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https://engineering.wustl.edu/Profiles/Pages/Roman-Garnett.aspx96Roman Garnett<img alt="" src="/Profiles/PublishingImages/Garnett_Roman.jpg?RenditionID=6" style="BORDER:0px solid;" />​​Assistant ProfessorRoman Garnett - Computer Science & Engineering - Researches​ new Bayesian machine-learning techniques​​​PhD, University of Oxford, 2010<br/>MS, Washington University in St. Louis, 2004<br/>AB, Washington University in St. Louis, 2004​ <div> <br/> </div><p>  <a href="https://scholar.google.com/citations?user=CUkAtC4AAAAJ&hl=en"><img src="/Profiles/PublishingImages/gscholar.png" alt="" style="margin: 0px 0px -5px;"/> Google Scholar</a></p>https://sites.wustl.edu/machinelearning/<p>​​​Assistant Professor</p><h3>Research</h3><p>Professor Garnett's main research interest is developing new Bayesian machine-learning techniques for sequential decision making under uncertainty. He is particularly interested in active learning—especially with atypical objectives—Bayesian optimization, intelligent approaches to approximate Bayesian inference, and Bayesian quadrature. ​He is also interested in learning problems involving large-scale graph data. </p><h3>​​Biography</h3><p>Professor Garnett came to WashU in January 2015.</p> <img alt="" src="/Profiles/ResearchImages/Garnett_research.jpg?RenditionID=13" style="BORDER:0px solid;" /><p>314-935-4992<br/><a href="mailto:scg@wustl.edu"><span><span></span></span></a><a href="mailto:%E2%80%8Bgarnett@wustl.edu%E2%80%8B">​garnett@wustl.edu​</a>​​<br/>Jolley Hall, Room 504​<br/></p><div class="ms-rtestate-read ms-rte-wpbox" contenteditable="false"><div class="ms-rtestate-notify ms-rtestate-read fa907774-d987-49f3-b056-4efc2fc0e656" id="div_fa907774-d987-49f3-b056-4efc2fc0e656" unselectable="on"></div><div id="vid_fa907774-d987-49f3-b056-4efc2fc0e656" unselectable="on" style="display: none;"></div></div><ul style="margin-top: -10px;"><li> <a href="/news/Pages/WashU-computer-scientists-part-of-$8M-big-data-research-grant.aspx">WashU computer scientists part of $8M big data research grant</a><br/></li></ul>

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