{"title":"SIGecom winter meeting 2022 highlights","authors":"Emily Diana, Mingzi Niu, Georgy Noarov","doi":"10.1145/3572885.3572886","DOIUrl":null,"url":null,"abstract":"Emily Diana is a rising fifth year Ph.D. student in Statistics and Data Science at the Wharton School, University of Pennsylvania, where she is advised by Michael Kearns and Aaron Roth. Her research focuses on the intersection of ethical algorithm design and socially aware machine learning, and she is honored to have been recognized as both a Rising Star in EECS by MIT and a Future Leader in Data Science by the University of Michigan. Before Penn, she received a B.A. in Applied Mathematics from Yale and an M.S. in Statistics from Stanford, and she spent two years as a software developer at Lawrence Livermore National Laboratory. Mingzi Niu is a rising fifth year Ph.D. student in Economics at Rice University, where she is advised by Mallesh Pai and Hülya Eraslan. Her research interest are primarily in microeconomic theory, with a focus on mechanism design, information theory and behavioral economics. Before Rice, she received a B.A. in Finance and Banking and a B.S. in Mathematics and Statistics at Peking University, and a M.A. in Economics at Duke University. Georgy Noarov is a rising third year PhD student in Computer and Information Science at the University of Pennsylvania, advised by Michael Kearns and Aaron Roth. Previously, he graduated from Princeton University with a B.A. in Mathematics. His research interests span across the fields of uncertainty quantification, online learning, fairness in machine learning, and algorithmic game theory.","PeriodicalId":56237,"journal":{"name":"ACM SIGecom Exchanges","volume":"20 1","pages":"3 - 23"},"PeriodicalIF":0.6000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGecom Exchanges","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3572885.3572886","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Emily Diana is a rising fifth year Ph.D. student in Statistics and Data Science at the Wharton School, University of Pennsylvania, where she is advised by Michael Kearns and Aaron Roth. Her research focuses on the intersection of ethical algorithm design and socially aware machine learning, and she is honored to have been recognized as both a Rising Star in EECS by MIT and a Future Leader in Data Science by the University of Michigan. Before Penn, she received a B.A. in Applied Mathematics from Yale and an M.S. in Statistics from Stanford, and she spent two years as a software developer at Lawrence Livermore National Laboratory. Mingzi Niu is a rising fifth year Ph.D. student in Economics at Rice University, where she is advised by Mallesh Pai and Hülya Eraslan. Her research interest are primarily in microeconomic theory, with a focus on mechanism design, information theory and behavioral economics. Before Rice, she received a B.A. in Finance and Banking and a B.S. in Mathematics and Statistics at Peking University, and a M.A. in Economics at Duke University. Georgy Noarov is a rising third year PhD student in Computer and Information Science at the University of Pennsylvania, advised by Michael Kearns and Aaron Roth. Previously, he graduated from Princeton University with a B.A. in Mathematics. His research interests span across the fields of uncertainty quantification, online learning, fairness in machine learning, and algorithmic game theory.