Dr. Priya Donti is an Assistant Professor and the Silverman (1968) Family Career Development Professor at MIT EECS and LIDS. Her research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Methodologically, this entails exploring ways to incorporate relevant physics, hard constraints, and decision-making procedures into deep learning workflows.
Priya is also the co-founder and Chair of Climate Change AI, a global nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning. Priya received her Ph.D. in Computer Science and Public Policy from Carnegie Mellon University, and is a recipient of the MIT Technology Review’s 2021 “35 Innovators Under 35” award, the ACM SIGEnergy Doctoral Dissertation Award, the Siebel Scholarship, the U.S. Department of Energy Computational Science Graduate Fellowship, and best paper awards at ICML (honorable mention), ACM e-Energy (runner-up), PECI, the Duke Energy Data Analytics Symposium, and the NeurIPS workshop on AI for Social Good.
Keynote Address
Talk title: Optimization-in-the-loop ML for energy and climate
Date: Monday, July 29th, 2024
Time: 8:00 A.M.
Location: Grand Station Ballroom
Abstract:
Addressing climate change will require concerted action across society, including the development of innovative technologies. While methods from machine learning (ML) have the potential to play an important role, these methods often struggle to contend with the physics, hard constraints, and complex decision-making processes that are inherent to many climate and energy problems. To address these limitations, I present the framework of “optimization-in-the-loop ML,” and show how it can enable the design of ML models that explicitly capture relevant constraints and decision-making processes. For instance, this framework can be used to design learning-based controllers that provably enforce the stability criteria or operational constraints associated with the systems in which they operate. It can also enable the design of task-based learning procedures that are cognizant of the downstream decision-making processes for which a model’s outputs will be used. By significantly improving performance and preventing critical failures, such techniques can unlock the potential of ML for operating low-carbon power grids, improving energy efficiency in buildings, and addressing other high-impact problems of relevance to climate action.
Dr. Denise R. Simmons, Ph.D., PE, F.ASEE, PMP, LEED-AP is a distinguished figure in civil engineering education and workforce development. With tenure at the University of Florida's Department of Civil and Coastal Engineering, she blends deep academic knowledge with hands-on industry experience. With over three decades of work experience in positions across consulting, professional engineering, and academia, Dr. Simmons has served in diverse roles, from leadership positions in for-profit entities to guiding minority-serving institutions.
As the inaugural Associate Dean for Workforce Development in the Herbert Wertheim College of Engineering, her leadership highlights her unparalleled foresight and industry relevance. She has dedicated over a decade to engineering leadership roles in industry.
Her pioneering research, backed by $9M in federal funding and resulting in over 100 refereed articles, positions her at the nexus of civil engineering education and real-world applications. In 2023, her contributions earned her the grade of Fellow Member in the American Society for Engineering Education.
A fervent advocate for diversity, equity, and inclusion (DEI) in engineering, Dr. Simmons champions a business ethos where inclusivity aligns with profitability and societal impact. Esteemed in academia, Dr. Simmons' advisory role for numerous NSF grants underscores her reputation. Her expertise in deciphering industry challenges and tailoring solutions is unmatched, making her a sought-after consultant for academic institutions and businesses aiming to navigate the evolving engineering landscape.
Keynote Address
Talk title: From Concepts to Code: Programming the Future of Civil Engineering with Inclusion and Innovation
Date: Tuesday, July 30th, 2024
Time: 8:00 A.M.
Location: Grand Station Ballroom
Abstract:
In this keynote address, Dr. Denise R. Simmons explores the critical role of inclusion in driving innovation within the field of civil engineering. As the built environment faces unprecedented challenges, the integration of diverse perspectives and cutting-edge technologies becomes essential for sustainable and resilient solutions. Drawing on her extensive experience in workforce development and her pioneering research, Dr. Simmons will highlight strategies to prepare the next generation of civil engineers to meet these challenges. Attendees will gain insights into how fostering an inclusive and innovative culture can transform concepts into actionable strategies, ensuring a vibrant and forward-thinking future for civil engineering.