About me
Hi! I am an undergraduate student studying Computer Science at the University of Washington's Paul Allen School for CSE, passionately pursuing a career in computer vision and artificial intelligence, with a focus on image and video generation. I am dedicated to contributing to the rapidly expanding field of generative AI, particularly in creating hyperrealistic images and cinematic-like videos. My approach emphasizes sourcing data from safe, ethical places, ensuring compliance with copyright restrictions. Through innovative research and development, I aim to advance the boundaries of what is possible in generative AI while maintaining a strong commitment to ethical practices. Additionally, I am focused on improving the quality of life for professionals in fields such as image and video editing by developing tools that streamline workflows, enhance creativity, and reduce manual effort.
Things I have worked on...
Machine Learning Analysis & Data Visualization
As an Machine Learning Research Intern in the University of Toronto's Department of Industrial and Mechanical Engineering, I investigated factors of depression that best predict the efficacy of antidepressant drug interventions. Performed data analysis and visualization for the ML models on clinical trial data, with the use of Scikit-Learn, Pandas, Matplotlib, and Seaborn under the guidance of Dr. Martin Katzmann and Prof. Lu Wang. Communicated progress effectively with stakeholders at the S.T.A.R.T. Clinic for Mood & Anxiety Disorders in Toronto.
LeetCode Helper Extension
Chrome extension that provides personalised feedback and allows users to optimise their solutions or receive assistance from a model towards deriving their solution.
Software Development & API Usage
Created a responsive, user-friendly website interface that tracks real-time AQI & offers tailored health recommendations using Weather, OpenAI,& AQI APIs.
Experimental Design & Research Publication
As a Undergraduate Research Assistant, Analyzed ML models which were trained with the GEMINI dataset to predict delirium in hospitalized patients and evaluated model stability over time under the guidance of Prof. Lu Wang. Primary developmental manuscript drafter and co-author for a tentative publication on the Journal of American Medical Informatics (JAMIA).
