Mehdi Rezvandehy
ATB Financial | Principal Data Scientist
Actions
Mehdi Rezvandehy is a Principal Data Scientist at ATB Financial with over a decade of experience leveraging machine learning and artificial intelligence to address complex challenges across banking, telecommunications, energy, and research domains. His expertise spans Large Language Models (LLMs), Generative AI, predictive modeling, and the design of scalable AI solutions that deliver measurable business value. Prior to joining ATB Financial, Mehdi worked as a Senior Data Scientist at Symend and a Principal Researcher at the University of Calgary. He holds a PhD in Geostatistics from the University of Alberta and is passionate about translating advanced AI and statistical research into practical, production-ready solutions that bridge the gap between academia and industry.
Area of Expertise
Machine Learning Simulation of Industrial CO2 Mitigation on Satellite Observations
Canada's climate goals require reliable methods to evaluate how industrial emission reductions translate into measurable atmospheric changes. Traditional bottom-up emission inventories identify emission sources but do not capture atmospheric transport, dispersion, or carbon uptake by natural sinks. While airborne and drone-based measurements provide detailed observations, they are expensive, cover limited geographic areas, and cannot support continuous, large-scale monitoring. This research addresses these limitations by integrating facility-level emission inventories with satellite-derived CO₂ observations using a machine learning framework.
The key innovation is the integration of industrial emissions and satellite-derived CO₂ fluxes into a unified spatial model that captures complex, non-linear relationships between emission sources and atmospheric response. The framework enables counterfactual simulations to estimate how specific emission reduction strategies affect atmospheric CO₂, providing a practical tool for evaluating mitigation scenarios. By moving beyond emission reporting to quantify real atmospheric impacts, this research supports more effective, evidence-based climate policy and industrial decarbonization planning.
Please note that Sessionize is not responsible for the accuracy or validity of the data provided by speakers. If you suspect this profile to be fake or spam, please let us know.
Jump to top