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/video/3D generation. I am dedicated to contributing to the rapidly evolving field of generative AI, driven by how the breakthroughs of 2020 reshaped not only the way I work but also how I think. Seeing AI enable ideas to be explored 10x faster made me intensely curious about how these systems function and how to make them safer, more reliable, and more aligned with human values and needs.
I'm currently the most curious about vision-language models, image editing, fine-tuning foundation models, and model evaluation. As I continue exploring this space, my goal is to help shape AI systems that empower people by being trustworthy, intuitive, and creative. I'm excited to keep pushing the boundaries of what these models can do while contributing to a future where AI is a force for good.
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.
AI is the new electricity. Just as electricity transformed almost everything 100 years ago, today I actually have a hard time thinking of an industry that I don't think AI will transform in the next several years.