About

I am an undergraduate studying Computer Science and Mathematics at Cornell University.

I have interned at Moloco this summer as a machine learning engineer, exploring the important use cases of deep learning in the ads industry. My tasks focused on leveraging MLSys techniques (ensemble learning & knowledge distillation) to improve the company’s core bidding model, while at the same time lowering its cost after being deployed.

I conduct research with Cornell University Artificial Intelligence on enhancing vision-language (VLP). We’ve proposed Distribution Normalization, a state-of-the-art augmentation to vision-language models (such as OpenAI CLIP) at inference. Additionally, I volunteer as an ML developer for arXiv, where I contribute to large-scale dataset construction and model fine-tuning.

Besides ML engineer, I’m a food & cooking enthusiast, classical pianist 🎹, and long-distance runner 🏃!