COVID Research Lightning Talks May 19 + More Events & Opportunities

COVID Information Commons Newsletter | April 30, 2021

May 2021 COVID Information Commons Community Webinar: Lightning Talks and Q&A

Date: May 19, 2021, 4:00-5:00pm ET
REGISTER HERE

Meet the scientists seeking new insights on COVID-19. Every month, we bring together a group of researchers studying wide-ranging aspects of the current pandemic, to share their research and answer questions from our community. Learn more about their ongoing efforts in the fight against COVID-19, including opportunities for collaboration.

Featured Speakers:

Alka Sapat, Florida Atlantic University: RAPID: Health, Housing, and Hazards: COVID-19, Subjective Resilience, Vulnerabilities, and Policy Evolution in Hurricane Prone Counties. Funded by NSF Social, Behavioral and Economic Sciences / Division of Social and Economic Sciences.

Ruth Serra-Moreno, University of Rochester: Membrane remodeling dynamics by SARS-CoV-2. Funded by NSF Biological Sciences / Division of Molecular and Cellular Biosciences.

David Konisky, Indiana University: The Effects of COVID-19 on Household Energy Insecurity. Funded by NSF Social, Behavioral and Economic Sciences / Division of Social and Economic Sciences.

Austin Mast, Florida State University: Rapid Creation of a Data Product for the World’s Specimens of Horseshoe Bats and Relatives, a Known Reservoir for Coronaviruses. Funded by NSF Biological Sciences / Division of Biological Infrastructure.

Peter Pirolli, Florida Institute for Human and Machine Cognition, Inc.: Improving Computational Epidemiology with Higher Fidelity Models of Human Behavior. NSF Computer and Information Science and Engineering / Division of Information and Intelligent Systems.

Researchers Discuss New Insights in April CIC Community Webinar

Thank you to all of the participants and speakers who attended the April CIC Community webinar! The webinar included talks from seven NSF-funded researchers working to provide new insights around COVID-19: Brian Chang of Clark University, Lalitha Sankar of Arizona State University, Song Gao of University of Wisconsin-Madison, Dan O'Brien of Northeastern University, Kollbe Ahn of ACatechol, Inc., Jaideep Vaidya of Rutgers University-Newark, and Olga Wilhelmi of University Corporation For Atmospheric Research.

If you would like to present your NSF or NIH-funded COVID-related research at a future CIC community event, please contact the project team. We look forward to hearing from you!

Duke Machine Learning Virtual Summer School 2021

Dates: June 14-17, 2021

The Duke+Data Science program (+DS) is pleased to announce a virtual offering of the Duke Machine Learning School for summer 2021, which will be held June 14-17.

The 3.5 day curriculum in the Machine Learning Virtual Summer School (MLvSS) is targeted to individuals interested in learning about machine learning, with a focus on recent deep learning methodology. The MLvSS will introduce the mathematics and statistics at the foundation of modern machine learning, and provide context for the methods that have formed the foundations of rapid growth in artificial intelligence (AI). Additionally, the MLvSS will provide hands-on training in the latest machine learning software, using the widely used (and free) PyTorch framework.

Eight Duke Machine Learning Schools have been presented since 2017, reaching hundreds of participants from academia and industry and including international audiences at the SingHealth/Duke NUS Medical School and the Duke Kunshan University campus.

The 2021 MLvSS will be led by a trio of machine learning experts at Duke University: Professors Ricardo Henao, David Carlson, and Timothy Dunn. The event will also feature lectures by other Duke professors and the founding director of the Duke machine learning schools, Lawrence Carin. Hands-on software training will be provided by Duke graduate students who have extensive experience with these tools, and teaching assistants from the Duke AI Health Fellowship program will be available for assistance throughout the course.

Request for Information (RFI): Use of Common Data Elements (CDEs) in NIH-Funded Research

NIH is requesting public comment on the use of CDEs, particularly in the context of COVID-19 research, including opportunities for advancing research with CDEs, challenges to adopting CDEs, and guidance or tools that could facilitate use of CDEs. These comments will be used to inform NIH’s continuing development of guidance of CDE use for COVID-related research and assist in the planning for adequate funding of CDE efforts through research awards and contracts.

Learn more here.

Open Position at the Northeast Big Data Innovation Hub

Apply for the open position at the Northeast Big Data Innovation Hub: Northeast Big Data Innovation Hub operations and communications manager

Build Your PI Page!

As part of the new NSF COVID Awards and PI Database on the COVID Information Commons website, we've already added websites, research findings, and collaboration opportunities provided by over 250 NSF PIs. If you would like to help others further engage with your work by adding or updating any information on your PI page, please fill out this survey .

To learn more about the database, watch this overview from our November 2020 webinar.

The COVID Information Commons (CIC) serves as a resource for researchers, students and decision-makers from academia, government, nonprofit, and industry to identify collaboration opportunities, to leverage each other's research findings, and to accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic.

To suggest COVID research-related news, events, and opportunities for an upcoming newsletter, please email info@covidinfocommons.net.

Help build our community by forwarding CIC news widely, and encourage your colleagues to sign up for updates via this web form.

Thanks! —The CIC Project Team