We are a systems science group developing the methodology to advance modeling, observation and inference for prediction and discovery in Earth, Planets, Climate, and Life applications. Our approach emphasizes closed-loop Dynamic Data-Driven Systems Optimization to informatively combine theory, data, experts, and analogs for a variety of stochastic systems problems in nonlinear high-dimensional settings. Our advances coupling theory- and data-driven systems science has led to new approaches for estimation, control, learning, model reduction, uncertainty quantification, adaptive observation, detection, and decision making. ESSG is strongly interdisciplinary and comfortable developing both methodology and application. You can find us tinkering with "what works in the field" while stretching the contours of systems science. At our heart, we are motivated to bring systems science to investigations of the earth and environment.
Participants come from many pedagogical areas including EAPS, EECS, Mathematics, and Mechanical and Aerospace Engineering. For example, here are a few who attended Z. Li's talk on his project work--
Left to Right: Margaret Trautner (18, Learning-Dynamics), Jacob Edison (16, Dynamics-UAS), Goran Zivanovic (6, Learning-Exoplanets), Aarti Dwivedi (12, Learning-Geophysics), Michael Barbehenn (visiting scientist, Ecology), Sai Ravela (EAPS), Ziwei Li (12, Learning-Atmosphere), Zhchang Zhan (12, Learning-Exoplanets) are present with our test aircraft. Photo by L. Hinkel.
ESSG is funded in part by the Massachusetts Institute of Technology's Climate Grand Challenges program, Liberty Mutual, Office of Naval Research (ONR), the AFOSR Data-Driven Dynamic Application Systems (DDDAS) Program, the National Science Foundation (NSF), Lincoln Laboratory, Naval Undersea Warfare Center Division (NUWC), the Seaver Intitute, MIT's MISTI and ESI programs.
Here you will find the people, projects, and publications associated with our group. Enjoy!