"Text-to-Sticker: Style Tailoring Latent Diffusion Models for Human Expression" accepted at ECCV 2024
Paper on the text-to-image foundation model used in various Meta platforms.
Hey there!
I'm currently at Meta Fundamental AI Research (FAIR), working on using multi-modal LLMs to evaluate text-to-image models.
I'm also a PhD student at UT Austin, advised by Amy Zhang, and an NSF CSGrad4US Fellow.
My interests include controllability of generative AI and AI robustness via uncertainty quantification.
Previously I was an engineer at Meta working on various ML projects, including: Meta's first Generative AI product ( AI-generated stickers), uncertainty quantification in deep learning, and Bayesian modeling.
News & Updates:
Started PhD at University of Texas at Austin
Advised by Amy Zhang.
Joined the Generative AI Team at Meta
Joined the team that founded generative AI efforts at Meta. Working on text to image models and their product applications. The New York Times wrote about our team here.
Received NSF's CSGrad4US Graduate Fellowship
Provides funding for a PhD in the Computer and Information Sciences. I will be applying for PhD programs in the 2022 fall application cycle.
"Practical and Configurable Network Traffic Classification Using Probabilistic Machine Learning" published in Springer Nature's Cluster Computing 2021
My undergraduate thesis, PDF available here.
Joined the Probabilistic Neural Netowrks team at Facebook Research
Working on research and infrastructure for uncertainty quantification in deep learning.