Four Recipients Announced for new Transformative Research Funds
The inaugural recipients of the Transformative Research Fund include: the team of Tess Smidt and Abigail Bodner (top row, left to right); Mina Konaković Luković (bottom left); Stefanie Mueller (bottom center); and Laura Lewis (bottom right). Photos courtesy of their subjects. The Department of EECS is pleased to announce the four inaugural recipients of the Transformative Research Fund, an exciting new funding opportunity designed to facilitate bold and pivotal research, especially that which applies recent breakthrough technologies (such as generative AI) to important problems with broad societal impact. The Transformative Research Funds, which were made possible through the generous support of The SPC Foundation and Dick Thornton, exist to “place necessary bets on novel ideas and explore exciting, untested directions”–a priority which became particularly pressing with the breakneck-paced advances in AI and digital technologies. These new technologies have the potential for transformative change in fields ranging from healthcare to communications, commerce, the arts, sciences, and education.
As Department Head Asu Ozdaglar explains, “We need a roadmap for the future that combines frontier knowledge in AI and computing technologies with domain knowledge in several fields, including engineering, sciences, social sciences, and humanities. Transformative Research Funds will support groundbreaking projects that will apply the highest level of expertise in computer science, AI, and electrical engineering to some of humanity’s greatest problems.”
The initial call for proposals this year yielded a dozen responses; the following four proposals were selected to receive up to $200K in funding through the initiative, which will reopen for a new round of proposals next year.
Laura Lewis, the Athinoula A. Martinos Associate Professor, proposes “Technology for measuring brain fluid clearance in the home sleep environment”, a study relating to Alzheimer’s Disease in which machine learning strategies will be used to help analyze biometric data collected by EEG.
Mina Konaković Luković, Assistant Professor, proposes “Vision-Activated Directed Evolution”, in which researchers will combine robotics and a vision-based AI system to meet multidimensional objectives and solve complex problems in directed evolution.
Stefanie Mueller, TIBCO Career Development Associate Professor, proposes “Real-time Radiation Feedback for Breast Cancer Treatment via AI-enabled Electrochemical Impedance Sensing” in collaboration with Dana-Farber Cancer Institute of Brigham and Women’s Hospital. The project is aimed at giving medical technicians real-time feedback on the effects of radiation on their patients’ tissue, allowing them to adjust radiation locations and dosages for greater cancer treatment efficacy.
Abigail Bodner (EECS+EAPS) and Tess Smidt have teamed to present their proposal,
“Multi-Scale Climate Turbulence with Euclidean Neural Networks”, which aims to apply formal Euclidean symmetry-equivariant neural networks (ENNs) to the challenge of learning and representing mappings between 2D and 3D ocean turbulence, a representation problem within climate change modeling.
Media Inquiries
Journalists seeking information about EECS, or interviews with EECS faculty members, should email eecs-communications@mit.edu.
Please note: The EECS Communications Office only handles media inquiries related to MIT’s Department of Electrical Engineering & Computer Science. Please visit other school, department, laboratory, or center websites to locate their dedicated media-relations teams.