Four new faculty members working on research and instruction that address climate hazards and other environmental challenges are welcomed to the MIT Schwarzman College of Computing.
One of the most significant problems that humanity is currently experiencing is the condition of the planet. A variety of major issues, including climate change, hazardous levels of air and water pollution, and erosion of agricultural and coastal land, pose a threat to the wellbeing of people and ecosystems.
It is necessary to use methods that link scientific, engineering, social, economic, and political issues in order to ensure the safety and health of our planet. By offering data-driven models and solutions for more breathable air, drinkable water, resilient food, effective transportation systems, better protected biodiversity, and sustainable energy sources, new computational tools can play a significant role.
As part of MIT’s strategy to appoint 20 faculty members with a focus on climate change as part of its climate action plan, the MIT Schwarzman College of Computing is committed to hiring a number of new professors in computing for climate and the environment. One of the six strategic areas of inquiry identified in an MIT-wide planning process to help focus shared hiring efforts was computing for the health of the planet. This year, the college undertook searches with several departments in the schools of Engineering and Science for shared faculty in this area. The Department of Electrical Engineering and Computer Science at the college conducted searches for core computer faculty members (EECS).
The MIT Schwarzman College of Computing is now conducting searches for 50 additional faculty members, 25 of whom will be shared with other academic departments and 25 of whom will specialise in computer science, artificial intelligence, and decision-making. The objective is to increase MIT’s capacity to aid in departments’ deeper integration of computing and other fields.
In these searches, four interdisciplinary scholars were hired. In the upcoming year, they will join the MIT faculty to conduct research and teach courses that will improve physical comprehension of low-carbon energy solutions, Earth-climate modelling, biodiversity monitoring and conservation, and agricultural management through high-performance computing, transformational numerical methods, and machine-learning techniques.
“We were able to bring a group of outstanding researchers in this field to MIT by combining hiring efforts with other departments and institutions. According to Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and Henry Warren Ellis Professor of Electrical Engineering and Computer Science, “each of them is creating and using cutting-edge computational methods and tools to assist in finding solutions for a variety of climate and environmental issues.” They will improve interdepartmental relationships in computing, a vital field for MIT and the rest of the globe.
Anantha P. Chandrakasan, dean of the MIT School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science, says that the college has a fantastic opportunity to deepen its academic offerings and open up new opportunities for collaboration across MIT with these strategic hires in the field of computing for climate and the environment. “The college plays a crucial part in MIT’s overall endeavour to hire academics who are climate-focused, introducing the crucial role of computing to address the health of the planet through creative research and courses.”
The four new professors are:
In September 2023, Sara Beery will start working at MIT as an assistant professor in the department of artificial intelligence and decision-making in EECS.
Pietro Perona served as Beery’s advisor as she pursued a PhD in computing and mathematical sciences at Caltech in 2022. Her work develops computer vision techniques to support multimodal global environmental and biodiversity monitoring, addressing practical issues such high spatiotemporal correlations, poor data quality, fine-grained categories, and long-tailed distributions. Through interdisciplinary capacity building and education, she strives to increase the diversity and accessibility of academic research in artificial intelligence. She collaborates with nongovernmental organisations and governmental organisations to deploy her methods in the wild throughout the world.
In the academic year 2023–2024, Priya Donti will join MIT as an assistant professor at the departments of Electrical Engineering and Artificial Intelligence and Decision-Making in EECS.
Donti recently received her PhD from Carnegie Mellon University’s Department of Engineering and Public Policy and Computer Science, under the joint supervision of Zico Kolter and Inês Azevedo. Her research focuses on using machine learning in high-renewable power networks for forecasting, optimization, and control. Her research specifically investigates ways to include the physics and rigid restrictions related to electric power systems in deep learning models. Donti is also the co-founder and chair of Climate Change AI, a nonprofit organisation that is currently being supported by the Cornell Tech Runway Startup Postdoc Program and aims to stimulate important research at the confluence of climate change and machine learning.
In July 2023, Ericmoore Jossou will start working at MIT as an assistant professor in a joint appointment with the faculty of electrical engineering in EECS and the Department of Nuclear Science and Engineering. He is currently an assistant scientist at the Brookhaven National Laboratory, a facility connected to the US Department of Energy that performs research in the fields of environmental and bioscience, energy science and technology, nanoscience, and national security. Through cutting-edge experiments, multiscale simulations, and data science, his work at MIT will be centred on understanding the processing-structure-properties correlation of materials for nuclear energy applications. 2019 saw Jossou graduate from the University of Saskatchewan with a PhD in mechanical engineering.
In the academic year 2023–2024, Sherrie Wang will start working at MIT as an assistant professor in a joint appointment held by the Department of Mechanical Engineering and the Institute for Data, Systems, and Society. In residence with Solomon Hsiang and the Global Policy Lab at the University of California, Berkeley, Wang is a Ciriacy-Wantrup Postdoctoral Fellow. She creates machine learning for information from Earth observation. Improving agriculture management and predicting climate events are her main application areas. In 2021, she graduated from Stanford University with a PhD in computational and mathematical engineering under David Lobell’s guidance.