Faculty profile
Christiane Lemieux
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Research
Latest papers
Efficient Simulation of a Leak-Detection-and-Repair Program.
ACS ES&T air · 2026 · first author
Message-Passing Monte Carlo: Generating low-discrepancy point sets via graph neural networks.
Proceedings of the National Academy of Sciences of the United States of America · 2024
Estimation and Applications of Uncertainty in Methane Emissions Quantification Technologies: A Bayesian Approach.
ACS ES&T air · 2024
Latest funding
- $90,000
Evaluation of Current and Emerging Methane Emission Quantification Tools for Upstream Oil and Gas Facilities
NSERC · 2021 · Co-investigator
- $120,000
Advances in sampling methods with a dependence structure
NSERC · 2020 · Principal investigator
- $1,650,000
NSERC CREATE Program on Machine Learning in Quantitative Finance and Business Analytics
NSERC · 2018 · Co-investigator
4 publications.
Efficient Simulation of a Leak-Detection-and-Repair Program.
Lemieux C, Daun KJ, Wigle A
Message-Passing Monte Carlo: Generating low-discrepancy point sets via graph neural networks.
Rusch TK, Kirk N, Bronstein MM, Lemieux C, Rus D
Estimation and Applications of Uncertainty in Methane Emissions Quantification Technologies: A Bayesian Approach.
Wigle A, Béliveau A, Blackmore D, Lapeyre P, Osadetz K, Lemieux C, Daun KJ
Quasi-Monte Carlo simulation of the light environment of plants.
Cieslak M, Lemieux C, Hanan J, Prusinkiewicz P
Evaluation of Current and Emerging Methane Emission Quantification Tools for Upstream Oil and Gas Facilities
Principal investigators: Daun, Kyle KJ
Keywords: climate change; methane emissions; monitoring; Monte Carlo simulation; regulations; spectroscopy; uncertainty quantification; upstream oil and gas
Advances in sampling methods with a dependence structure
Principal investigators: Lemieux, Christiane
Keywords: quasi-monte carlo; variance reduction; dependence; discrepancy; variation; importance sampling; adaptive sampling
NSERC CREATE Program on Machine Learning in Quantitative Finance and Business Analytics
Principal investigators: Morales, Manuel JM
Keywords: artifical intelligence; business analytics; deep learning; derivatives pricing and hedging; finfncial analytics; machine learning; mathematical modeling; portfolio management; quantitative finance; simulation and modeling
Design and analysis of efficient quasi-Monte Carlo sampling methods
Principal investigators: Lemieux, Christiane
Issues in high-dimensional quasi-monte carlo sampling
Principal investigators: Lemieux, Christiane
Highly-uniform point sets for integration and simulation
Principal investigators: Lemieux, Christiane
From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.
Frequent collaborators
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