BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Stanford - Department of Biomedical Data Science - ECPv6.17.3.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Stanford - Department of Biomedical Data Science
X-ORIGINAL-URL:https://dbds.stanford.edu
X-WR-CALDESC:Events for Stanford - Department of Biomedical Data Science
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20240310T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20241103T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20250309T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20251102T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20260308T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20261101T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20250402T160000
DTEND;TZID=America/Los_Angeles:20250402T170000
DTSTAMP:20250326T193614Z
CREATED:20250326T193614Z
LAST-MODIFIED:20250326T193614Z
UID:12785-1743609600-1743613200@dbds.stanford.edu
SUMMARY:Jure Leskovec: From Data to Discovery: How Foundation Models Transform Biology 4/2
DESCRIPTION:Wednesday\, April 2\, 2025 4:00pm – 5:30pm PDT \nSimonyi Conference Center\, CoDa\, 389 Jane Stanford Way\, Stanford\, CA 94305 \nAbstract: Foundation models are revolutionizing biology by learning the underlying structure of complex biological data and transforming how we analyze\, interpret\, and generate scientific knowledge. In this talk\, we explore how these models accelerate discovery by integrating vast datasets\, uncovering biological organization\, and guiding hypothesis-driven research. We begin with models that learn universal representations of cells across tissues and species. Without explicit supervision\, these models capture fundamental biological organization\, allowing researchers to analyze\, compare\, and annotate cells with unprecedented precision. This ability to model biological diversity naturally leads to the next challenge: how to generate and test new biological hypotheses. Large language models\, trained on vast scientific literature\, can play a crucial role in this process. \nFor more information: https://datascience.stanford.edu/events/scientific-discovery-age-data-ai/jure-leskovec-stanford
URL:https://dbds.stanford.edu/event/jure-leskovec-from-data-to-discovery-how-foundation-models-transform-biology-4-2/
LOCATION:CA
ATTACH;FMTTYPE=image/jpeg:https://dbds.stanford.edu/wp-content/uploads/2025/03/57a37b0d-d638-ddd8-f80f-d42d220d77af.jpeg
END:VEVENT
END:VCALENDAR