{"id":31700,"date":"2021-02-24T12:12:36","date_gmt":"2021-02-24T16:12:36","guid":{"rendered":"https:\/\/www.bu.edu\/cise\/?p=31700"},"modified":"2021-10-13T13:50:08","modified_gmt":"2021-10-13T17:50:08","slug":"ruidi-chen-dissertation-award-recipient","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/cise\/ruidi-chen-dissertation-award-recipient\/","title":{"rendered":"\u2018Happy and Proud,\u2019 Declares Ruidi Chen, Dissertation Award Recipient"},"content":{"rendered":"<p><img loading=\"lazy\" src=\"\/cise\/files\/2021\/03\/sorkin-471x636.png\" alt=\"\" width=\"217\" height=\"293\" class=\" wp-image-31701 alignleft\" \/>As an applied scientist at Microsoft,<span>\u00a0alumnus Ruidi Chen (SE PhD \u201919)<\/span>\u00a0has already established herself as a pioneer in a new area of research called Distributionally Robust Optimization (DRO). Her resume boasts 12 co-authored papers and her monograph on Distributionally Robust Learning was recently featured in<span>\u00a0<\/span><em>NOW Foundations and Trend.<span>\u00a0<\/span><\/em>Plus, this early-career engineer already piloted her first medical study, which took place at Boston Medical Center.<\/p>\n<p>Chen completed her PhD in Systems Engineering in 2019 and relocated to Bellevue, WA to begin her career at Microsoft. She is now developing core data mining and machine learning algorithms, applies statistical concepts and techniques to analyze advertisers\u2019 bidding behavior and user preference, and builds robust user response models and develops optimal bidding strategies for advertisers.<\/p>\n<p>The 2019\/2020 award winning dissertation project\u00a0\u2014titled \u201cDistributionally Robust Learning under the Wasserstein Metric\u201d\u2014was the culmination of four years of hard work and research. It\u00a0explores learning models that are immunized against data perturbations. Ultimately, Chen was able to develop a novel systematic way of robustifying regression\/classification models, improve the prediction accuracy of patients\u2019 readmission and the accuracy of CT radiation overdose detection, and develop an optimal prescription algorithm that is predicted to lower the HbA1c\/systolic blood pressure by around 20%.<\/p>\n<p>\u201c[I\u2019m] happy and proud of our work. I\u2019m also deeply grateful to my thesis committee members, Yannis in particular, for their constant support and guidance,\u201d says Chen.<\/p>\n<p>Chen is especially grateful for the support of her advisor, Professor<span>\u00a0<\/span><a href=\"https:\/\/www.bu.edu\/eng\/profile\/ioannis-paschalidis\/\" target=\"_blank\" rel=\"noopener noreferrer\">Ioannis (Yannis) Paschalidis<\/a><span>\u00a0<\/span>(ECE, BME, SE, CISE). \u201cHe helped me open up my perspective and build the confidence in my work. Without him I would not have achieved my goal,\u201d says Chen. \u201cHis immense knowledge, endless positivity and enthusiasm on scientific research benefited me tremendously. I feel extremely lucky to have a supervisor who cared so much about my work.\u201d<\/p>\n<p>The 2021 dissertation award recipient will be selected in late April and announced in May.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>As an applied scientist at Microsoft,\u00a0alumnus Ruidi Chen (SE PhD \u201919)\u00a0has already established herself as a pioneer in a new area of research called Distributionally Robust Optimization (DRO). Her resume boasts 12 co-authored papers and her monograph on Distributionally Robust Learning was recently featured in\u00a0NOW Foundations and Trend.\u00a0Plus, this early-career engineer already piloted her first [&hellip;]<\/p>\n","protected":false},"author":18553,"featured_media":31701,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[245],"tags":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts\/31700"}],"collection":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/users\/18553"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/comments?post=31700"}],"version-history":[{"count":8,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts\/31700\/revisions"}],"predecessor-version":[{"id":34530,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/posts\/31700\/revisions\/34530"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/media\/31701"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/media?parent=31700"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/categories?post=31700"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/cise\/wp-json\/wp\/v2\/tags?post=31700"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}