awesome-MIT-AI-for-Climate-Change

Awesome-MIT-AI-for-Climate-Change is a curated list of professors and other faculty at Massachusetts Institute of Technology (MIT) who are tackling climate change with machine learning (CCML).

Finding people at the intersection of machine learning and climate change can be difficult, because they are spread across various departments and research a wide breadth of topics. Whether you're applying for graduate school, look for collaborators, or inspiring projects - this list is intended to get you started by finding the right people.

This is a safe, open, and inclusive community. The list is most surely incomplete, so please add your favorite researchers through commenting in an issue or creating a pull request.

MIT Campaign for a Better World logo from MIT Better World

Department

• Aeronautics and Astronautics
• Architecture
• Civil and Environmental Engineering (CEE)
• Computer Science and Artificial Intelligence Laboratory (CSAIL)
• Earth, Atmospheric, and Planetary sciences (EAPS)
• Electrical Engineering and Computer Science (EECS)
• Materials Sciences and Engineering
• Mechanical Engineering (MechE)
• MIT Media Lab
• MIT Sloan School of Management
• Woods Hole Oceanographic Institution (WHOI)

Aeronautics and Astronautics

• Dava Newman
  Fast climate models, physics-informed neural networks, climate visualizations, virtual reality. Associates in CCML include Björn Lütjens, Phillip Cherner.

• Daniel Varon
  Remote sensing, methane emissions, scientific computing. Links in CCML include 1.

• Youssef Marzouk
  Uncertainty quantification, Bayesian modeling and computation, data assimilation, machine learning in complex physical systems, environmental applications. Associates in CCML include Maximilian Ramgraber, Aimee Maurais.

Architecture

• John E. Fernandez
  Deforestation, environmental justice.

• Marcela Angel
  Technology development and data analysis for community-based planning, natural climate solutions, deforestation, ML-based aerial monitoring, environmental justice.

Computer Science and Artificial Intelligence Laboratory (CSAIL)

• Chris Rackauckas
  Scientific machine learning, physics-informed neural networks, climate modeling, differential equations.

• Daniela Rus
  Distributed or collaborative robotics, soft robotics, mobile computing, pruned neural networks, robustness, climate change.

• Sara Beery
  Computer Vision for Ecology, wildlife camera footage, forest detection, fine-grained visual classification.

Civil and Environmental Engineering (CEE)

• César Terrer
  Earth system science, forests, plant-soil interactions, field and satellite observations, remote sensing, land surface modeling.

• Michael Howland
  Wind farm modeling, fluid mechanics, weather and climate modeling, uncertainty quantification, optimization and control, physics-informed machine learning, renewable energies. Links in CCML include 1.

• Saurabh Amin
  Control of infrastructure systems, game theory, optimization in networks, sustainability, natural resource supply chains.

Earth, Atmospheric, and Planetary Sciences (EAPS)

• Andre Souza
  machine learning methods for discovering dynamics, optimal control, rare events in dynamical systems, Ocean modeling. Links in CCML include 1.

• Brent Minchew
  Cryosphere, glaciers, remote sensing, inSAR, mechanics of flowing ice. Link in CCML include 1.

• Chris Hill
  Ocean modeling, climate modeling, green high-performance computing, physics-informed neural networks, multi-scale modeling of fluids. Links include 1.

• Noelle Selin
  Air pollution, atmospheric chemistry, aerosols. Associates and links include Björn Lütjens, Paolo Giani, Chris Womack and 1.

• Paul O'Gorman
  Atmospheric dynamics, precipitation, physics-informed neural networks. Associates and links in CCML include Griffin Mooers, Janni Yuval, Ziwei Li, 3Q.

• Raffaele Ferrari
  Ocean modeling, Ocean dynamics, Atmospheric dynamics. Associates and links in CCML include Andre Souza, Björn Lütjens 1, 2.

• Sai Ravela
  Data-Driven Dynamics; Optimization and Learning; Natural Hazards and Climate Risk; Computational Sustainability; Autonomous Observing Systems. Students and associates in CCML include Anamitra Saha and Joaquin Salas; links include 1

• Stephanie Dutkiewicz
  Ocean sciences, marine ecosystems, phytoplankton, biogeochemistry, biogeography, unsupervised learning. Links in CCML include 1

• Taylor Perron
  Geomorphology, remote sensing, forests, influence of climate on landscapes, river networks.

Electrical Engineering and Computer Science (EECS)

• Priya Donti
  Forecasting, optimization, and control in high-renewable power grids, hard constraints in deep learning, co-founder of Climate Change AI.

Materials Sciences and Engineering

• Elsa Olivetti
  Environmental and economic sustainability of materials, recycled and renewable materials, recycling-friendly material design, intelligent waste disposition, dematerialization and waste mining. Links in CCML include 1.

• Jeffrey Grossman
  Nano materials, energy applications, applied machine learning. Strategic advisor to MIT Climate and Sustainability Consortium. Links in CCML include 1.

Mechanical Engineering (MechE)

• Anuradha Annaswamy
  Adaptive control, data-driven methods, federated learning for optimizing smart energy distribution grids. Links in CCML include 1.

• Pierre Lermusiaux
  Ocean modeling and data assimilation to quantify regional ocean dynamics on multiple scales. Multiscale modeling, uncertainty quantification, data assimilation.

• Sherrie Wang
  Remote sensing and machine learning for climate science and agriculture. Associates and links in CCML include 1.

• Themistoklis Sapsis
  Physics-informed machine learning, reduced order modeling for sampling of extreme climate events. Associates and links in CCML include Mengze Wang and 1.

MIT Media Lab

• Danielle Wood
  Environmental justice, ecosystem monitoring, space policy, remote sensing.

• Dava Newman
  See Aeronautics and Astronautics

• Fadel Adib
  Ocean internet of things, distributed sensors, reinforcement learning.

• Joseph A. Paradiso
  Sustainable and smart agriculture, internet of things, food systems, sensor networks. Associates in CCML include Caroline Jaffe and Neil Gaikwad.

MIT Sloan School of Management

• Christopher R. Knittel
  Energy and environmental policy, energy efficiency investments, environmental economics, machine learning. Links in CCML include 1.

• David Rand
  Cognitive science, behavioral economics, social psychology, climate misinformation. Associates in CCML include Zivvy Epstein.

• Jason Jay
  Leadership, strategy, sustainable business, combining social and business goals.

• John Sterman
  System dynamics, climate policy, systems analysis, simulating complex systems, only tangentially machine learning. Links in CCML include en-roads

Woods Hole Oceanographic Institution (WHOI)

• Yogesh Girdar
  Deep sea exploration, robots, communication-starved environments, unsupervised learning. Associates in CCML include Stewart Jamieson, Jess Todd.

Awesome-awesome

• MIT Climate Grand Challenge Finalists
  A list of professors interested in climate change.

Contributions

This list has only been possible to assemble through the extensive input by Zivvy Epstein, Helena Caswell, Salva Rühling, Will Atkinson, Sidhant Pai, Sai Ravela, Margaret Capetz, and more.