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We face many overwhelming challenges in America today: systemic racism, data privacy, and political misinformation. Scholars and industry experts often disagree on how to find solutions. So, how can we find the right way to move forward? We let the data speak for itself.

Join hosts Liberty Vittert and Munther Dahleh on Data Nation, a production of MIT's Institute for Data, Systems, and Society.  Available on on Apple, Spotify, or other podcast platforms.

Data Science in Domains: Interaction of Physical, Social, and Institutional Systems
As we contemplate the preparation of the future data science learner, I want to highlight a core principle of IDSS and how it affected our decision to set up two of our flagship graduate education programs.

Building a resilient, carbon-neutral electric grid requires energy 'superhighways'
Today’s electric grid infrastructure is just not ready for the scale and speed of energy portfolio transformation being envisioned.

Making Data- Informed Covid-19 Testing Plans
Implementing testing within an organization raises a number of questions. Who should be tested? How often? How do other mitigation efforts impact testing need? How much will it all cost?

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Excess Fatal Overdoses in the United States During the COVID-19 Pandemic by Geography and Substance Type: March 2020–August 2021
Jay Chandra , Marie-Laure Charpignon , Anushka Bhaskar, Andrew Therriault, Yea-Hung Chen, Alyssa Mooney ,Munther A. Dahleh , Mathew V. Kiang , and Francesca Dominici
American Journal of Public Health, June 2024.

Data-driven control of COVID-19 in buildings: a reinforcement-learning approach
Ashkan Haji Hosseinloo, Saleh Nabi, Anette Hosoi, and Munther A. Dahleh
IEEE Transactions on Automation Science and Engineering, 2023.

Selling Information in Competitive Environments
Alessandro Bonatti, Munther Dahleh, Thibaut Horel, Amir Nouripour
To appear in the Journal of Economic Theory.

Causal Matrix Completion
A. Agarwal, M.A. Dahleh,  D. Shah, and D. Shen
COLT 2023

Incentive Compatibility in Two-Stage Repeated Stochastic Games
Bharadwaj Satchidanandan, Munther A. Dahleh
IEEE Transactions on Control of Network Systems, 2023.

Learning Good State and Action Representations for Markov Decision Process via Tensor Decomposition
C. Ni, Y. Duan, M. A. Dahleh, M. Wang, A. R. Zhang
Published in the Journal of Machine Learning Research, February 2023

Coordination via Selling Information
A. Bonatti, M. A. Dahleh, T. Horel, A. Nouripour
February 2023

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The Munther Dahleh Research Group works in the general area of “Decisions Under Uncertainty”.

The group addresses foundational issues in terms of fundamental limits and capabilities of real-time decision-making under uncertainty, societal challenges in specific domains such as finance, transportation, power grid and digital platforms, and translation challenges by working directly with stakeholders.

Meet the GroupSee Our Research Interests