Machine Learning 101: From particle astrophysics to ethical considerations

Date

Friday November 3, 2023
1:30 pm - 2:30 pm

Location

STI A

Ryan D. Martin,
Undergraduate Chair, Associate Professor
Department of Physics, Engineering Physics & Astronomy

Abstract

This talk will start with a basic introduction to machine learning to show how easy it is for anyone to get started using these tools. I will then discuss a few applications of machine learning. These range from our work to remove electronic noise in particle astrophysics experiments to pricing stock options and determining the deformation of a bouncing ping-pong ball. The talk will conclude with some thoughts, and hopefully some lively discussion, about the ethics of artificial intelligence and, more generally, training STEM students without including formal ethics training.

Timbits, coffee, tea will be served in STI A before the colloquium.

 

From Telescopes to Dark Matter & Black Holes

Date

Friday October 20, 2023
1:30 pm - 2:30 pm

Location

STI A

Ting Li
Assistant Professor
Department of Astronomy and Astrophysics
University of Toronto

Abstract

In this talk, I will summarize astrophysical observations that can constrain the fundamental physics of dark matter in the era of modern cosmic surveys. I will highlight the progress that has been made so far with past and ongoing astronomical observations with modern surveys, and discuss how the next-generation cosmic survey programs will complement other experiments to strengthen our understanding of the fundamental characteristics of dark matter. I will finish my talk with a program that I am leading: the Southern Stellar Stream Spectroscopic Survey, or S5, and discuss how we study dark matter and black holes together with this program.

Timbits, coffee, tea will be served in STI A before the colloquium.

 

Mark Ward

Mark Ward

Mark Ward

Research Associate

he/him

Research Associates

Physics, Engineering Physics & Astronomy

Arts & Science

Area of Study

Particle Astrophysics

Supervisor: Prof. M. Chen

About Mark

Physicist and all round nerd. In my spare time I enjoy photography, video gaming and retro-gaming.

 

 

Ryan Bayes

Ryan Bayes

Ryan Bayes

Post Doctorate

he/him

Post Doctorate

Physics, Engineering Physics & Astronomy

Arts & Science

Area of Research

Particle Astrophysics

Co-Supervisors: Prof. M. Chen, Dr. C. Kraus

Ryan's CV (46 KB)

About Ryan

An avid brass musician and once upon a time competitive fencer, I enjoy hiking and biking when I am able. I am also an avid reader of science fiction and non-fiction titles, and I am always more comfortable when I have a book within reach.

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