BIES: James Zou, Stanford University

BIES: James Zou, Stanford University

By Harvard Office of Technology Development and the HMS Dept. of Biomedical Informatics

A monthly conversation about medicine, biology, computers, and entrepreneurship.

Date and time

Location

Online

Good to know

Highlights

  • 1 hour 30 minutes
  • Online

About this event

Science & Tech • Biotech

Hosted by Harvard Office of Technology Development and the HMS Dept. of Biomedical Informatics.

In person at Harvard Medical School, Countway Library, Room 506, The Minot Room for Harvard ID holders or online via Zoom for all.


New Location:

Countway Library, Room 506, Minot Room

695 Huntington Ave., Boston, MA 02115

In person attendance is limited to Harvard ID holders only. For those withoout Harvard ID, please join us via Zoom

In-person networking with lunch for Harvard ID holders from 11:30–12:00pm, followed by a live virtual presentation at 12:00pm. Both Dr. Kohane and the speaker will participate remotely via Zoom, with their discussion streamed in the Minot room (Harvard ID required for access) or online for all.


Featured Speaker:

James Zou, PhD, Associate Professor of Biomedical Data Science at Stanford University

This Entrepreneurs Salon will be hosted by Isaac Kohane, Chair, Department of Biomedical Informatics, Harvard Medical School.


Location:

We are pleased to return for another hybrid Salon event. Harvard ID holders are welcome to join us at Countway Library, Room 506, Minot Room, at Harvard Medical School in Boston. For those unable to attend in person, we welcome you to join us on Zoom (access the Zoom registration link via Eventbrite's "Online Event Page" after registering with Eventbrite). Please register here so we can plan accordingly for food for in-person registrants (Harvard ID Only) and provide the Zoom link for virtual registrants.

Dr. James Zou is an Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science and Electrical Engineering at Stanford University. He works on making machine learning more reliable, human-compatible and statistically rigorous, and is especially interested in applications in human disease and health. Several of his algorithms are widely used in tech and biotech industries. He received a Ph.D from Harvard in 2014, and was a member of Microsoft Research, a Gates Scholar at Cambridge and a Simons fellow at UC Berkeley. He joined Stanford in 2016 and is a two-time Chan-Zuckerberg Investigator and the faculty director of the university-wide Stanford Data4Health hub. He is also a member of the Stanford AI Lab. His research is supported by the Sloan Fellowship, the NSF CAREER Award, and Google, Amazon and Adobe AI awards.


FUTURE COMMUNICATIONS:

Please note: By registering, you agree to receive emails about this event and future communications from Harvard OTD.

Free
Nov 4 · 8:30 AM PST