Name: Detecting adaptive and ghost introgression in human populations using machine learning approaches
Start: 2026-12-08T18:00:00.000Z
End: 2026-12-08T19:00:00.000Z
Location: San Francisco

# Detecting adaptive and ghost introgression in human populations using machine learning approaches

- **When:** Tue, Dec 8, 2026, 10:00 AM PST – 11:00 AM PST
- **Where:** Mission Hall, 550 16th St, San Francisco, CA 94158
- **Price:** Free
- **Organizer:** [School of Medicine](https://eventing.ing/organizers/orgz_1m4v60zhrfx8c0w7z86907)
- **Categories:** AI & ML
- **View on UCSF:** https://calendar.ucsf.edu/event/detecting-adaptive-and-ghost-introgression-in-human-populations-using-machine-learning-approaches

It is now widely recognized that introgression from archaic humans left a lasting impact on the modern human genome, yet many questions remain unanswered regarding how introgressed variants contributed to adaptation and whether additional, unsampled archaic hominins also contributed to the modern human gene pool. In this talk, I will present recent works from my lab to study both adaptive and ghost introgression in humans. First, I will discuss a work on adaptive…

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