"That's My Kind of Data": The Love Data Week Keynote
"That's My Kind of Data": The Love Data Week Keynote
Overview
Join us for the Love Data Week keynote event! The keynote will feature a panel of data experts—Allison Jauré (University of Sydney), Jessa Lingel (University of Pennsylvania), and Raesetje Sefala (Distributed AI Research Institute)—who will discuss their affinity for and experience with various data types, including geospatial and qualitative data. In addition to talking about the rewards and challenges of working with data, the panelists will share advice for those interested in similar work.
This panel will be moderated by Kayla Shipp, Program Manager at the Yale Digital Humanities Lab, and Kaitlin Throgmorton, Data Librarian for the Health Sciences at Yale’s Cushing/Whitney Medical Library.
About the Panelists
Allison Jauré (née Tong) is a Principal Research Fellow at the Sydney School of Public Health, The University of Sydney. She holds an Australian National Health and Medical Research Council (NHMRC) Investigator Award and a Robinson Fellowship, and has experience in patient-centered outcomes research in chronic disease, particularly chronic kidney disease. Allison is interested in patient involvement in research, including in the context of research priority setting, the development of core outcomes for research, and in the co-production of clinical trials.
Jessa Lingel is an associate professor at the Annenberg School for Communication and core faculty in the Gender, Sexuality and Women’s Studies Program at the University of Pennsylvania. She received her PhD in communication and information from Rutgers University, an MLIS from the Pratt Institute, and an MA in gender studies from New York University. Her research interests include digital inequalities and technological distributions of power.
Raesetje Sefala is an AI Research Fellow at the Distributed AI Research (DAIR) Institute. Her research focuses on creating ground truth datasets and using machine learning and other computational social science techniques to study the effects of spatial apartheid in South Africa, post-Apartheid. She is also a PhD student at McGill investigating ways to evaluate datasets that are created for machine learning use. Her previous work involved partnering with various stakeholders and using machine learning techniques to study poverty and traffic safety in the urban parts of Nigeria and Jakarta, respectively.
Event Details
Date and Time:
Thursday, February 15, 2024
4-5 p.m. EST
Location:
Online
Registration
This event is free and open to all; please note that registration is required. To sign up, visit the Eventbrite page for the keynote.
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