I specialize in Retrieval-Augmented Generation (RAG), agentic AI systems, and fine-tuning large language models. I bring strong foundations in machine learning and NLP to build end-to-end systems from raw data pipelines to deployed, production-grade applications.
A selection of work spanning ML, NLP, and full-stack data applications.
Published work in AI and biomedical NLP.
End-to-end framework using GPT-4 and In-Context Learning to extract hierarchical Molecular Regulatory Pathways from biomedical literature. Constructed m6A-KG — a knowledge graph with 2.4K nodes and 4.7K edges. Designed G-Eval, an LLM-based annotation-free evaluation framework.
Introduces MetaphorPrompt, a novel approach using GPT-4 to generate metaphors that map biological processes onto real-world scenarios, improving extraction of molecular regulatory pathways from biomedical literature. Tested on the reguloGPT dataset; achieves improved precision, recall, and F1 scores in causal event link prediction via analogical reasoning and in-context learning.
Parth Patel, Yu-Chiao Chiu, Yufei Huang, Jianqiu Zhang
University of Texas at San Antonio
University of Texas at San Antonio
I'm open to research collaborations, full-time data science and ML engineering roles, and PhD internship opportunities. Feel free to reach out.