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Speaker Information

Alex Guillot is a dual-degree alumnus holding a B.S. in Systems Engineering and an M.S. in the Data Analytics & Statistics (DAS) program. After graduation, he worked for three years as a Research Assistant in the Division of Financial Stability at the Federal Reserve Board of Governors and later joined the International Monetary Fund as a Research Analyst in the Systemic Issues Division.
His work draws heavily on technical and quantitative methods, including machine learning, regression analysis, Kalman filtering, and dynamic programming. He has also contributed to teaching and coordination for Howard University’s Introduction to Statistical Programming course.

Tanner R. Cooper is an Associate and Senior Building Performance Consultant at IMEG, where he leads Monitoring & Analytics services focused on optimizing building performance and energy efficiency. His work includes energy audits and studies, commissioning and retro-commissioning, warranty period performance verification, and monitoring-based commissioning.
Tanner specializes in applying advanced analytics to improve building operations, validate system performance, and identify actionable energy-saving opportunities. He holds both a B.S. and M.S. in Mechanical Engineering from Washington University in St. Louis and is committed to data-driven strategies that support sustainability and decarbonization goals.

Patricio Salvatore La Rosa is a decision science and AI leader with over 20 years of experience bridging scientific research and industry innovation. He currently leads global analytics initiatives at Bayer Crop Science, deploying AI-driven decision intelligence systems to advance sustainability and operational efficiency. Previously, he held data science leadership roles at Monsanto, developing predictive and geospatial analytics solutions for precision agriculture.
Dr. La Rosa is also an Adjunct Faculty Member and Industrial Advisory Board member at Washington University in St. Louis, where he earned both his M.S. and Ph.D. in Electrical Engineering. He completed postdoctoral training in Biostatistics at the Washington University School of Medicine, focusing on experimental design and large-scale biological data analysis. His work integrates machine learning, statistical modeling, and decision systems across academia and industry.