Spring 2020 Data Science Showcase
Date: Tuesday, May 5, 2020
Time: 2:00 - 3:30 PM Pacific
Virtual Presentation: Watch the event live via this Zoom link.
The Division of Computing, Data Science, and Society's Spring Data Science Showcase features students' work in helping to design courses, explore the human and social contexts and ethics of data, and advance data science research.
- 2:00 - 2:15 PM -- Welcome and Keynote Address by Jennifer Tour Chayes, Associate Provost, Division of Computing, Data Science, and Society, and Dean, School of Information
- 2:15 - 2:30 PM -- Human Contexts and Ethics -- Find out how to use the Human Contexts and Ethics (HCE) toolkit to explore what’s at stake for society and ethics in every step of the data science life cycle.
- 2:30 - 2:50 PM -- Modules -- Get the latest on Modules, an innovative approach to integrating data science in research and teaching across campus, from neurobiology to linguistics to macroeconomics.
- 2:50 - 3:10 PM -- Discovery -- Learn about some of the 30+ hands-on student Discovery research projects leveraging data science for everything from making cyberspace inclusive to promoting environmental justice.
Featured Discovery Projects
- Environmental Justice Mapping Project: The team is creating a hub for environmental justice data across the country. With guidance from environmental justice organizations, they're aggregating this data into a single indicator of vulnerability for every state, similar to CalEnviroScreen(link is external) and the Washington Environmental Health Disparities Map(link is external) This will fill an existing gap in data accessibility and provide a valuable tool for advocates and policymakers. The final product will be an online map and datasets combining census, environmental pollutants, and health data for every state. Student Team: Neha Hudait, Siddharth Gangrade, Tiffany Huynh, Zain Khan, Chandana Bhimarao.
- Understanding Flight Performance Data (NASA Ames): The team is investigating the flight behavior of airline pilots and the factors affecting that behavior in a series of challenging simulated flights. Working with a large, heterogeneous data set including a variety of types of written records, a large corpus of simulator log files, and associated eye-tracking data, the team is comparing pilot activity on different flights, on a variety of measures, such as the time between two events (e.g. an initiating challenge and following response) and the frequency of particular patterns of behavior. Student Team: Abhishek Kumar, Danyal Shahroz, Mengzhu Sun, Saad Jamal, Sajal Sharma.
- Making Cyberspace Inclusive: Many studies have focused on building a detection algorithm for hate speech, but no one has developed a similar algorithm for inclusion and belonging. The gap matters because inclusive cyberspace is not equal to the absence of online hate speech. It means people exchange ideas online in an inclusive manner. This project aims to fill this gap by developing a replicable and scalable research methodology that helps identify and examine incidents of inclusive online speech. Student Team: Carlos Ortiz, Sarah Nam, Sarah Santiago, Vivek Datta.