metabolic pathways.
Tamon Stephen is a Professor in the Department of Mathematics at Simon Fraser University (SFU), part of the Faculty of Science. His research focuses on operations research, with an emphasis on combinatorial optimization, algorithms, discrete geometry, and computational biology. He holds a Ph.D. in Mathematics from the University of Michigan (2002). His work often bridges theoretical and computational aspects, addressing interdisciplinary applications. Stephen is affiliated with the Centre for Operations Research and Decision Sciences (CORDS) and has contributed to software tools for hypergraph transversals and colorful linear programming. He has taught courses such as Math 208W (Introduction to Operations Research) and has advised projects in metabolic network analysis and scheduling optimization. His office is located at the Surrey campus (SRYC 2886). Key research collaborations include studies on firefighter scheduling, nurse rostering, and metabolic pathway analysis. His methodologies often leverage algorithm design, polytope theory, and discrete mathematics. Stephen actively participates in academic service, organizing seminars and contributing to conferences such as the West Coast Optimization Meeting. His work emphasizes practical applications of theoretical results, with a focus on solving real-world optimization challenges.
Dr. Nancy L. Sin is an Associate Professor in the Department of Psychology within the Faculty of Arts at the University of British Columbia. She teaches undergraduate and graduate courses in health psychology and supervises students at multiple levels. She is Co-Chair of the Antiracism Task Force for the Society for Biopsychosocial Science and Medicine and a member of the Steering Committee at the UBC Edwin S.H. Leong Centre for Healthy Aging. Previously, she served on the Executive Committee for the American Psychological Association's Division on Adult Development and Aging and established the Diversity Mentorship Program. PhD, University of California, Riverside, 2012 Dr. Sin's research focuses on biological and behavioural pathways linking daily well-being and stress to health. Her work demonstrates that emotional responses to daily stressors are associated with inflammatory, neuroendocrine, and autonomic mechanisms implicated in aging-related conditions like cardiovascular disease. She investigates daily positive events as protective factors for stress processes and health, with particular interest in emotional well-being and aging, stress-sleep cycles, and health equity. Her research spans multiple disciplines including health psychology, gerontology, and social psychology. Analysis of Dr. Sin's recent publications reveals consistent focus on daily stress processes, positive emotions, and health outcomes across the lifespan. Her work increasingly examines pandemic-related stressors, social determinants of health, and health disparities, with strong emphasis on methodological rigor through daily diary and longitudinal approaches. The publications demonstrate interdisciplinary collaboration across psychology, public health, and medicine, with growing attention to diversity, equity, and inclusion in health research. Distinguished Alumni Award, Department of Psychology, University of California, Riverside (2025) Fellow, Gerontological Society of America (2025) Innovative Research on Aging Award (Bronze Award) from the Mather Institute (2021) Michael Smith Foundation for Health Research Scholar (2020) Springer Early Career Achievement Award in Research on Adult Development and Aging (2019) Gerontological Society of America's Behavioral and Social Sciences Student Research Award Editor's Choice article at Annals of Behavioral Medicine Dr. Sin actively supervises undergraduate, MA, and PhD students, with a current focus on Health Psychology graduate students specializing in adult development and aging, stress, and health equity/disparities. Her research has been supported by significant grants as PI or Co-I from the U.S. National Institute on Aging, Social Sciences and Humanities Research Council of Canada, Canadian Institutes of Health Research, Canada Foundation for Innovation, and the Michael Smith Foundation for Health Research. She has established a strong research program examining daily experiences and their health implications across adulthood. Dr. Sin directs the UPLIFT Health Lab (Understanding Pathways Linking Inter- and Intraindividual Factors To Health), which explores psychosocial well-being and biobehavioural mechanisms underlying healthy aging. The lab investigates how daily positive events promote health through lower inflammation, adaptive cortisol profiles, and better health behaviors, with particular attention to how positive emotions buffer stress processes. The lab actively recruits community participants for studies on daily experiences and health, contributing to intervention development for promoting psychological and physical well-being across adulthood.
