CV

Master's

Carnegie Mellon University

Master of Intelligent Information Systems (MIIS)

• Advanced Natural Language Processing (Grade TBD)
• Introduction to Question Answering (Grade TBD)
• Independent Study in Language Technologies (Grade TBD)
• Directed Study in Language Technologies (Grade TBD)

Bachelor's

University of Southern California

Computer Science and Applied & Computational Mathematics

• Language Models in Natural Language Processing (A)
• Applied Machine Learning for Natural Language Processing (A)
• Applications of Machine Learning (A)
• Applied Neural Networks (A)
• Introduction to Artificial Intelligence (A)
• Capstone: Design and Construction of Large Software Systems (A)
• Software Engineering (A)
• Mathematical Statistics (A)
• Probability Theory (A)
• Linear Algebra and Differential Equations (A)
• Numerical Methods (A)
• Data Structure and Object-Oriented Design (A)
• Introduction to Algorithms and the Theory of Computing (A-)

Believing without Seeing: Quality Scores for Contextualizing Vision-Language Model Explanations

Submitted to NeurIPS 2025

We introduce Visual Fidelity and Contrastiveness -- two explanation quality scores that help users more appropriately rely on vision-language model predictions without seeing the image.

ELI-Why: Evaluating the Pedagogical Utility of LLM Explanations

Findings of ACL 2025

Evaluate the pedagogical utility of LLMs in tailoring explanations to users with different educational backgrounds.

Attributing Culture-Conditioned Generations to Pretraining Corpora

ICLR 2025

This paper introduces MEMOed, a framework to analyze whether AI generations are driven by memorization or generalization, with a focus on cultural symbols.

Enhancing Debugging Skills of LLMs with Prompt Engineering

Technical Report

Study on improving LLM debugging through prompt engineering techniques. Evaluated few-shot learning and chain-of-thought approaches on GPT-3.5, revealing limitations in current debugging capabilities.

LLM Prompt Recovery

Developed a system to recover user prompts using fine-tuned Mixtral models, achieving top 3.4% in a Kaggle competition.

• Achieved a score of 0.65 using sentence-T5-base and sharpened cosine similarity.
• Ranked 75/2175 globally in the Kaggle competition.
• Published fine-tuned model on Kaggle for broader access.

AI-Based Career Advisor

Built an AI tool to assist users in planning career paths based on skills and interests.

• Developed a Streamlit-based interactive UI integrating GPT-4o for job suggestions.
• Implemented cosine similarity search for skill-job matching.
• Integrated Bing AI for real-time job application link retrieval.

Enhancing Debugging Skills of LLMs with Prompt Engineering

Improved LLM debugging capabilities through advanced prompt engineering techniques.

• Experimented with various prompting strategies to enhance debugging efficiency.
• Achieved significant improvements in LLM performance on debugging tasks.

Automated Hate Speech Detection in Social Media

Developed an advanced ML model for detecting hate speech, achieving 94% accuracy.

• Fine-tuned BERT for classification tasks.
• Enhanced online safety and inclusivity through robust model optimization.

Silver Medal, Kaggle Competition

Ranked 75/2175 (Top 3.4%) on the global leaderboard, LLM Prompt Recovery Project.

USC Academic Achievement Award

Awarded in Fall 2022, Spring 2023, Spring 2024, and Fall 2024. Covered 11 units of tuition costs in total, amounting to approximately $24,000.

4th Place, USC Integral Bee Competition

Ranked 4th in the USC Integral Bee Competition.

1st Prize, International Linguistics Olympiad

Senior Level, Individual Open Round, China.

1st Prize, International Linguistics Olympiad

Senior Level, Team Open Round, China.