I am a NLP/ML researcher with a versatile background, bringing extensive expertise in machine learning, natural language processing, and computer vision. My profound passion centers around advancing foundation models in the realms of both NLP and computer vision, with a specific emphasis on Large Language Models (LLMs). Despite the incredible improvements in LLMs over the last few years, I believe they still face challenges that are yet to be solved, and I am excited about the opportunity to explore and contribute to advancements in this dynamic field.

Currently, I am actively collaborating with the UC Santa Barbara NLP Group, playing a significant role in the development of robust evaluation metrics for text-to-image (T2I) models. Our ongoing project, named "T2IScoreScore," specifically tackles the absence of comprehensive evaluation methods for assessing the faithfulness and consistency of T2I models. Our goal is to create a highly comprehensive evaluation framework to enhance the quality of these models.

I firmly believe that building AI models from scratch is an exceptionally effective method of learning. Therefore, I am interested in implementing AI models from scratch, as I am convinced that this hands-on approach fosters a profound understanding of the field. This philosophy motivates my consistent pursuit of opportunities to engage in collaborative research projects within these domains. If you're interested in working together or have any questions about my research, please feel free to get in touch!