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
Colloquium on Digital Transformation Science
May 20, 3 pm CT
Feedback Control Perspectives on Learning
Jeff Shamma, Professor, Department of Industrial and Enterprise Systems Engineering, University of Illinois at Urbana-Champaign
The impact of feedback control is extensive. It is deployed in a wide array of engineering domains, including aerospace, robotics, automotive, communications, manufacturing, and energy applications, with super-human performance having been achieved for decades. Many settings in learning involve feedback interconnections, e.g., reinforcement learning has an agent in feedback with its environment, and multi-agent learning has agents in feedback with each other. By explicitly recognizing the presence of a feedback interconnection, one can exploit feedback control perspectives for the analysis and synthesis of such systems, as well as investigate trade-offs in fundamental limitations of achievable performance inherent in all feedback control systems. This talk highlights selected feedback control concepts — in particular, robustness, passivity, tracking, and stabilization — as they relate to specific questions in evolutionary game theory, no-regret learning, and multi-agent learning.
Jeff S. Shamma is the Department Head of Industrial and Enterprise Systems Engineering (ISE) and Jerry S. Dobrovolny Chair in ISE at the University of Illinois at Urbana-Champaign. Prior academic appointments include faculty positions at King Abdullah University of Science and Technology (KAUST), as Adjunct Professor of Electrical and Computer Engineering, and Georgia Institute of Technology, where he was the Julian T. Hightower Chair in Systems and Controls. Shamma received a PhD in Systems Science and Engineering from MIT in 1988. He is a Fellow of IEEE and IFAC; recipient of IFAC High Impact Paper Award, AACC Donald P. Eckman Award, and NSF Young Investigator Award; and a past Distinguished Lecturer of the IEEE Control Systems Society. Shamma is currently serving as Editor-in-Chief for IEEE Transactions on Control of Network Systems.Quick Links:
Information on Call for Proposals
C3.ai DTI Training Materials Overview (password protected)
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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