Hi, I’m Shaoyi Zheng, currently a Ph.D. student in Computer Science at the Courant Institute of Mathematical Sciences, New York University, where I am advised by Prof. Shengjie Wang. I completed my undergraduate studies at NYU Shanghai, majoring in Computer Science with a minor in Mathematics.

My research interests broadly lie in Efficient AI and generative models, focusing on model architectural design and algorithmic acceleration.

Efficiency in Generative Models

Generative models such as diffusion models and large language models have achieved remarkable capabilities, but their ever-growing scale and input size lead to significant efficiency bottlenecks. My research focuses on algorithmic improvements and architectural innovations to accelerate these models without sacrificing quality. I explore methods such as sparsity, efficient model designs together with kernel optimization to reduce latency and memory usage. My broader vision is to make powerful generative models more accessible and affordable, enabling their deployment in real-world scenarios.