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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Andrew E. Cohen</title>
<link rel="stylesheet" href="/resume/fonts.css" type="text/css"/>
<link rel="stylesheet" href="/resume/main.css" type="text/css"/>
</head>
<body>
<div id="container">
<h1 id="name">Andrew E. Cohen</h1>
<p id="contact">
1474 Sacramento Street, San Francisco, California 94109
<br>
<a href="[email protected]">[email protected]</a>
‒
516.993.5087
</p>
<h2><span>Education</span></h2>
<div id="education">
<p>
<strong>State University of New York at Binghamton</strong>
<br><br>
<em>Ph.D., Computer Science (Reinforcement Learning)</em>
<time>January 2020</time>
<br>
Advisor: Dr. Lei Yu
<br>
Research: Diversity driven approaches in reinforcement learning
<br><br>
<em>M.S., Computer Science</em>
<time>May 2016</time>
<br>
Advisor: Dr. Lei Yu
<br>
Thesis: Diverse Exploration
<br><br>
<em>B.S., Mathematics</em>
<time>May 2014</time>
<br>
Award for Excellence in Mathematical Sciences, Honors in Mathematics, Phi Beta Kappa Honor Society, Pi Mu Epsilon Mathematics Honor Society
</p>
</div>
<br><br>
<h2><span>Research Experience</span></h2>
<div id="r experience">
<p>
<strong>Unity Technologies</strong>
<time>August 2019 - present</time>
</p>
<em>Senior Research Engineer</em>
<br>
Core developer of the Unity ML-Agents toolkit (https://github.com/Unity-Technologies/ml-agents) with a focus primarily on cooperative and competitive multi-agent reinforcement learning.
<br>
<p>
<strong>State University of New York at Binghamton</strong>
<time>September 2015 - January 2020</time>
</p>
<em>Reinforcement Learning Research Assistant</em>
<br>
Project: "Fast and Reliable Reinforcement Learning." Developing methods to quickly improve the performance of a reinforcement learning agent in domains with high sample cost and risk.
<br>
<p>
<strong>General Electric Global Research, Machine Learning Lab</strong>
<time>Summer 2016 <br>Winter 2016<br> Summer 2017 </time>
</p>
<em>Graduate Research Intern</em>
<br><br>
Project: "Reinforcement Learning for Additive Manufacturing." Designed and implemented a reinforcement learning based controller for a cutting edge additive manufacturing technique.
<br>
Project: "Digital Twin Model Management with Reinforcement Learning." Designed and implemented a reinforcement learning solution to manage a data-driven model of a GE gas turbine during operation.
<br>
<p>
<strong>Air Force Research Lab Information Directorate</strong>
<time>Summer 2015</time>
</p>
<em>Research Intern</em>
<br>
Project: "Reward Function Transfer for Convenient Use of RL Systems." Investigated the difficulty in designing an efficient learning signal using using a simple robotics domain as a case study.
<br>
</div>
<!--<br><br>
<h2><span>Teaching Experience</span></h2>
<div id="t experience">
<p>
<strong>Graduate Teaching Assistant</strong>
<time>January 2015 - May 2019</time>
</p>
<ul>
<li>Automata Theory and Formal Languages</li>
<li>Design and Analysis of Algorithms</li>
</ul>
<p>
<strong>Undergraduate Course Assistant</strong>
<time>Fall 2013</time>
</p>
<ul>
<li>Calculus I</li>
</ul>
</div>
<br><br>
<h2><span>Service</span></h2>
<div id="Service">
<ul>
<li>Reviewer: AAAI 2022</li>
</ul>
<ul>
<li>Reviewer: IJCAI 2020</li>
</ul>
<ul>
<li>Reviewer: IJCAI 2019</li>
</ul>
<ul>
<li>Reviewer: AAAI 2019</li>
</ul>
<ul>
<li>Reviewer: AAAI 2018</li>
</ul>
<ul>
<li>Reviewer: KDD 2017</li>
</ul>
</div>
-->
<br><br>
<h2><span>Publications</span></h2>
<div id="publications">
<p>
<strong>Diverse Exploration for Fast and Safe Policy Improvement</strong>
<br><em><strong>Andrew Cohen</strong>, Lei Yu, Robert Wright</em>
<br>Proceedings of the Thirty-Second Conference on Artificial Intelligence, 2876--2883 (AAAI 2018)
</p>
<p>
<strong>Ensemble Management under Concept Drift via Reinforcement Learning</strong>
<br><em><strong>Andrew Cohen</strong>, Paul Ardis, Weizhong Yan</em>
<br>Modeling the World's Systems, (MOMACS 2019)
</p>
<p>
<strong>Diverse Exploration via Conjugate Policies for Policy Gradient Methods</strong>
<br><em><strong>Andrew Cohen</strong>, Xingye Qiao, Lei Yu, Elliot Way, Xiangrong Tong</em>
<br>Proceedings of the Thirty-Third Conference on Artificial Intelligence, 3404-3411 (AAAI 2019)
</p>
<p>
<strong>Maximum Entropy Diverse Exploration: Disentangling Maximum Entropy Reinforcement Learning</strong>
<br><em><strong>Andrew Cohen</strong>, Lei Yu, Xingye Qiao, Xiangrong Tong</em>
<br>arXiv preprint arXiv:1911.00828 2019
</p>
<p>
<strong>Unity: A General Platform for Intelligent Agents</strong>
<br><em>Arthur Juliani, Vincent-Pierre Berges, Ervin Teng, <strong>Andrew Cohen</strong>, Jonathan Harper, Chris Elion, Chris Goy, Yuan Gao, Hunter Henry, Marwan Mattar, Danny Lange</em>
<br>arXiv preprint arXiv:1809.02627 2020
</p>
<p>
<strong>Generating Multi-type Temporal Sequences to Mitigate Class-imbalanced Problem</strong>
<br><em>Lun Jiang, Nima Salehi Sadghiani, Zhuo Tao, <strong>Andrew Cohen</strong></em>
<br>Joint European Conference on Machine Learning and Knowledge Discovery in Databases(ECML-PKDD 2021)
</p>
<p>
<strong>On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learning</strong>
<br><em><strong>Andrew Cohen</strong>, Ervin Teng, Vincent-Pierre Berges, Ruo-Ping Dong, Hunter Henry, Marwan Mattar, Alexander Zook, Sujoy Ganguly</em>
<br>RL in Games Workshop AAAI 2022
</p>
<p>
<strong>Transfer RL Across Observation Feature Spaces via Model-Based Regularization</strong>
<br><em>Yanchao Sun*, Ruijie Zhang, Xiyao Wang, <strong>Andrew Cohen</strong>, Furong Huang</em>
<br>Internation Conference on Learning Representations (ICLR 2022)
<br><em>* Work mentored while an intern at Unity
</p>
</div>
<br><br>
<h2><span>Patents</span></h2>
<div id="patents and disclosures">
<p>
<strong>Andrew Cohen</strong> and Paul Ardis. Ensemble Management under Concept Drift via Reinforcement Learning. US Patent (US 62/459,789) in process.
</p>
<p>
Lei Yu and <strong>Andrew Cohen</strong>. Methods for Diverse Exploration in Reinforcement Learning. US Patent no. US20190228309A1.
</p>
</div>
<br><br>
<h2><span>Skills</span></h2>
<div id="skills">
<ul>
<li class="strong">Languages</li>
<li>Python</li>
<li>C#</li>
<li>Bash</li>
</ul>
<ul>
<li class="strong">Tools</li>
<li>PyTorch</li>
<li>Tensorflow</li>
<li>OpenAI Gym</li>
<li>Vim</li>
<li>Git</li>
<li>Unity</li>
</ul>
</div>
</div>
</div>
</body>
</html>