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Hao Liang

Graduate StudentEmail Hao Liang

Hao Liang graduated from the University of Wisconsin-Madison in December 2021 with a double major in Statistics and Economics. During his undergraduate study, he developed a data-oriented mindset through rigorous courses and various hands-on projects. Hao also worked as a research assistant under Prof. Michael Hernke on topics related to sustainability science. His primary task was to adopt quantitative analysis to evaluate the Ecological Footprint of electric vehicles by developing models to detect variations in CO2 emissions. Additionally, during the research project with Prof. Margie Rosenberg associating the Great Recession with food insecurity, Hao utilized the survey-weighted method in R to handle unparalleled datasets and relied on the difference-in-differences method to analyze oral health conditions. These research experiences allowed him to experience the complete data analysis workflow and strengthen his determination to address real-world issues using data science methodology. To explore broad and diverse applications of data analytics across industries, Hao started an internship at Minsheng Securities, whose primary task was analyzing A-share market performance by running time-series regression on private placement data. He also collaborated with colleagues to advise clients on financial decisions by predicting their anticipated returns and potential risks. In addition, during the internship at Refinitiv, Hao wrote Python scripts to extract meaningful messages from Eikon data and relied on advanced Excel functions to develop a comprehensive carbon-industry database. In a group project where the complexity of the code base caused unexpected challenges, he took the initiative of refactoring the code to make it more manageable while integrating new R packages. These enlightening internships honed his creativity and collaboration skills. Both research and internship experiences helped improve his critical thinking ability in data analytics and cultivated the skills of incorporating data science techniques in solving complicated real-world problems. By joining the MSiA* program at Northwestern, Hao Liang aims to become an aspiring data scientist who hopes to integrate the frontiers of data science with optimal business practices.

*later renamed MS in Machine Learning and Data Science