(Machine) Learning the Genealogy of the Milky Way

  • Speaker
  • Lina Necib, Ph.D.Assistant Professor of Physics, Massachusetts Institute of Technology
Date & Time


Location

Gerald D. Fischbach Auditorium
160 5th Ave
New York, NY 10010 United States

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Doors open: 5:30 p.m. (No entrance before 5:30 p.m.)

Lecture: 6:00 p.m. – 7:00 p.m. (Admittance closes at 6:20 p.m.)

The 2024 lecture series in mathematics and computer science is “Machine Learning in the Natural Sciences.” Machine learning has become a transformative tool for advancing science. In these lectures, scientists will discuss their use of machine learning in everything from biology and oceanography to astrophysics and particle physics. These applications are sparking discoveries while also helping scientists uncover what the tools are actually gleaning from data.
 
 
2024 Lecture Series Themes

Biology: Dynamics of Life

Mathematics and Computer Science: Machine Learning in the Natural Sciences

Neuroscience and Autism Science: The Social Brain

Physics: Atmospheres: Earth to Exoplanets

About Presidential Lectures

Presidential Lectures are free public colloquia centered on four main themes: Biology, Physics, Mathematics and Computer Science, and Neuroscience and Autism Science. These curated, high-level scientific talks feature leading scientists and mathematicians and are intended to foster discourse and drive discovery among the broader NYC-area research community. We invite those interested in the topic to join us for this weekly lecture series.

Galaxies form and grow by merging with other galaxies, making the formation history of a galaxy resemble that of a family tree. Our galaxy, the Milky Way, is no exception. With recent telescopes like the Gaia space mission, we can finally build the Milky Way’s family tree.

In this presidential lecture, Lina Necib will discuss how we can use machine learning techniques to unveil the secrets of the merger history of our galaxy, including clustering techniques that group stars by their original galaxies, neural networks that separate stars with galactic and extragalactic origins, and anomaly detectors that uncover faint signatures of old mergers. Putting all this work together is a step towards building our galaxy’s family tree, she says.

About the Speaker

Necib is originally from Tunisia. She received a B.A. in math and physics from Boston University in 2012 and a Ph.D. in particle physics from MIT in 2017. She was then a Sherman Fairchild Fellow at Caltech starting in 2017 before starting as an assistant professor of physics at MIT in July 2021. Her research interests in theoretical astrophysics center around dark matter.

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