People / Students / Class of 2026
Jiarui received his bachelor's degrees in Data Science and Business Analytics from the University of Rochester in May 2023. During his undergraduate studies, he built a strong foundation in core data science principles and developed hands-on experience in areas such as data mining, machine learning, time series analysis, and natural language processing. He is proficient in Python and SQL and brings a practical, analytical mindset to solving complex problems. For his Capstone project at the University of Rochester, his group developed a pairs trading algorithm for equities. During the project, he led the pair identification component of the algorithm, leveraging unsupervised learning techniques such as OPTICS clustering and statistical measurements including cointegration test and Hurst exponent to identify optimal stock pair candidates. His contributions helped the trading strategy achieve performance that exceeded the S&P 500 benchmark during backtesting. Beyond coursework, he also actively participated in research projects. Working as a Data Science Research Assistant at the University of Rochester Medical Center, he applied NLP techniques such as sentiment analysis and topic modeling to X (formerly Twitter) dataset to extract public perceptions of smokeless tobacco products. On a separate project, he analyzed the influence of specific tobacco marketing elements in Instagram posts on user engagement metrics using statistical methods including negative binomial model and hypothesis testing. Both studies yielded insights on the product strategy and market positioning of tobacco products and were published in the peer-reviewed Journal of Medical Internet Research (JMIR).
After graduating from the University of Rochester, Jiarui joined Amazon Web Services (AWS) as an Enterprise Account Engineer. At AWS, he worked with both external clients and internal stakeholders. Externally, he led cloud cost and usage analysis for enterprise clients, helping them to identify actionable recommendations which resulted in cost optimization and reinvestment into the cloud usage. He also contributed to the Analytics Technical Field Community as a QuickSight specialist, designing tailored analytics solutions to meet diverse client needs. Internally, he led a project to build a data pipeline and dashboard with AWS Glue and QuickSight that visualized client engagement lifecycle metrics—enhancing internal visibility and reducing delivery delays by ~10%.
Jiarui is excited to join the Machine Learning and Data Science program at Northwestern University, where he looks forward to deepening his expertise in areas such as deep learning and generative AI. He is particularly drawn to the program’s emphasis on real-world application through the practicum and capstone projects. By building both technical depth and practical experience, Jiarui hopes to be well-prepared to pursue a career as a data scientist.
