While infrastructure, both static and dynamic, is the driver of the modern global economy, it is also a significant contributor towards global climate change due to the increased emissions. Artificial intelligence (AI) provides a radical framework for mitigating emissions by improving efficiency in static infrastructure, as well as enhancing mobility in transportation through low-carbon transport options and reduction in overall travel time. Through this mini-colloquium, we hope to bring together researchers from varied fields employing AI on these strategies.
October 2022 Colloquium
Advances in AI for Sustainability
Colloquium Public Presentations: Oct. 6, 8:00am – 1:00pm
Remote via Zoom.
About the Speakers
Prof. Dr. Felix Creutzig is head of the working group Land Use, Infrastructures and Transport and Chair of Sustainability Economics at Technische Universität Berlin. He was lead author of the IPCC’s Fifth Assessment Report and lead analyst of the Global Energy Assessment. His research focuses on conceptualizing and quantifying GHG emissions of cities world-wide, assessing opportunities for GHG mitigation of cities world-wide and building models of sustainable urban form and transport.
Dr. Kaack is Assistant Professor of Computer Science and Public Policy at the Hertie School. Her research and teaching focus on methods from statistics and machine learning to inform climate mitigation policy across the energy sector, and she also has an interest in climate-related AI policy. She is a co-founder and chair of the organization Climate Change AI, and a member of the Austrian Council on Robotics and Artificial Intelligence, which is an advisory board of the Austrian Ministry for Climate Action.
Priya Donti is the Co-founder and Executive Director of Climate Change AI, a global non-profit initiative to catalyze impactful work at the intersection of climate change and machine learning, which she is currently running through the Cornell Tech Runway Startup Postdoc Program. She will also join MIT EECS as an Assistant Professor in Fall 2023. Her research focuses on machine learning for forecasting, optimization, and control in high-renewables power grids. Specifically, her work explores methods to incorporate the physics and hard constraints associated with electric power systems into deep learning workflows. 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 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.
Dr. Mohamed’s research focuses on the systemic evaluation of transportation networks to achieve sustainable and resilient transportation systems. He is a strong believer of zero-emission, sustainable, resilient transit systems that support the rise of smart communities. His research focuses on the utilization of disruptive technologies in public transit networks with emphasis on electric and autonomous technologies. In particular, he investigates the operational efficiency of disruptive technologies in public transit networks with emphasis on; operational reliability, environmental assessment, and total cost of ownership. His research also investigates the systemic impacts of the transit system on utility grid and energy demand.