Domain > aegelfand.github.io

More information on this domain is in AlienVault OTX

DNS Resolutions

Date	IP Address
2016-12-10	151.101.44.133 (ClassC)
2017-07-06	151.101.0.133 (ClassC)
2018-02-02	151.101.185.147 (ClassC)
2025-07-17	185.199.111.153 (ClassC)
2025-08-16	185.199.109.153 (ClassC)
2025-11-30	185.199.110.153 (ClassC)
2026-01-01	185.199.108.153 (ClassC)

HTTP/1.1 200 OKConnection: keep-aliveContent-Length: 8112Server: GitHub.comContent-Type: text/html; charsetutf-8permissions-policy: interest-cohort()Last-Modified: Mon, 11 Apr 2016 00:14:21 GMTAccess-

!DOCTYPE html PUBLIC -//W3C//DTD XHTML 1.0 Strict//EN http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd>html xmlnshttp://www.w3.org/1999/xhtml>head>title>Andrew Gelfand /title>meta http-equivcontent-type contenttext/html; charsetutf-8 />link hrefdefault.css relstylesheet typetext/css />/head>body>div idcontent>  div>    h1>Andrew E Gelfand/h1>    h2>Research Scientist in Machine Learning / Quantitative Researcher /h2>  /div>  div idmenu>    ul>      li>a href# idmain-menu1>Home/a>/li>      li>a href#publications idmain-menu2>Publications/a>/li>      li>a href#chapters idmain-menu2>Book Chapters/a>/li>      li>a href#thesis idmain-menu2>Thesis/a>/li>      li>a hrefhttps://github.com/aegelfand/>Software/a>/li>    /ul>  /div>  div idleft>    p>I am an applied researcher interested in developing and deploying scalable machine learning systems. I work at a NYC-based hedge fund where I apply advanced machine learning techniques to complex, quantitative trading problems. Prior to that I was a research scientist at a hrefhttps://yahooresearch.tumblr.com>Yahoo Labs/a> working on recommendation and ranking problems./p>     p>I recieved my Ph.D. from the University of California, Irvine and was co-advised by a hrefhttp://www.ics.uci.edu/~dechter/>Rina Dechter/a> and a hrefhttp://www.ics.uci.edu/~ihler/>Alex Ihler/a>. I also had the good fortune of working with a hrefhttp://www.ics.uci.edu/~welling/>Max Welling/a> and a hrefhttps://sites.google.com/site/mchertkov/>Misha Chertkov/a> during my time at UC Irvine. My expertise is in developing methods to efficiently learn from data using graphical models - a modeling formalism that provides structure to probability distributions over large, complex systems./p>    h2>a namepublications>Publications/a>/h2>    ul>	li>a hrefpub/wsdm2016.pdf>Geographic Segmentation via a Latent Poisson Factor Model/a>br />  Rose Yu, Andrew Gelfand, Suju Rajan, Cyrus Shahabi & Yan Liubr />  i>WSDM 2016./i> San Francisco, USA, February 2016./li>	li>a hrefpub/nips_matching_final_aeg_

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Domain > aegelfand.github.io

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