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    Home»Health»Computing for the Health of the Planet | MIT News
    Health

    Computing for the Health of the Planet | MIT News

    M.KaratasBy M.Karatas13. September 2022No Comments5 Mins Read
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    The health of our planet is one of the most important challenges facing humanity today. Many serious challenges threaten human and ecosystem health, from climate change to dangerous levels of air and water pollution to coastal and agricultural erosion.

    Ensuring the health and security of our planet requires an approach that brings together scientific, engineering, social, economic and political dimensions. By providing data-driven models and solutions for clean air, available water, resilient food, efficient transport systems, biodiversity conservation, and sustainable energy sources, new computational methods , can play an important role.

    MIT Schwartzman College of Computing has announced several new faculty members in computing for climate and environment as part of MIT’s plan to recruit 20 climate-focused faculty members under its Climate Action Plan. We are committed to adopting This year, the university teamed up with several departments of engineering and science to find a joint faculty member on computing and global health. This is one of six strategic research areas identified in the MIT-wide planning process to help focus common hiring efforts. The university also searched for a Core Computing Faculty in the Department of Electrical Engineering and Computer Science (EECS).

    The research is part of an ongoing effort by the MIT Schwartzman College of Computing to hire 50 new faculty members, 25 of whom will be shared with other departments and 25 in computer science, artificial intelligence, and shared in the field of decision making. The goal is to build MIT’s capabilities to push computing and other areas deeper into the sector.

    These searches employed four interdisciplinary academics. They will join the MIT faculty next year in research and education that advances the physical understanding of low-carbon energy solutions, global climate modeling, biodiversity monitoring and conservation, and agricultural management through high-performance computing and transformative numerical methods. Engage , and machine learning techniques.

    “By coordinating our recruitment efforts with multiple departments and schools, we have been able to attract top academics in this field to MIT. Warren Ellis Professor Daniel Huttenlocher said: “They also help strengthen cross-departmental ties in computing in areas that are important and important to MIT and the world. .”

    “These strategic hires in the field of Computing for Climate and Environment are a great opportunity for the University to deepen its academic offerings and create new opportunities for collaboration across MIT. Professor Bush: “This university plays a pivotal role in MIT’s overarching efforts to employ climate-focused faculty to address the health of our planet through innovative research and curricula.” It introduces the important role of computing in

    The four new faculty members are:

    Sara Beery will join MIT in September 2023 as an Assistant Professor in the Artificial Intelligence and Decision Making Department at EECS. Beery completed her PhD in Computing and Mathematical Sciences at her Caltech in 2022, advised by Pietro Perona. Her research addresses real-world challenges such as strong spatio-temporal correlations, imperfect data quality, fine-grained categories, and long-tail distributions, enabling global environmental and biodiversity monitoring across data modalities. Focuses on building a computer vision technique for her. She partners with non-governmental and governmental organizations to extend her methods globally and to increase the diversity and accessibility of academic research in artificial intelligence through interdisciplinary development and education.

    Priya Dhonti will join MIT as an Assistant Professor in the Electrical Engineering and Artificial Intelligence and Decision Making Department of the EECS in the 2023-24 academic year. Donti recently completed her PhD in Computer Science and Engineering and Public Policy at Carnegie Mellon University, co-advised by Zico Kolter and Inês Azevedo. Her work focuses on machine learning for prediction, optimization and control in highly renewable power grids. Specifically, her research explores ways to incorporate the physics and tight constraints associated with power systems into Deep Learning her models. Donti is also co-founder and chairman of Climate Change AI. Climate Change AI is a non-profit initiative that catalyzes impactful work at the intersection of climate change and machine learning, currently running through the Cornell Tech Runway Startup Postdoc Program.

    Ericmoore Jossou joins in July 2023 as an Assistant Professor at MIT in a joint position in the Nuclear Science and Engineering Department and the Electrical Engineering Department of the EECS. He is currently an assistant professor at the Brookhaven National Laboratory of the US Department of Energy, which conducts research in nuclear and high energy physics, energy science and technology, environmental and biological sciences, nanoscience, and national security-related labs. His research at MIT focuses on understanding the processing structure-property relationships of materials for nuclear energy applications through advanced experiments, multi-scale simulations, and data science. Jossou received his PhD in Mechanical Engineering from the University of Saskatchewan in 2019.

    Sherrie Wang will join MIT in the 2023-24 academic year as an Assistant Professor in a joint position between the Department of Mechanical Engineering and the Institute for Data, Systems, and Society. Wang is currently her Ciriacy-Wantrup postdoctoral fellow at the University of California, Berkeley, hosted by Solomon Hsiang and the Global Policy Lab. She develops machine learning for earth observation data. Her main areas of application are improving agricultural management and predicting climate phenomena. She will complete her PhD in Computational and Mathematical Engineering at Stanford University in 2021, advised by David Lobell.



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