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?

Understanding how people make sense of information in the information age 
Graduate student Manon Revel uses quantitative methodologies to investigate how advertising in online publications affects trust in journalism.

IDSS COVID- 19 Collaboration 
IDSS COVID-19 Collaboration (Isolat) is an initiative organized by IDSS that takes a data-driven approach to addressing the COVID-19 pandemic.

Why the Data Marketplaces of the Future Will Sell Insights, Not Data
MIT Sloan Management Review spoke with M. Dahleh about why current data marketplaces fall short, how a more efficient one would work.

An Efficient and Incentive-Compatible Mechanism for Energy Storage Markets
Satchidanandan B., Dahleh M.A; Submitted to IEEE Transactions on Smart Grid, 2020. 

A Cross-Domain Approach to Analyzing the Short-Run Impact of COVID-19 on the US Electricity Sector
Guangchun Ruan, Dongqi Wu,Xiangtian Zheng, Haiwang Zhong, Chongqing Kang, Munther A. Dahleh, S. Sivaranjani, Le Xie; Appeared in the Joule Journal | ScienceDirect.com, Sept. 2020.

Data-driven control of micro-climate in buildings: an event-triggered reinforcement learning approach
Hosseinloo A.H., Ryzhov A., Bischi A., Ouerdane H., Turitsyn K., Dahleh M.A; Appeared in the Journal of Applied Energy, Vol 277, 2020.

Towards Data Auctions with Externalities
Agarwal A., Dahleh M.A., Horel T., Rui M.; Submitted for Publication, March 2020.