CV

AI Research Intern

ATLAS - AI Exploration Team, University of Illinois Urbana-Champaign

• Architecting a Retrieval-Augmented Generation (RAG) prototype to function as an academic advising assistant agent, designed to automate responses to logistical student inquiries using Python.
• Engineering a vector database pipeline to ingest and index unstructured administrative data (PDF handbooks, FAQs), enabling high-precision semantic search for complex degree requirements.
• Implementing robust prompt engineering and quantitative evaluation metrics to minimize hallucinations, benchmarking the model’s accuracy and citation relevance against human advisor standards.

Course Assistant

Department of Statistics, University of Illinois Urbana-Champaign

• Supported instruction in an introductory statistics and data science course with 400+ students through labs, grading, and weekly office hours.
• Collaborated with instructors to enhance grading consistency and lab design.
• Guided students in Python-based data analysis (hypothesis testing, logistic regression, regularization, and machine learning).

Research Assistant

Professor Hui Liu's Research Team, Zhejiang University

• Analyzed unstructured human-AI interaction logs using Python and TF-IDF vectorization to transform sequential dialogue into high-dimensional feature sets.
• Identified distinct learner behavioral archetypes by implementing Hierarchical Clustering, uncovering latent patterns in how users transition between clarification and uptake.
• Engineered over 500 N-gram features and built a Random Forest classifier to predict performance, achieving statistical rigor through Leave-One-Out Cross-Validation (LOOCV) for small-sample optimization.
• Validated predictive behavioral sequences (e.g., Clarify Standards -> Partial Uptake) using Permutation Tests (p<0.01) to ensure the significance of feature importance.

Community Leadership and Marketing Intern

Glocal

• Supported the University Pilot Program across multiple institutions, including Priestley College (UK), by coordinating feedback and go-to-market (GTM) strategies.
• Helped train an internal AI agent using pilot data to improve prediction accuracy and decision support.
• Promoted educational equity through cross-campus engagement and data-driven outreach.

Bachelor of Science & Bachelor of Arts

University of Illinois, Urbana-Champaign

Statistics & Sociology

• Machine Learning, R Programming, Python, Java, C++, Calculus, Discrete Structures, Statistics and Probability, Data Analysis, Data Visualization, Data Management, Social Research Methods
• Minor: Computer Science & Data Science

The discerning principal: What prompting-uptake behaviors characterize high performers in human-AI collaboration?

Computers & Education. (Under Review)

Intelligence Amplification: Cultivating Deep Thinking in the AI Era.

Shanghai Education: Global Education, Issue 35, pp. 56-61.