People / Students / Class of 2026
Keming Zhang graduated from the University of Rochester in May. 2025, majoring in Data Science & Business Analytics with a minor in Statistics. She currently a graduate student in Machine Learning and Data Science (DSML) program at Northwestern University. She is actively engaged in advancing her knowledge and skills in this field. Her academic journey has provided her with a robust foundation in data science principles and techniques, including extensive coursework and hands-on projects that have honed her ability to analyze complex data sets and derive meaningful insights.
Keming’s research experience demonstrates her technical capabilities and passion for innovative applications of data science. She customized and fine-tuned large language models (LLMs), implemented Retrieval-Augmented Generation (RAG) techniques using ChatGPT, Cohere, and DeepSeek APIs to simulate Abrahamic scholars responding to questions derived from the World Value Survey. She further applied principal component analysis (PCA) to assess the model outputs and contributed to an academic publication. In another research project, she implemented time series forecasting models for the S&P 500 index, engineered key features, and built interactive dashboards to communicate results.
Her industry experience includes an internship at China Unicom, where she applied in-class knowledge to the real-world scenario. She cleaned and preprocessed the customer call data, refined NLP models to forecast customer subscription renewal, and finally achieved 81.2 accuracy on the test set. What’s more, Her independent internship with ACT Rochester demonstrated her ability to distill complex data into actionable insights for civic and government stakeholders. She collected and prepared the data, performed descriptive analysis with Python and SQL, then produced more than 140 visualizations using various data visualization tools, like Tableau, Excel, and Arcgis, which culminated to accessible, decision-oriented reports for the community. She is particularly drawn to data scientist or data analyst position, and she is eager to continuously learning and bring her skills and experiences to the workplace.
