Difference between revisions of "User:Akoul"
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=== Random Notes === | === Random Notes === | ||
* Once ran a triathlon with a broken toe bone, just to look better than an MTV VJ right behind me, who was being captured on camera all along. | * Once ran a triathlon with a broken toe bone, just to look better than an MTV VJ right behind me, who was being captured on camera all along. | ||
| − | * Have a photo site with over a million visitors, 2000 sites currently using my Creative Commons licensed photos, including New York Times, Wikipedia, Yahoo Homepages, ABC News, Lifehacker | + | * Have a photo site with over a million visitors, 2000 sites currently using my Creative Commons licensed photos, including New York Times, Wikipedia, Yahoo Homepages, ABC News, Lifehacker, ReadWriteWeb, Ars Technica, etc. [http://www.flickr.com/photos/anirudhkoul/sets/72157614703171283/detail/ Photogallery] |
| − | |||
== Brainstorming Idea == | == Brainstorming Idea == | ||
Revision as of 13:41, 6 September 2011
Contents
Anirudh Koul
Who am I and Why I am here
Hello there, I am Koul (Pronounced 'Cool') from Canada. I am a Masters students in the Very Large Information Systems program (between LTI & ISR).
Before joining CMU, I worked 4 years with Yahoo as a Research Engineer. I am here to gauge what new technologies can be build by combining NLP and Machine Learning.
Superpowers
- Can function sanely in -40 Degree weather, and still keep continuing experimentation.
- Have crashed IBM Watson : Proof
- Have developed 3 Question Answering systems, once personally, then under Dr Eric Nyberg and later under Dr Noah Smith.
Random Notes
- Once ran a triathlon with a broken toe bone, just to look better than an MTV VJ right behind me, who was being captured on camera all along.
- Have a photo site with over a million visitors, 2000 sites currently using my Creative Commons licensed photos, including New York Times, Wikipedia, Yahoo Homepages, ABC News, Lifehacker, ReadWriteWeb, Ars Technica, etc. Photogallery
Brainstorming Idea
- Extracting Facts from Wikipedia Text to generate a Fact relation hierarchy
- Automatic extraction of answering patterns for Question Answering
* Corpus : Yahoo Research Webscope Dataset for Yahoo Answers
