Splash Biography

Yes, you may hate taking Spanish in school, but this class will show you how similar languages from all around the world really are. We'll use language puzzles from the North American Computational Linguistics Olympiad to begin exploring these commonalities, investigating the ways words and sentences are structured.

Opera was once the enemy of public decency—a pre-TV Game of Thrones, if you will. Incest, murder, and sex graced stages from Moscow to Milan. I will be your guide on this journey of operatic depravity: along the way, we’ll peep at masterpieces like Don Giovanni, Carmen, and Tosca. This class will explore opera as it is, raw and without preconceptions. I combine brief lectures with performance excerpts from live performances and archival footage. Come willing to listen and discuss. No dress code.

Out of all the things one can learn, the most important is to learn how to learn! By acquiring the knowledge and skills that can increase the rate at which we acquire knowledge and skills, we enter a virtuous cycle of positive feedback. This is the type of cognitive investment that compounds on itself. This Splash presentation will expose students to the research of Harvard educated cognitive scientist Daniel Willingham on the neuroscience behind the principles of learning. By doing so, high school students will be better prepared to maximize the amount of learning during college.

"Big Data" and "Data Science" are big fancy-schmancy buzzwords these days in the field of technology. Facebook, Twitter, Google etc. all have "data science" teams. The Harvard Business Review called it the "sexiest job of the 21st century." But what is it? Why are people even interested? If you want to find out, come to this brief introduction to data science -- led by some Fellows from UChicago's Data Science for Social Good Fellowship.

How does Netflix recommend movies? Or Spotify songs? Or Facebook ads? How are new planets and galaxies discovered? Can machines ever replace doctors? In this class, you will learn about: 1.) current technologies that are driven by machine learning algorithms; 2.) how computers learn to do certain tasks; 3.) similarities and differences between how computers and humans learn. By end of the class, the students will 1.) understand how and why computers are better at certain tasks than humans; and 2.) know which type of tasks computers currently struggle with and why.