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The Development and Evolution of Data Science: Potential and Leadership (with Philip E. Bourne, Ph.D., Founding Stephenson Dean, School of Data Science and Professor of Biomedical Engineering, University of Virginia)

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Manage episode 352746806 series 1526434
Content provided by Harris Search Associates. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Harris Search Associates or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Dr. Philip Bourne, founding Stephenson Dean of the School of Data Science at the University of Virginia, established in 2019 with a gift of $120 million. Dr. Bourne’s career encompasses work at Columbia University, the University of California at San Diego, and the National Institutes of Health and includes motorcycle jaunts throughout western Virginia and beyond. We spoke with him at his office in Charlottesville about the following (abridged version of) questions: 1. Why a separate school of data science? 2. What gives data science its coherence as a professional field and an academic discipline? Does that include tackling a set of “grand challenges” such as we see in, for example, engineering? 3. Your school is described as one “without walls,” suggesting perhaps a virtual format for learning. How will students, including working professionals you identify as persons you seek to serve, learn in the school? 4. Is there any reason to expect student enrollment and degree completion in data science to be any different in terms of representation of persons of color? Will students be taught by a diverse data science faculty? If so, why? 5. What do you see as the other key attributes, experiences, and expertise of someone who can lead successfully an academic leadership position in data science? INNOVATORS is a podcast production of Harris Search Associates. *The views and opinions shared by the guests on INNOVATORS do not necessarily reflect the views of the interviewee's institution or organization.*
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72 episodes

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Manage episode 352746806 series 1526434
Content provided by Harris Search Associates. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Harris Search Associates or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
Dr. Philip Bourne, founding Stephenson Dean of the School of Data Science at the University of Virginia, established in 2019 with a gift of $120 million. Dr. Bourne’s career encompasses work at Columbia University, the University of California at San Diego, and the National Institutes of Health and includes motorcycle jaunts throughout western Virginia and beyond. We spoke with him at his office in Charlottesville about the following (abridged version of) questions: 1. Why a separate school of data science? 2. What gives data science its coherence as a professional field and an academic discipline? Does that include tackling a set of “grand challenges” such as we see in, for example, engineering? 3. Your school is described as one “without walls,” suggesting perhaps a virtual format for learning. How will students, including working professionals you identify as persons you seek to serve, learn in the school? 4. Is there any reason to expect student enrollment and degree completion in data science to be any different in terms of representation of persons of color? Will students be taught by a diverse data science faculty? If so, why? 5. What do you see as the other key attributes, experiences, and expertise of someone who can lead successfully an academic leadership position in data science? INNOVATORS is a podcast production of Harris Search Associates. *The views and opinions shared by the guests on INNOVATORS do not necessarily reflect the views of the interviewee's institution or organization.*
  continue reading

72 episodes

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