Difference between revisions of "User:Advanne"

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==Personal Stuff==
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==About Me==
  
 
My name is Advaitha Anne and I'm a member of the Duke Class of 2021. I'm interested in studying some combination of biomedical engineering,  electrical and computer engineering (ECE), and economics. I was born in Pittsburgh but grew up in Hockessin, Delaware.  I'm enjoy photography, writing, traveling, and watching ESPN.
 
My name is Advaitha Anne and I'm a member of the Duke Class of 2021. I'm interested in studying some combination of biomedical engineering,  electrical and computer engineering (ECE), and economics. I was born in Pittsburgh but grew up in Hockessin, Delaware.  I'm enjoy photography, writing, traveling, and watching ESPN.
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==Pronunciation==
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Ad-vay-tha (first name) A-neigh (last name)
  
 
==Engineering Grand Challenges==
 
==Engineering Grand Challenges==

Latest revision as of 04:16, 17 October 2017

About Me

My name is Advaitha Anne and I'm a member of the Duke Class of 2021. I'm interested in studying some combination of biomedical engineering, electrical and computer engineering (ECE), and economics. I was born in Pittsburgh but grew up in Hockessin, Delaware. I'm enjoy photography, writing, traveling, and watching ESPN.

Pronunciation

Ad-vay-tha (first name) A-neigh (last name)

Engineering Grand Challenges

New Theory Cracks Open the Black Box of Deep Learning, Natalie Wolchover , Quanta Magazine, 21 September 2017, accessed 21 September 2017 (Reverse-Engineering the Brain)

MATLAB Demonstration

My favourite demonstration was the one titled "Changing Transparency". Compared the the regular 3-D plots, I thought that this demonstration was cool because it showed you how to reveal the actual working of a 3-D object that may have been previously masked. It allows for the accurate graphing of more complex mathematical models and the explanation of a texture map shows how this can be applied for meteorology. Plus, it was nice to play around with the different levels of opaqueness and the lighting. I thought this was one of the most applicable demonstrations for real life problems.