Quick Links:
Information on Call for Proposals
Proposal Matchmaking (Archive from 2020 CFP)
C3 Administration (password protected)
Have Questions? Please contact one of us:
- Jay Roloff, jayr@illinois.edu (Executive Director, c3.ai.DTI)
- R. Srikant, rsrikant@illinois.edu (Co-Director, c3.ai.DTI)
- Tandy Warnow, warnow@illinois.edu (Co-chief Scientist, c3.ai.DTI)
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Announcing our Third Call for Proposals:
AI to Transform Cybersecurity and Secure Critical Infrastructure
It is anticipated that up to USD $10 million in Research Awards will be awarded from this Call for Proposals. Proposals can request funding of USD $100,000 to $1,000,000 for an initial period of one (1) year.
C3DTI will also make available up to USD $2 million in Azure Cloud computing resources, supercomputing resources at UIUC’s NCSA and LBNL’s NERSC, and free, unlimited access to the C3 AI Suite hosted on the Microsoft Azure Cloud.
**** We will be offering a virtual session with information on the CFP including an opportunity to ask questions early in January. Please keep an eye out on you email and this wiki page for more information. ****
Proposals are Due February 7, 2022
Awards will be made in March 2022 with start dates of around June 1, 2022
Announcements
August 6, 3 pm CT
Optimal Targeted Lockdowns in a Multi-Group SIR Model
Daron Acemoglu, Institute Professor, Department of Economics, MIT
This colloquium will investigate targeted lockdowns using a multi-group SIR model, in which infection, hospitalization, and fatality rates vary among groups—in particular among young, middle-aged, and old patients. The model—developed by PI Daron Acemoglu with MIT Economics Professors Victor Chernozhukov, Iván Werning, and Michael Whinston—enables a tractable quantitative analysis of optimal policy. For baseline parameter values for the COVID-19 pandemic as applied to the United States, Daron Acemoglu and his colleagues find that optimal policies differentially targeting risk/age groups significantly outperform optimal uniform policies and most of the gains can be realized by having stricter lockdown policies on the oldest group. Intuitively, a strict and long lockdown for the most vulnerable group both reduces infections and enables less strict lockdowns for the lower risk groups. The colloquium also will investigate: the impacts of group distancing, testing, and contract tracing; the matching technology; and the expected arrival time of a vaccine for optimal policies. Overall, Acemoglu’s model indicates targeted policies combined with measures that reduce interactions among groups and increase testing and isolation of the infected can minimize both economic losses and deaths.Quick Links:
Information on Call for Proposals
Proposal Matchmaking Matchmaking
C3 Administration (password protected)
Have Questions? Please contact one of us:
- Jay Roloff, jayr@illinois.edu (Executive Director, c3.ai.DTI)
- R. Srikant, rsrikant@illinois.edu (Co-Director, c3.ai.DTI)
- Tandy Warnow, warnow@illinois.edu (Co-chief Scientist, c3.ai.DTI)
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