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Class of 2021

Photo of Qiaozhen Wu

Qiaozhen first became interested in data science as a comparative-literature-majoring freshman at a machine learning panel hosted by the CS department. During the panel, a professor presented on her research that predicted voters’ political inclinations through twitter posts. The perspective of data science seemed to yield convincing and powerful interpretations on social and political issues.

To better arm herself with statistics, she built a crime tracker that informs users of the probability of crimes according to their locations in the LA hacks hackathon. The model used a clustering model to divide the data into three levels of crimes using levels of charges and punishments. Looking for internships that bring exposure to different data analytical tools. Her interest in media and journalism enabled her to learn about data analysis in business and corporate environment. She participated in a meeting of the LA Times data science section. This experience of using data analysis and media presentation to raise public awareness in immigrant injustice inspired her to pursue a market analyst internship at a technology media company after sophomore year. For the annual tech conference, she gathered customer information from the past five years and used machine learning model to predict what types of articles would best advertise conference and looked for correlations between readers and products. She later seek for opportunities in data science in research in Zarlab led by professor Eleazar Eskin at UCLA. Qiaozhen helped with data processing in projects such as predicting patient’s returning rate in a hospital after discharge. She participated intensely in a project that evaluated and compared the efficiency of popular error-correction softwares for genome datasets and eventually contributed as the fourth author of our paper published in Genome Biology. This experience solidified her interest in data science research and its application in industrial settings.

Qiaozhen plans on combining her interests in quantitive analysis and cultural studies into computational social science and media studies. After graduation, she plans on pursuing a career as a data scientist in the media industry or conducting social science research in the fields of media studies and public policy. Qiaozhen wish to gain deeper insight in social and cultural problems through data, and help optimize policies through these understanding.