Slides from the UIUC Information Session on February 15
Second Call for Proposals on Digital Transformation and AI for Energy and Climate Security announced
The energy industry is being digitally transformed by investment at all levels of production, generation, transmission, and distribution: sensors, data analytics, new privacy-aware markets, and usage of smart meters in homes are all part of this transformation. However, the transformation of energy to be resilient to large environmental changes, faults (including maintenance errors), and cyber-attacks is still a work in progress. The early lead of energy operators in embracing digital transformation has enabled those systems to use digital transformation not only to enhance energy efficiency but also to lead the way to a lower-carbon, higher-efficiency economy that will enhance both energy and climate security.
This C3DTI Second Call for Proposals addresses the challenges for AI and Digital Transformation for Energy and Climate Security.
Areas of interest include but are not restricted to:
All proposals should be submitted online via EasyChair at:
https://easychair.org/conferences/?conf=c3dticfp2
Proposals must be submitted to EasyChair before 11:59 pm PDT March 29, 2021.
Awards will be announced in late May 2021, with start dates of June 1, 2021.
C3DTI will host a series of online information sessions and to provide an overview of the call for proposals and discuss the computing resources available to Research Award recipients as well as office hours with technical staff. Below are the dates and times for each information session and details about office hours.
General Information Sessions (Online)
Computing Resources Information Sessions (Online)
Weekly Office Hours (Online)
Additionally, the C3DTI Development Operations and C3 AI technical support teams will be available every Tuesday from 2 – 3 pm PT / 5 – 6 pm ET between March 2 and March 23.
Zoom Meeting: https://illinois.zoom.com.cn/j/87825348092?pwd=c1k1VWkxRXRQQTRuWllxUnN0Q256Zz09
Questions about general eligibility, proposal preparation, or research awards should be directed to the C3DTI by e-mail at proposals@c3dti.ai.
Colloquium on Digital Transformation Science
March 11, 3 pm CT Using Data Science to Understand the Heterogeneity of SARS-COV-2 Transmission & COVID-19 Clinical Presentation in MexicoStefano Bertozzi, MD, Professor, School of Public Health, University of California, Berkeley Juan Pablo Gutierrez, Professor at the Center for Policy, Population & Health Research, National Autonomous University of Mexico In 2020, Mexico confirmed 1.5M cases of COVID-19, with 128,000 deaths — an 8.8 percent fatality rate that is among the highest worldwide. The positivity rate for those tested is 42 percent (WHO target = 5 percent). The pandemic is likely to become the main cause of death in 2020, and in 2021— even with the vaccine —mortality is expected to rise. Almost half of the Mexican population receives its medical care from the Mexican Social Security Institute (IMSS). Our team from UCB, IMSS, and UNAM aims to harness the massive patient-level clinical and socio-demographic data from the IMSS to better predict susceptibility to infection and serious complications among those who are infected. The advantages of working with the IMSS are clear – the disadvantage is that it has taken many months to get approval from the relevant human subjects and research committees. The IMSS comprises many poorly integrated data systems, so there is significant work involved in relating the disparate databases to each other. We now have 2.5 years of utilization data (outpatient visits [>300M], hospitalizations, prescriptions [almost 500M], and COVID tests). We will study variability by employer, by state and neighborhood, by household structure, by clinic, by provider (and provider behavior), by current and prior health conditions, by degree of control of chronic health conditions, by any drugs that they have been prescribed, as well as by the usual demographic and socioeconomic characteristics. The priority will be to identify modifiable factors that the IMSS can use to reduce population risk. Stefano M. Bertozzi is Dean Emeritus and Professor of Health Policy and Management at the University of California, Berkeley School of Public Health, and Interim Director of University of California systemwide programs with Mexico (UC-MEXUS, the UC-Mexico Initiative, and Casa de California). Previously, he worked at the Bill and Melinda Gates Foundation, Mexican National Institute of Public Health, World Health Organization, UNAIDS, World Bank, and the Government of the Democratic Republic of the Congo. He recently co-edited the Disease Control Priorities (DCP3) volume on HIV/AIDS, Malaria & Tuberculosis, has served on governance and advisory boards for the East Bay Community Foundation, HopeLab, UNICEF, WHO, UNAIDS, Global Fund, PEPFAR, NIH, Duke University, University of Washington, and the AMA, has advised NGOs and ministries of health and social welfare in Asia, Africa, and Latin America, and is a member of the National Academy of Medicine. Juan Pablo Gutierrez is Professor at the Center for Policy, Population & Health Research, National Autonomous University of Mexico (UNAM), Chair of the Technical Committee of the Morelos’ Commission on Evaluation of Social Development, and Member of GAVI Evaluation Advisory Committee. His research focuses on comprehensive evaluation of social programs and policies, universal health coverage and effective access, and social inequalities in health. He has been responsible for the evaluation of social and health programs in Mexico, Ecuador, Guatemala, Dominican Republic, Honduras, and India, as well as several population-based health surveys both in households and facilities. He is a member of the National Observatory on Health Inequalities in Mexico and has authored or co-authored more than 60 papers in peer-reviewed journals. |
Information on Call for Proposals
C3.ai DTI Training Materials Overview (password protected)
C3 Administration (password protected)
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