<div><br></div><div><span style="font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px;box-sizing:inherit"><span style="box-sizing:inherit"><span style="box-sizing:inherit"><h1 style="box-sizing:inherit;font-weight:300;padding:0px;font-feature-settings:"kern","liga","dlig";font-size:1.76471em;line-height:normal;font-stretch:normal;color:rgb(0,60,118);text-transform:uppercase;display:inline-block">S&DS|CS JOINT SEMINAR, EMMA PIERSON</h1></span></span></span><span style="font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px;box-sizing:inherit;margin-left:5px"><span style="box-sizing:inherit"><span style="box-sizing:inherit">Stanford University</span></span></span><br><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div style="box-sizing:inherit;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><div style="box-sizing:inherit;font-size:20px;font-weight:600;line-height:1.2;margin-bottom:1em;margin-top:0.5em">Data science methods to reduce inequality and improve healthcare</div></div></div></div><div style="box-sizing:inherit;float:left;width:auto;padding-right:15.3125px;max-width:30%;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><img src="https://statistics.yale.edu/sites/default/files/styles/user_picture_node/public/new.011014.rhodes1.jpg?itok=ehbYVCZn" width="400" height="480" alt="" style="box-sizing:inherit;border:0px;max-width:100%;height:auto;vertical-align:bottom"></div></div></div></div><div style="box-sizing:inherit;float:left;width:auto;max-width:65%;padding-left:22.9688px;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><div style="box-sizing:inherit;color:rgb(0,60,118);font-size:18px;line-height:1.4"><span style="box-sizing:inherit">Monday, February 24, 2020<span style="box-sizing:inherit;float:left;width:396.484px"><span style="box-sizing:inherit">4:00PM</span> to <span style="box-sizing:inherit">5:00PM</span></span></span></div></div></div><div style="box-sizing:inherit"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><span style="box-sizing:inherit">YINS</span> <span style="box-sizing:inherit;margin-left:0.25em;font-size:0.925em;line-height:1.55;letter-spacing:0.05em;word-spacing:0.05em;text-transform:lowercase;font-feature-settings:"smcp""><a href="http://maps.google.com/?q=17+Hillhouse+Avenue%2C+Rm.+328%2C+New+Haven%2C+CT%2C+06511%2C+us" style="box-sizing:inherit;outline:none;line-height:inherit;color:rgb(40,109,192)" target="_blank">see map</a> </span><div style="box-sizing:inherit">17 Hillhouse Avenue, Rm. 328</div><span style="box-sizing:inherit">New Haven</span>, <span style="box-sizing:inherit">CT</span> <span style="box-sizing:inherit">06511</span></div></div></div></div></div><div style="box-sizing:inherit"><div style="box-sizing:inherit"><div style="box-sizing:inherit"><a href="https://cs.stanford.edu/~emmap1/index.html" style="box-sizing:inherit;text-decoration-line:none;outline:none;line-height:1.5;color:rgb(0,60,118);font-size:16px" target="_blank">Website</a></div></div></div></div><div style="box-sizing:inherit;clear:both;padding-top:15px;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div style="box-sizing:inherit"><div style="box-sizing:inherit;font-weight:bold">Information and Abstract: </div><div style="box-sizing:inherit"><div style="box-sizing:inherit"><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px">I will describe how to use data science methods to understand and reduce inequality in two domains: criminal justice and healthcare. First, I will discuss how to use Bayesian modeling to detect racial discrimination in policing. Second, I will describe how to use machine learning to explain racial and socioeconomic inequality in pain.</p><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px">Bio: Emma Pierson is a PhD student in Computer Science at Stanford, supported by Hertz and NDSEG Fellowships. Previously, she completed a master’s degree in statistics at Oxford on a Rhodes Scholarship. She develops statistical and machine learning methods to study two deeply entwined problems: reducing inequality and improving healthcare. She also writes about these topics for broader audiences in publications including The New York Times, The Washington Post, FiveThirtyEight, and Wired. Her work has been recognized by best paper (AISTATS 2018), best poster (ICML Workshop on Computational Biology), and best talk (ISMB High Throughput Sequencing Workshop) awards, and she has been named a Rising Star in EECS and Forbes 30 Under 30 in Science.</p><p style="box-sizin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</blockquote></div></div>-- <br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature">Sent from mobile phone</div>