{"id":11179,"date":"2020-11-19T12:20:12","date_gmt":"2020-11-19T17:20:12","guid":{"rendered":"https:\/\/web.uri.edu\/artsci\/?p=11179"},"modified":"2020-11-19T12:21:19","modified_gmt":"2020-11-19T17:21:19","slug":"ones-ohs-assistant-professor-of-computer-science-sarah-brown-on-coming-to-uri","status":"publish","type":"post","link":"https:\/\/web.uri.edu\/artsci\/news\/ones-ohs-assistant-professor-of-computer-science-sarah-brown-on-coming-to-uri\/","title":{"rendered":"Ones &amp; Ohs: Assistant Professor of Computer Science Sarah Brown on Coming to URI"},"content":{"rendered":"<p><span style=\"font-weight: 400\"><strong>Name:<\/strong> Sarah Brown<br \/>\n<\/span><span style=\"font-size: 20px;font-weight: 400\"><strong>URI Title:<\/strong> Assistant Professor of Computer Science<br \/>\n<\/span><span style=\"font-size: 20px;font-weight: 400\"><strong>Email:<\/strong> brownsarahm@uri.edu<br \/>\n<\/span><span style=\"font-size: 20px;font-weight: 400\"><strong>Pronouns:<\/strong> she\/her\/hers<\/span><\/p>\n<p><span style=\"font-weight: 400\">Assistant Professor of Computer Science Sarah Brown is a bit of a traveler. After receiving her Ph.D. in Electrical Engineering from Northeastern University in December 2016, Brown went west, serving as a Chancellor\u2019s Postdoctoral Fellow at the University of California Berkeley from January 2017 to July 2018. From there, she returned to New England in August 2018, this time serving as a Data Science Postdoctoral Research Associate at Brown University until July 2020, after which she took up her position as one of URI\u2019s newest faculty members. \u201cI had always liked visiting RI, and I fell in love with living here when I started working at Brown as a Postdoc,\u201d she says. \u201cLittle Rhody is quirky in a way, and I&#8217;m excited to support diversity in computer science, which is severely lacking, by working at a public institution. In my interview, the faculty in <a href=\"https:\/\/web.uri.edu\/cs\/\">Computer Science and Statistics<\/a> were friendly and welcoming, and that was something I knew I wanted when I started my career as a professor.\u201d<\/span><\/p>\n<p style=\"text-align: left\"><span style=\"font-weight: 400\">This semester, Brown is teaching <\/span><span style=\"font-weight: 400\">CSC 310: <\/span><i><span style=\"font-weight: 400\">Programming for Data Science<\/span><\/i><span style=\"font-weight: 400\">, and next semester she looks forward to teaching <\/span><i><span style=\"font-weight: 400\"><em>CSC 592:<\/em> Machine Learning for Science &amp; Society<\/span><\/i><span style=\"font-weight: 400\">. When she isn\u2019t teaching, Brown looks forward to continuing to pursue her research interests. \u201cMy research is about how we can adapt machine learning algorithms and the systems they&#8217;re embedded in in order to prevent AI from reinforcing patterns of discrimination,\u201d she says. \u201cPreviously, programmers directly wrote all of the instructions in the algorithms that were deployed, but machine learning allows them to define general goals and describe how to learn from the world, feed their algorithm a bunch of data, and let that algorithm write another algorithm. These computer generated algorithms require more careful examination in order for them to not learn the wrong things about the world. I\u2019m currently looking at how we can build tools for people with social science expertise instead of computer science expertise to examine the computer-written algorithms. In another project, I&#8217;m working to develop better learning algorithms that can learn from general data and specific expert advice at the same time. My third main project right now is in collaboration with a social psychologist at Brown University, trying to understand what types of fairness people would prefer algorithms respect, what social factors influence their preferences, and what features of an algorithm influence their preferences.\u201d<\/span><\/p>\n<div class=\"cl-wrapper cl-card-wrapper\"><a class=\"cl-card   right\" href=\"https:\/\/web.uri.edu\/cs\/\" title=\"\"><div class=\"cl-card-container media\"><img decoding=\"async\" src=\"https:\/\/web.uri.edu\/wp-content\/uploads\/sites\/1132\/feat_img_comp_sci.jpg\" srcset=\"\" alt=\"\"><\/div><div class=\"cl-card-container text\"><div class=\"cl-card-text\"><h2>Computer Science and Statistics<\/h2><p>We provide a supportive, integrative center of multidisciplinary learning and research.<\/p><\/div><\/div><div class=\"cl-card-container button\">Explore<\/div><\/a><\/div>\n<p style=\"text-align: left\"><span style=\"font-weight: 400\">Thinking back on her own prior collegiate experience &#8212; and now with almost a semester as an Assistant Professor under her belt &#8212; Brown has plenty of advice to give, stressing the importance of a balanced course-load. \u201cMy advice for computer science students is to take advantage of a liberal arts education to gain an understanding of things a computer science degree doesn&#8217;t require,\u201d she says. \u201cIncreasingly the hardest problems in this field aren&#8217;t the purely computational ones, but the aspects of how we make this real in a safe, fair, trustworthy way. That requires understanding from the social sciences, humanities, and experimental practices of physical sciences. Computing touches every aspect of our daily lives now, so we, as computing professionals, need to be aware of when problems are harder than they appear and able to ask good questions and gather advice from other experts.\u201d She even has words of wisdom for those not involved in computer science, as she advises, \u201cFor non-computer science students, I have complementary advice: to take at least one course that helps you understand a little bit about how computers and programming work and then really think about how it intersects with your other material. The world is changing quickly, and you have a tremendous advantage to adapt and be creative if you can relate with technology not only as a tool, but anticipate how it will impact your domain.\u201d<\/span><\/p>\n<p><em>~Written by <span style=\"font-weight: 400\">Chase Hoffman, Writing &amp; Rhetoric and Anthropology Double Major, URI Class of December 2020<\/span><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Our newest Assistant Professor of Computer Science, Sarah Brown, is interested in adapting machine learning algorithms and the systems they are embedded in to prevent Artificial Intelligence from reinforcing patterns of discrimination.<\/p>\n","protected":false},"author":1089,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[7],"tags":[214,251],"class_list":["post-11179","post","type-post","status-publish","format-standard","hentry","category-news","tag-computer-science","tag-computer-science-and-statistics"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts\/11179","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/users\/1089"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/comments?post=11179"}],"version-history":[{"count":5,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts\/11179\/revisions"}],"predecessor-version":[{"id":11197,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/posts\/11179\/revisions\/11197"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/media?parent=11179"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/categories?post=11179"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/artsci\/wp-json\/wp\/v2\/tags?post=11179"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}