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<!DOCTYPE html>
<html lang="en-us">
<head>
<link href="http://gmpg.org/xfn/11" rel="profile">
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<title>Waren Long</title>
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<div class="header">
<a href="/" class="name-link">Waren Long | Machine Learning</a>
<div class="header-right">
<a href="/work.html" class="work-link">Work.</a>
<a href="/about.html" class="about-link">About.</a>
<a href="/publications.html" class="about-publications">Publications.</a>
</div>
</div>
<div class="content">
<h1 class="hello">Hello,</h1>
<div class="bio-content">
<img src="static/me_centered.jpg"/>
<div class="bio-text">
<p>
I'm Waren, a Machine Learning Engineer at <a href="https://sourced.tech/" target="_blank">source{d}</a>.
I apply NLP techniques to source code and other types of software engineering artifacts
like Git metadata, CI logs or Docker images. The idea is first to gain better visbility into the code base
and then suggest actionnable insights to ease software development.
While <em>MLonCode</em> innovations mostly come from academia,
source{d} aims to bridge the gap between research and production through open source tools
and publicly available machine learning models.
In the past, we've developed <a href="https://github.com/src-d/lookout" target="_blank">Lookout</a>,
a ML-powered assisted code review framework that learns from your code base.
</p>
<p>
Occasionally, I write papers about our research and publish them
in Data Mining or ML conferences I like.
I also love to speak in ML meetups or Python related conferences to share both
my latest work and my favourite open source librairies.
</p>
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