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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

Information Session Slide Deck


Quick Links:

C3.ai DTI Webpage

Events

Information on Call for Proposals

Proposal Matchmaking (Archive from 2020 CFP)

C3.ai DTI Training Materials

C3 Administration (password protected)


Have Questions? Please contact one of us:



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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

Colloquium on Digital Transformation Science

September 16, 3 pm CT

Causal Tensor Estimation

Devavrat Shah, Professor of Electrical Engineering and Computer Science, Massachusetts Institute of Technology

REGISTER FOR ZOOM WEBINAR

In this talk, we present a framework for causal inference for the “panel” or “longitudinal” setting from the lens of tensor estimation. Traditionally, such panel or longitudinal settings are considered in econometrics literature for program or policy evaluation. Tensor estimation has been considered in machine learning, where tantalizing statistical and computational tradeoffs have emerged for random observation models. We introduce a causal variant of tensor estimation that provides a unified view for prior works in econometrics and provides newer avenues to explore. We discuss a method for estimating such a causal variant of the tensor and various exciting directions for future research, including offline reinforcement learning. This is based on joint work with Alberto Abadie (MIT), Anish Agarwal (MIT), and Dennis Shen (MIT/UC Berkeley).

Devavrat Shah is a professor in the Department of Electrical Engineering and Computer Science at MIT. His current research interests are at the interface of statistical inference and social data processing. His work has been recognized through prize paper awards in machine learning, operations research, and computer science, as well as career prizes including the 2010 Erlang prize from the INFORMS Applied Probability Society and the 2008 ACM Sigmetrics Rising Star Award. He is a distinguished alumnus of his alma mater IIT Bombay. He co-founded Celect, Inc. (now part of Nike) in 2013 to help retailers decide what to put where by accurately predicting demand using omni-channel data.


Quick Links:

C3.ai DTI Webpage

Events

Information on Call for Proposals

Proposal Matchmaking

C3.ai DTI Training Materials (password protected)

C3 Administration (password protected)


Have Questions? Please contact one of us:



Recent space activity

Recently Updated
typespage, comment, blogpost
max5
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themesocial

Space contributors

Contributors
modelist
scopedescendants
limit5
showLastTimetrue
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