Find Academic Supervisors

Olaf WeberView profile

Professor

• Sustainable Finance
• ESG Integration
• Climate Risk Management
• +5 more

Olaf Weber is a Professor and CIBC Chair in Sustainable Finance at the Schulich School of Business, York University . He also serves as a Senior Fellow at CIGI and Adjunct Professor at the School of Environment, Enterprise and Development (SEED), University of Waterloo . His research focuses on the intersection of finance, sustainability, and policy, particularly addressing how financial institutions can advance sustainable development goals (SDGs), manage climate risks, and integrate ESG principles into investment strategies. He is the Director of the Centre of Excellence in Responsible Business at Schulich. Key research areas include sustainable finance regulation , ESG performance measurement , transition finance , and green bond markets . Weber critiques Canada’s lag in sustainable finance leadership, emphasizing the need for stronger policy alignment between financial activities and climate goals. His work highlights challenges such as fossil fuel financing by Canadian banks and proposes solutions like public-private partnerships and stricter sustainability criteria for investments. He advises on climate stress testing , carbon pricing mechanisms , and the role of institutional investors in driving sustainable transitions. Weber’s interdisciplinary approach combines finance, environmental science, and policy to address global sustainability challenges. His research has been applied to sectors like renewable energy, water management, and microfinance.

Kenneth ZhouView profile

Associate Professor

• Statistics
• Actuarial Science

Kenneth Zhou is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. His academic profile indicates expertise in statistical methods and actuarial modeling, though specific research details are not provided in the source materials. Based on departmental affiliation, his work likely involves developing statistical models for risk assessment, insurance mathematics, or data analysis techniques. Zhou maintains an office in the Mathematics 3 building (M3 3131) and can be contacted via university email.

• Feminist Theory
• Marxian Theory
• Post/Anti/Decolonial Studies
• +8 more

Dia Da Costa is a Professor in the Department of Educational Policy Studies at the University of Alberta's Faculty of Education. She holds a PhD and specializes in decolonial, anti-caste, and feminist theories. Her work examines intersections of cultural politics, state violence, and development with a focus on South Asia and diasporic communities. Research focuses include: 1) Creative economy activism in India; 2) Colonialism's impact on cultural production across Asia and Americas; and 3) Caste-indigeneity connections in transnational contexts. SSHRC-funded projects include workshops on decolonizing creativity and studies of micro-insurance in agrarian India. Teaching emphasizes critical pedagogies through courses like Education and Social Change, Cross-Cultural Studies in Education, and International Development Education. Supervision priorities include decolonial methodologies, anti-racist education, and postcolonial history. Recent publications include a monograph on creative economy activism (2017) and articles in Antipode, Cultural Studies, and Journal of Peasant Studies. Collaborations include co-editing special issues on colonialism's cultural impacts and organizing international workshops.

Manuel MoralesView profile

Associate Professor

• Financial Mathematics
• Actuarial Science
• Machine Learning Applications in Finance
• +5 more

Manuel Morales is an Associate Professor in the Department of Mathematics and Statistics at the University of Montreal since 2005. He holds a Ph.D. in Mathematics (2003) from Concordia University, an M.Sc. in Statistics (2000) from Concordia, and a B.Sc. in Mathematics (1996) from the National Autonomous University of Mexico. His research focuses on Financial and Actuarial Mathematics, particularly in Ruin Theory, Lévy processes, and High-Frequency Finance. He leads applied projects integrating Machine Learning in Banking and ESG Investment, and has pioneered AI governance frameworks at the National Bank of Canada as their Chief AI Scientist. Education: Ph.D. Mathematics, Concordia University, 2003 M.Sc. Statistics, Concordia University, 2000 B.Sc. Mathematics, National Autonomous University of Mexico, 1996 Research Interests: His work spans theoretical and applied directions, including non-Gaussian option pricing, regime-switching models, Limit Order Book dynamics simulation, and AI applications in finance. He emphasizes responsible investment and ESG factors through alternative data analysis. Advising & Partnerships: Supervises Master’s/Ph.D. students in Insurance and Financial Mathematics. Leads the FinML Network (since 2018) and collaborates with industry partners like the National Bank of Canada on AI-driven financial projects. His grants and contracts enable applied research in high-frequency market surveillance and model governance. Labs & Teams: Directs the FinML Network and oversees the National Bank’s AI initiatives, focusing on AI governance and algorithmic trading strategies.

Liqun DiaoView profile

Associate Professor

• Statistical Methodology
• Machine Learning
• Causal Inference
• +7 more

Liqun Diao is an Associate Professor (Tenured) in the Department of Statistics and Actuarial Science at the University of Waterloo. He holds affiliations with the Health Data Science Lab and the Waterloo Artificial Intelligence Institute. His research focuses on developing statistical methods and machine learning algorithms for applications in medicine, public health, and insurance. Education: B.Econ. in Statistics, Renmin University of China (2007) M.Math. in Statistics (Biostatistics), University of Waterloo (2009) Ph.D. in Statistics (Biostatistics), University of Waterloo (2013) Research Interests: Recursive partitioning and tree-based methods for survival and health data Causal inference and missing data methodologies Bayesian nonparametric models and copula dependence structures Mortality forecasting and actuarial science applications Awards: 2013 Pierre Robillard Award (best doctoral thesis in Canadian statistics) 2024 Outstanding Performance and Teaching Awards at UW Professional Activities: Led research groups in health data science and AI Recipient of multiple grants from NSERC and industry partners Advises graduate students in statistics and actuarial science Labs/Teams: Active contributor to the Health Data Science Lab and Waterloo AI Institute, focusing on applying statistical innovations to real-world health and insurance challenges.

Philippe GachonView profile

Professor

• Hydro-climatology
• Climate Risk Assessment
• Extreme Weather Events
• +4 more

Philippe Gachon is a Professor in the Department of Geography at the University of Quebec at Montreal (UQAM), Director of the ESCER Research Centre, and leader of the Quebec InterSectoral Flooding Network (RIISQ). He specializes in hydro-climatology and climate risk assessment, with extensive experience at Environment Canada and as a Strategic Research Chair holder on Hydrometeorological Risks Related to Climate Change. His research examines climate change impacts on extreme weather events including floods, droughts, and heat waves. Recent work focuses on improving risk identification and adaptation strategies through intersectoral approaches. Key research themes include: Regional climate modeling and validation Hydro-meteorological hazard intensification Systemic risk assessment Community-scale resilience building Climate services development His recent publications demonstrate advanced statistical approaches for modeling non-stationary flood regimes, evaluating wildfire risks under climate change, and quantifying vector-borne disease transmission. Collaborative projects with 16 universities address physical climate risks and socioeconomic vulnerabilities across Quebec.

Andrei L. BadescuView profile

Professor

• Risk and Ruin Theory
• Matrix Analytic Methods
• Stochastic Claim Reserving
• +6 more

Andrei L. Badescu is a Professor of Actuarial Science and Director of the Master of Financial Insurance in the Department of Statistical Sciences at the University of Toronto. His academic leadership spans editorial roles at Insurance: Mathematics and Economics and program direction for graduate actuarial programs. His educational foundation includes: BSc in Mathematics and Economics from Bucharest University of Economic Studies (1998) MSc in Mathematics and Economics from Bucharest University of Economic Studies (2000) PhD in Actuarial Science from Western University (2004) He completed postdoctoral training at the University of Waterloo (2006) before joining the University of Toronto faculty in 2006. Research interests evolved from foundational work in Risk and Ruin Theory using Matrix Analytic Methods to contemporary applications in Stochastic Claim Reserving, Dependence Modelling, and Predictive Analytics. Current emphases include Telematics risk assessment and Insurance Data Science, leveraging advanced statistical techniques for real-world insurance challenges. Recent publications (2021-2025) reveal a strategic shift toward data-driven insurance solutions. Key trends include micro-level claim reserving via inverse probability weighting, telematics-based driving risk modeling using unsupervised learning, and mixture-of-experts frameworks for portfolio ratemaking. These works bridge traditional actuarial science with machine learning, particularly in handling censored data and operational risk. Professor Badescu mentors five doctoral students (Spark Tseung, Sebastian Calcetero, Ian Weng, Sophia Chan, Hassan Abdelrahman) and two master's students (Kaihua Sun, Yifeng Ge). His administrative leadership includes directing the Master of Financial Insurance program and previously overseeing the Data Science concentration in the Master of Applied Computing. His research group develops practical tools like the LRMoE.jl software package for actuarial loss modeling, while future work targets telematics integration and insurance-specific artificial intelligence applications.

Milton BoydView profile

Professor

• Quantitative Finance
• Risk Management
• Derivatives
• +7 more

Milton Boyd is a Professor in the Department of Agribusiness and Agricultural Economics at the University of Manitoba, Faculty of Agricultural and Food Sciences. He also serves as an Adjunct Professor in Risk Management and Actuarial Science at the Asper School of Business. His research and teaching focus on quantitative finance, risk management, derivatives, and international business. PhD, Purdue University, United States MA, Washington State University, United States BA, Seattle Pacific University, United States His research interests center on quantitative finance and agricultural risk management , with a strong emphasis on derivatives, portfolio strategies, and market behavior. He applies statistical and financial modeling to real-world agricultural and commodity markets, often integrating international and policy perspectives. His work bridges academic rigor with practical application in agribusiness and government sectors. His recent publications reflect a consistent focus on financial risk modeling, commodity pricing, and market efficiency. Themes include hedging strategies, volatility analysis, and the role of futures markets in price discovery and income stability. His work spans both developed and emerging markets, with increasing attention to Asia and global trade dynamics. Two University of Manitoba Awards for Research and Outreach Fellow of Seattle Pacific University Best Conference Presentation Award Outstanding Journal Paper Award Dr. Boyd has advised numerous graduate students and contributed to academic service through editorial roles, conference committees, and keynote presentations. He has secured research funding through university and external grants, though specific grants are not listed. His outreach includes media commentary, industry training, and policy advising, particularly in commodity market development. He has been actively involved in professional development and public service, including teaching short courses at the Winnipeg Commodity Exchange (ICE), Canadian International Grains Institute, and Canadian Securities Course. He has served as a Policy Advisor for the Frontier Center for Public Policy and as a columnist for Grainews , contributing to public understanding of financial and commodity markets.

• Microeconomics
• Industrial Organization
• International Trade
• +2 more

Elie Appelbaum is Professor of Economics at York University's Department of Economics. His research spans microeconomic theory, industrial organization, and international trade policy. Current research interests include trade agreements as insurance mechanisms, stochastic dominance in medical decisions, carbon tax policies, and dynamic conflict models. His work bridges economic theory with practical policy applications. Professor Appelbaum maintains an active research profile with publications in high-impact journals across microeconomics, trade theory, and applied game theory.

Edward FurmanView profile

Professor

• Actuarial Science
• Risk Management
• Insurance
• +6 more

Dr. Edward Furman is a Professor in the Department of Mathematics and Statistics at York University, leading the Actuarial Science Program and serving as Founding Director of the Risk and Insurance Studies Centre (RISC). He holds a Master's (Distinction) and PhD (Summa Cum Laude) in Actuarial Science and Probability Theory from the University of Haifa, Israel. His research focuses on distribution theory, risk measurement, insurance pricing, and systemic risk modeling. Notable achievements include winning the Fortis Chair Best Paper Prize (K. U. Leuven) for collaborative work and serving as an external consultant for institutions like the Central Bureau of Statistics (Israel) and the Society of Actuaries (U.S.). Dr. Furman's work bridges theoretical and applied domains, with funded research by NSERC, the Society of Actuaries, and the Casualty Actuarial Society. He is a Fellow of the Science Leadership Program at the University of Toronto and an Associate Editor of the Journal of Statistical Distributions and Applications (Springer). His interdisciplinary RISC unit explores holistic approaches to insurance risk, integrating actuarial science with statistical and economic frameworks. Research Themes: Dependence modeling, risk capital allocation, systemic risk measurement, and inclusive insurance design. Consulting Expertise: Collaboration with public and private sector entities on actuarial and statistical challenges. Grants: Supported by NSERC, SOA, and CAS for projects on risk aggregation and insurance pricing models.

Sebastien BetermierView profile

Associate Professor

• Finance
• Asset Pricing
• Portfolio Management
• +5 more

Sebastien Betermier is an Associate Professor of Finance at the Desautels Faculty of Management, McGill University, and serves as Executive Director of the International Centre for Pension Management. He holds a PhD in Finance from the Haas School of Business, UC Berkeley, and has expertise in risk and return, portfolio management, pension systems, and sustainable finance. His research has been featured in top journals and media outlets like the Wall Street Journal and Financial Times. He teaches Applied Investments and Pension Funds courses at undergraduate and graduate levels. Education: PhD, Finance, University of California, Berkeley (Haas), USA MSc, Finance, University of California, Berkeley (Haas), USA AB, Economics & International Relations, University of California, Davis, USA Research Focus: Professor Betermier explores asset pricing, delegated asset management, and the design of sustainable retirement systems. His work emphasizes pension fund strategies, household finance, and ESG integration in investments. Recent studies include analyses of Canadian pension models, green urban development via impact investing, and ETF market dynamics. Teaching & Recognition: A屡获殊荣的 educator, he received the Desautels Distinguished Teaching Award (2016, 2020) and coached winning teams in the PRMIA Risk Management Challenge (2016-2019). His accolades include being named one of the 'World's Best 40 Under 40 Business School Professors' by Poets & Quants (2017). Awards & Grants: 2021 Morgan Stanley Best Paper Award SSHRC Insight Grants (2023, 2020) Global Risk Institute Research Award (2024) Leadership Roles: He coordinates the Finance Area at Desautels, directs the McGill International Portfolio Challenge, and advises the Bank of Canada. His research informs policy through affiliations with the National Pension Hub and Global Risk Institute.

Gord WillmotView profile

Professor

• Actuarial Science
• Insurance Mathematics
• Ruin Theory
• +5 more

Gord Willmot is a Professor in the Department of Statistics and Actuarial Science at the University of Waterloo and an Adjunct Professor at the University of Toronto. He holds the endowed position of Munich Re Professor of Insurance. His research focuses on insurance mathematics, particularly aggregate claims models, ruin theory, and surplus analysis using tools from applied probability and mathematical reliability theory. He is a co-author of the textbook Loss Models , widely used in professional actuarial exams. Willmot earned his BMath (1980), MMath (1981), and PhD (1986) from the University of Waterloo. He is a Fellow of the Society of Actuaries (F.S.A.) and the Canadian Institute of Actuaries (F.C.I.A.). His work includes contributions to discounted penalty functions, Laplace transform techniques, and phase-type distributions in risk analysis. He has taught at international conferences, including the Ninth International Congress on Insurance: Mathematics and Economics. Key research areas include ruin probability analysis, time-dependent risk models, and reinsurance treaties. His publications span journals like Insurance: Mathematics and Economics and Scandinavian Actuarial Journal , addressing topics such as Coxian interclaim times, mixed Erlang distributions, and deficit analysis at ruin. Willmot’s expertise bridges theoretical advancements and practical applications in insurance risk management.

Fan YangView profile

Associate Professor

• Quantitative Risk Management
• Actuarial Science
• Extreme Value Theory
• +5 more

Fan Yang is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. His research focuses on quantitative risk management and actuarial science, with emphasis on extreme value theory, asymptotic analysis of rare events, and heavy-tailed distributions. He holds a PhD in Applied Mathematical and Computational Sciences from the University of Iowa (2013), and BS degrees in Computational Mathematics and International Economics & Trade from Xi’an Jiaotong University (2008). Education: PhD, Applied Mathematical and Computational Sciences, University of Iowa, 2008–2013 MS, Mathematics, University of Iowa, 2008–2010 BS, Computational Mathematics, Xi’an Jiaotong University, 2004–2008 BS (minor), International Economics and Trade, Xi’an Jiaotong University, 2004–2008 Research Interests: Yang’s work addresses theoretical and applied aspects of risk modeling in insurance and finance. Key areas include extreme value theory for financial and insurance risks, asymptotic analysis of rare events, risk aggregation under dependence structures, and heavy-tailed distribution modeling. His research bridges mathematical rigor with practical applications in risk management, including catastrophe insurance and portfolio diversification. Publications: His recent work examines topics like asymptotic portfolio diversification, CAT bond premium prediction, and extreme risk estimation using copula models. These studies highlight trends in quantifying and managing extreme risks through advanced statistical methods. Awards: No specific prizes or fellowships are noted in the provided texts. Teaching & Service: Yang teaches courses on advanced actuarial topics including extreme value theory, quantitative risk management, and financial mathematics. He actively contributes to the academic community through peer-reviewed publications and graduate supervision.

Keith FreelandView profile

Associate Professor

• Mathematical Finance
• Financial Risk Management
• Equity-Linked Insurance Products
• +3 more

Keith Freeland is an Associate Professor (Teaching Stream) at the University of Waterloo's Department of Statistics and Actuarial Science, and Director of the Business Administration and Mathematics Double Degree Program. He holds a PhD in Business Administration from the University of British Columbia and a BSc in Actuarial Science from the University of Calgary. His career includes roles as an assistant professor at Waterloo from 2000–2010. Research interests historically focused on equity-linked insurance products and discrete-valued time series analysis, though he is no longer actively researching. He teaches courses like MATBUS 470 (Derivatives) and MATBUS 472 (Risk Management), emphasizing mathematical finance and financial risk management. Notable publications include work on categorical ARMA models, quasi-locally powerful tests for conditional variance, and integer-valued time series analysis. He holds the ASA designation from the Society of Actuaries (1991). Freeland's contributions bridge actuarial science, statistics, and financial mathematics, with teaching and past research centered on practical applications in risk management and insurance product modeling.

• Health Informatics
• Fraud Detection
• Cybersecurity
• +6 more

Dr. Fletcher Lu is an Associate Professor in the Department of Information Technology at the Faculty of Business and Information Technology, Ontario Tech University. His academic journey includes a PhD in Artificial Intelligence (specializing in Machine Learning) and a Master of Mathematics in Scientific Computation, both from the University of Waterloo. He also holds a Bachelor of Math in Computer Science from the same institution. His postdoctoral research at the Canadian Institute of Chartered Accountants (CIAC) focused on insurance fraud detection. His education includes: PhD in Artificial Intelligence, University of Waterloo Master of Mathematics in Scientific Computation, University of Waterloo Bachelor of Math in Computer Science, University of Waterloo Dr. Lu’s research interests span health informatics, fraud detection (including cybercrime and insurance fraud), and the application of machine learning and numerical analysis to business and health challenges. He has developed mobile technology applications to improve youth fitness and pioneered adaptive fraud pattern analysis in health insurance data. His work intersects with cybersecurity, data analytics, and gaming, emphasizing real-world collaborations with organizations such as Manulife Financial, the Canadian Department of National Defence, and Medavie Blue Cross. His recent publications highlight trends in supply chain resilience, optimization methodologies, and disruption risk analysis. These include studies on EV infrastructure planning, stochastic distribution networks, and Benders decomposition strategies for reliable systems design. Dr. Lu has received significant awards, including: First place at CORS 2014 Practice Prize Third place at INFORMS 2013 interactive poster sessions His research has been funded by the National Science Foundation, Ontario Partnership for Innovation and Commercialization, and NSERC. He is affiliated with the Business Analytics & AI Research Group, contributing to decision-making systems and data-driven solutions for business and health sectors.