IT for planetary health

The health of the planet is one of the most important challenges facing humanity today. From climate change to dangerous levels of air and water pollution to the erosion of coastal and agricultural lands, a number of serious challenges threaten human and ecosystem health.

Ensuring the health and safety of our planet requires approaches that link scientific, technical, social, economic and political aspects. New computational methods can play a critical role in providing data-driven models and solutions for cleaner air, usable water, resilient food, efficient transportation systems, better preserved biodiversity, and sources of energy. sustainable energy.

MIT Schwarzman College of Computing has pledged to hire several new faculty in climate and environmental computing, as part of MIT’s plan to recruit 20 climate-focused faculty as part of its action plan for the climate. This year, the college undertook a search of several departments in the schools of engineering and science for joint faculty in informatics and planetary health, one of six strategic areas of inquiry identified in a planning process at MIT-wide to help focus shared hiring efforts. The college has also undertaken a search for professors of basic computer science in the Department of Electrical Engineering and Computer Science (EECS).

The research is part of an ongoing effort by MIT Schwarzman College of Computing to hire 50 new faculty — 25 shared with other university departments and 25 in computer science and artificial intelligence and decision making. The goal is to build MIT’s capabilities to help infuse computer science and other disciplines more deeply into departments.

Four interdisciplinary researchers were hired in this research. They will join MIT faculty in the coming year to engage in research and teaching that will advance the physical understanding of low-carbon energy solutions, Earth climate modeling, monitoring and biodiversity conservation and agricultural management through high performance computing and transformational digital methods. and machine learning techniques.

“By coordinating hiring efforts with multiple departments and schools, we have been able to attract a cohort of outstanding scholars in this field to MIT. Each of them develops and uses advanced computational methods and tools to help find solutions to a range of climate and environmental problems,” says Daniel Huttenlocher, Dean of MIT Schwarzman College of Computing and Henry Warren Ellis Professor of Engineering. electrical and computer. . “They will also help strengthen cross-departmental computing ties in an important and critical area for MIT and the world.”

“These strategic hires in climate and environmental computing are an incredible opportunity for the college to deepen its academic offerings and create new opportunities for collaboration within MIT,” said Anantha P. Chandrakasan, Dean of the MIT School of Engineering and the Vannevar Bush Professor of Electrical Engineering and Computer Science. “The college plays a pivotal role in MIT’s overall effort to hire climate-focused faculty – introducing the critical role of computing in addressing the health of the planet through innovative research and curriculum.”

The four new teachers are:

Sara Beery will join MIT as an Assistant Professor in the Faculty of Artificial Intelligence and Decision Making at EECS in September 2023. Beery earned her PhD in Computer Science and Mathematical Sciences at Caltech in 2022, where she was advised by Pietro Perona. His research focuses on creating computer vision methods that enable global environmental and biodiversity monitoring through data modalities, tackling real-world challenges including strong correlations. spatiotemporal, imperfect data quality, fine-grained categories and long-tailed distributions. She partners with non-governmental organizations and government agencies to deploy her methods in the wild around the world and works to increase the diversity and accessibility of academic research in artificial intelligence through interdisciplinary capacity building and education.

Priya Donti will join MIT as an assistant professor in the faculties of Electrical Engineering and Artificial Intelligence and Decision Making at EECS in the 2023-24 academic year. Donti recently completed her PhD in the Department of Computer Science and the Department of Engineering and Public Policy at Carnegie Mellon University, co-directed by Zico Kolter and Inês Azevedo. His work focuses on machine learning for prediction, optimization and control in high renewable energy power grids. Specifically, his research explores methods to incorporate the physics and hard constraints associated with electrical power systems into deep learning models. Donti is also co-founder and president of Climate Change AI, a nonprofit initiative to catalyze impactful work at the intersection of climate change and machine learning currently taking place through the Cornell Tech postdoctoral program. Runway Startup.

Ericmoore Jossou will join MIT as an assistant professor in a position shared between the Department of Nuclear Science and Engineering and the Faculty of Electrical Engineering at EECS in July 2023. He is currently a Scientific Assistant at Brookhaven National Laboratory, a US Department of Energy. -affiliated laboratory that conducts research in the fields of nuclear and high energy physics, energy science and technology, environment and biosciences, nanosciences and national security. His research at MIT will focus on understanding the process-structure-properties correlation of materials for nuclear energy applications through advanced experiments, multi-scale simulations, and data science. Jossou received his Ph.D. in Mechanical Engineering in 2019 from the University of Saskatchewan.

Sherrie Wang will join MIT as an assistant professor in a position shared between the Department of Mechanical Engineering and the Institute for Data, Systems, and Society in the 2023-24 academic year. Wang is currently a Ciriacy-Wantrup Postdoctoral Fellow at the University of California, Berkeley, hosted by Solomon Hsiang and the Global Policy Lab. It develops machine learning for Earth observation data. Its main fields of application are the improvement of agricultural management and the forecasting of climatic phenomena. She received her PhD in Computer and Mathematical Engineering from Stanford University in 2021, where she was advised by David Lobell.

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Sherry J. Basler