Stanley Z. Hua

Stanley Z. Hua

PhD Student @ UC Berkeley & UCSF · Berkeley, USA

Hi! My name is Stan, and I want to create robust yet cautious machine learning systems that can meaningfully improve patient care, especially for those in under-served communities.

I care deeply about the usefulness of machine learning when deployed clinically. My current research interests revolve around algorithmic bias and methods to rigorously evaluate and monitor AI.

I also believe in slow science, which is not about time to completion but about the careful and meticulous art of advancing science.

Shoot me an email if you’d like to chat! And if you include the word “stupefy” in your email, I’ll know you read this :).

Currently
Reading on sequential hypothesis testing and changepoint detection, trying out ultimate frisbee, and thinking about creating a club.
Trustworthy ML for HealthAccessible Health Tech

News

Publications

Journal Conference Workshop
2026

Investigating Social Bias Changes in Quantized Large Language Models

Stanley Hua, Sanae Lotfi, Irene Y. Chen
COLM 2026ICLR 2026 Workshop on Trustworthy AI (Spotlight)
2026

Underrepresentation of children in public medical imaging datasets

Stanley Hua, Nicholas Heller, Stan He, Alex J. Towbin, Irene Y. Chen, Alex X. Lu, Lauren Erdman
Nature Health
2025

Longitudinal image-based prediction of surgical intervention in infants with hydronephrosis using deep learning: Is a single ultrasound enough?

Stanley Hua, Adree Khondker, ..., Mandy Rickard, Lauren Erdman
PLOS Digital Health (2025)SIPAIM (2022)
2024

Machine Learning-Enabled Renal Ultrasound View Labeling to Expand Use of Point-Of-Care Imaging in Community Settings

Stanley Hua, Lauren Erdman
Nature Conference on Precision Child Health
2023

Supervised Contrastive Learning for Improved View Labeling in Pediatric Renal Ultrasound Videos

Stanley Hua, Irene Y. Chen, Alex X. Lu, Lauren Erdman
20th IEEE International Symposium on Biomedical Imaging (ISBI)
2021

CytoImageNet: A large-scale pretraining dataset for bioimage transfer learning

Stanley Hua, Alex Lu, Alan Moses
NeurIPS Workshop on Learning Meaningful Representations of Life

Education

University of California, Berkeley
PhD. Computational Precision Health
2025 – 2030 (Expected)
University of California, San Francisco
PhD. Computational Precision Health
2025 – 2030 (Expected)
University of Toronto
B.Sc. Computer Science Specialist
2019 – 2024