People / Students / Class of 2023
Rena Zhang earned her bachelor of science degree from the University of North Carolina at Chapel Hill in 2022 with a double major in Statistics and Analytics and Computer Science and a minor in Data Science. At UNC, Rena dedicated herself to learning analytical knowledge and solving real-world problems with it. Her undergraduate curriculum was both diverse and question-driven, which includes Introduction to Data Models & Inference, Methods of Data Analysis, Discrete Mathematics, Data Structures, Introduction to Probability, Machine Learning, Stochastic Modeling, Algorithms & Analysis, Programming Language Concept and Connecting Language to Vision and Robotics. Coming from a less developed region of China, Rena had a clear goal of changing the world with better, smarter, and more accessible education, and the strong quantitative background she acquired during her undergraduate life empowered her to do so. During her sophomore year, she co-founded Xueyuanpai Academia, one of the most influential online higher learning video creators that has 820,000 students and partners with Bilibili, as the Chief Technology Officer with another student in UNC. Inside the Academia, she mainly used xxx technology to help scholars and professors the Academia works with to understand once mysterious behavior patterns of online viewers and learners and perfect their course design, teaching models, and pedagogical methodologies. The NLP model Rena used to develop a set of algorithms to predict the likes and dislikes of students with the visualization to show the scholars how audiences responded and could respond to different contents during the COVID Pandemic revolutionizes the way Academia works and university-level knowledge translates to common viewers in online video settings, which clearly reflects on the high growth of Academia at the time. Besides this main aspiration, Rena also works in various internships at Google and Microsoft and with a professor at Columbia University. In Microsoft, she independently completed four side projects to facilitate course development for the Training Program. At Google, she focused on the data analysis and application of vending machine business which includes data visualization, statistics modeling, and sales prediction. Working with Dr. Houlihan in Columbia, she and her teammates performed game comment classification and sentiment analysis with three machine learning models and published the paper Compare Machine Learning Models in Text Classification using Steam User Reviews in the Conference Proceedings of ACM. Besides, in her graduate-level course Connecting Language to Vision and Robotics, she reproduced the paper Bottom-up and top-down attention for image captioning and visual question answering by Anderson et al. (CVPR 2018) using Faster R-CNN to build a captioning model and conducted a ‘soft’ top-down attention mechanism with two LSTM layers. All these works reflected the cohesive ambition of Rena to understand how the next-generation ecosystem of mankind, the AI and algorithm-based online information system, actually works and can be improved for human’s own benefit. With such ambition in mind, in the MSiA* program at Northwestern Univerisity, Rena seeks to further enhance her theoretical understanding of statistics and data science. She will still dedicate herself to the cutting-edge application of data science technology for educational purposes and humanistic causes, as well as being eager to participate in more comprehensive and complicated works at various tech giants like Google and Microsoft could provide to further her understanding of the bigger system. She is excited to learn and understand data science as a meta-science of the 21st century and be well prepared for where this amazing journey could take her.
*later renamed MS in Machine Learning and Data Science
