My Experience

Research Projects

Multi-agent LLM System for Research Evaluation

Multi-agent LLM System for Research Evaluation

2024 - Present

Developing a collaborative AI system where multiple language models work together to identify weaknesses in research papers, generate critiques, and suggest improvements.

Technologies:

GPT-4LlamaClaudeAgentScience
iTox: Deep Learning for Pneumonitis Prediction

iTox: Deep Learning for Pneumonitis Prediction

2023 - 2024

Created a CNN-RNN model to predict radiation-induced pneumonitis risk from CT scans, achieving an AUC of 0.84. Developed Grad-CAM visualization tools to increase model interpretability.

Technologies:

CNNRNNGrad-CAMRadiologyMedical ImagingPneumonitisLung Cancer
VR Surgical Training System

VR Surgical Training System

2022

Built a virtual reality system for surgical training using Unity and C#, incorporating surgical video analysis and eye-tracking technologies to optimize training effectiveness.

Technologies:

UnityC#U-NetComputer VisionEye-tracking

Work Experience

Researcher - LLM Multi-Agent Systems

Sep. 2024 – Present

Pennsylvania State University

University Park, PA

  • Developed a multi-agent LLM system designed to identify weaknesses in research papers across NLP, computer vision, and medical AI domains.
  • Implemented a pipeline where multiple autonomous AI agents interact, critique, and generate counterarguments to refine research quality.
  • Integrated GPT-4, Llama, and Claude models to simulate peer review processes and enhance research reproducibility.

Teaching Assistant, Department of Computer Science

Sep. 2024 – Present

Pennsylvania State University

University Park, PA

  • Led recitations for CMPSC/DS 442 Artificial Intelligence courses, assisting 100+ students with AI models and Python implementations.
  • Designed and led homeword on open-source LLMs with reinforcement learning; guided students in understanding fine-tuning concepts through hands-on application of Group Relative Policy Optimization (GRPO) using DeepSeek R1.

AI Specialist

May 2024 – Aug. 2024

High Fashion Group

Hong Kong

  • Developed a fabric image recognition system using Siamese networks for pattern matching and quality control.
  • Built a text-based fabric search engine powered by LLMs to improve semantic retrieval across the product database.
  • Consolidated company-wide product and cost data to support a Retrieval-Augmented Generation (RAG) system that enables fashion trend forecasting and cost-performance analysis for internal teams and partner colleges.

Researcher

Jul. 2023 – May. 2024

Northwestern University Medical School

Chicago, IL

  • Designed iTox, a CNN-RNN deep learning model predicting pneumonitis risk from CT scans (AUC: 0.84).
  • Developed Grad-CAM-based visualization tools to identify lung regions most predictive of pneumonitis.
  • Proposed a novel iTox metric to guide radiation dose recommendations, reducing pneumonitis risk by 20%.