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COVID + Data Science Virtual Seminars in Summer 2020

Please join us for an 8-week series on data science methods with direct applications to the COVID-19 pandemic. Learn from Duke experts about the state-of-the-art in these 1-hour virtual sessions.

Several sessions will be paired with ethics discussions, co-hosted with Duke Science & Society Coronavirus Conversations. These sessions will discuss the ethical and policy implications of the novel use of data science to address the pandemic.

Tuesday, June 30 from 4–5 PM
Matthew Hirschey, Key elements of the analytical toolbox for understanding COVID-related data
Register at https://training.oit.duke.edu/enroll/common/show/21/175077
(People without a Duke e-mail can register here)

Tuesday, July 7 from 4–5 PM
David Carlson, Natural Language Processing and understanding the evolving COVID literature
Register at https://training.oit.duke.edu/enroll/common/show/21/175082
(People without a Duke e-mail can register here)

Tuesday, July 14 from 4–5 PM
Ricardo Henao, Molecular methodology connected to COVID data
Register at https://training.oit.duke.edu/enroll/common/show/21/175076
(People without a Duke e-mail can register here)

Tuesday, July 21 from 4–5 PM
Larry Carin, Simple introduction to deep learning
Register at https://training.oit.duke.edu/enroll/common/show/21/175075
(People without a Duke e-mail can register here)

Wednesday, July 22 from 4–5 PM
Matthew Kenney, Introduction to PyTorch computational platform for deep learning
Register at https://training.oit.duke.edu/enroll/common/show/21/175078
(People without a Duke e-mail can register here)

Thursday, July 23 from 4–5 PM
Tim Dunn, PyTorch for image analysis with deep learning
Register at https://training.oit.duke.edu/enroll/common/show/21/175079
(People without a Duke e-mail can register here)

Tuesday, July 28 from 4–5 PM
Rachel Draelos, Analysis of chest CT imaging data and connection to COVID diagnosis
Register at https://training.oit.duke.edu/enroll/common/show/21/175080
(People without a Duke e-mail can register here)

Thursday, July 30 from 4–5 PM
Ethics of AI and image analysis, moderated by Nita Farahany, with panelists including Rachel Draelos, Tim Dunn, and Raymond Geis
A panel on the ethics of using AI and machine learning in diagnostic imaging for COVID-19, co-hosted by the Duke University Initiative for Science and Society.
Attending this event fulfills the RCR-200 (Responsible Conduct of Research) requirement for Duke faculty and staff.
Register at https://scienceandsociety.duke.edu/events/coronavirus-conversations-ethics-of-ai-and-image-analysis/

Tuesday, August 4 from 4–5 PM
Ben Goldstein, Using data science to optimize scheduling elective procedures in the time of COVID
Register at https://training.oit.duke.edu/enroll/common/show/21/175073
(People without a Duke e-mail can register here)

Tuesday, August 11 from 4–5 PM
Fan Li, Causal inference for quantifying the efficacy of potential COVID medications and vaccines
Register at https://training.oit.duke.edu/enroll/common/show/21/175081
(People without a Duke e-mail can register here)

Tuesday, August 18 from 4–5 PM
Jessilyn Dunn, The opportunity for wearables for early COVID detection
Register at https://training.oit.duke.edu/enroll/common/show/21/175074
(People without a Duke e-mail can register here)

Thursday, August 20 from 4–5 PM
Ethics of AI and wearables, moderated by Nita Farahany, with panelists including Jessilyn Dunn
A panel on the ethics of using wearable technologies for early detection and tracking of COVID, co-hosted by the Duke University Initiative for Science and Society and moderated by Nita Farahany.
Attending this event fulfills the RCR-200 (Responsible Conduct of Research) requirement for Duke faculty and staff.
Register at https://scienceandsociety.duke.edu/events/coronavirus-conversations-ethics-of-the-use-of-wearables-for-early-covid-detection/