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Splash Spring 2016 is April 9-10

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  • Registration opens on 3/16 at 7:30pm.
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ESP Biography



CHRIS YOUNG, Stanford Electrical Engineering Graduate student




Major: Electrical Engineering

College/Employer: Stanford

Year of Graduation: G

Picture of Chris Young

Brief Biographical Sketch:

I'm originally from San Antonio, Texas and attended The University of Texas at Austin where I majored in Electrical Engineering and Economics. Currently, I'm a second year graduate student at Stanford in the Electrical Engineering Department. My passion for engineering came from working in the UT Satellite Design Lab and has continued into grad. school and DIY projects. I've interned at UT's Applied Research Laboratories as well as with Apple Inc. in the Mac audio department.



Past Classes

  (Clicking a class title will bring you to the course's section of the corresponding course catalog)

E2157: Audio Digital Signal Processing Lab in Splash! Spring 2012
Ever wonder how an ipod works? What about what it means to turn up the bass or treble? Come join this lab class and get hands on experience processing audio signals digitally (using a PC). We will talk about other topics like reverb, synthesizers, and auto-tune. We will conceptually look at how these algorithms work and what it means to process a signal using hands on examples with a PC. To actually work with audio signals, we will use programs (called patches) written with a freely available audio software called Pure Data (PD). Bring your headphones!


E1912: An Intro to Digital Signal Processing with Audio Applications in Splash! Fall 2011
Every wonder what it means for a signal to be digital? How your iPod turns bits into sounds or how exactly to get more bass out of a song? This class will answer these questions by discussing the basics of digital signal processing (DSP). From a historical standpoint, DSP is a relatively new field when compared to other areas of applied mathematics, but is arguably one of the largest driving forces in our modern technology. While the math can be fairly rigorous, we won't focus on the hard stuff and will take a more qualitative approach while also discussing how DSP is applied in audio.