Kshitiz Pokhrel

Kshitiz is a research associate specializing in statistical analysis, machine learning (ML), and natural language processing (NLP). His journey began with a Bachelor's degree in Mathematics and Statistics from Mississippi State University, where he developed strong analytical foundations, followed by a Master's in Data Science from the University of Guelph, where he focused on applied ML and NLP. Kshitiz has gained extensive experience with large language models (LLMs), adapting them effectively across various domains through fine-tuning in projects involving sentiment analysis and conversational modeling. He specializes in both comprehensive training approaches and resource-efficient fine-tuning techniques that enable practical and scalable implementation of LLMs in diverse applications. Additionally, he has designed and implemented retrieval-augmented generation (RAG) systems that enhance AI's capability to deliver accurate, contextually relevant responses by integrating external knowledge sources.

Kshitiz is dedicated to advancing machine learning and natural language processing technologies through innovative research and practical application. He continually explores new methods to enhance model performance, reliability, and efficiency, with a focus on real-world usability and impact. His work seeks to bridge the gap between cutting-edge computational techniques and their effective deployment across diverse, socially relevant contexts.