Stanley Z. Hua
Data Enthusiast, Toronto, Ontario, CA

Hi! My name is Stan, and I want to create machine learning models for healthcare that generalize and improve patient care.

I am particularly interested in methods that improve generalization when labeled data is scarce and noisy. In the past, I’ve explored:

  1. Large domain-specific pre-training datasets for transfer learning with microscopy images
  2. Supervised contrastive pre-training to improve generalization of ultrasound video models across hospitals
  3. Large language models for automated soft-labeling of domain-specific text with prompt engineering

I am also a believer of slow science when possible.

Shoot me an email if you’d like to chat! And do include the word “stupefy” in your email.


  • Robust Machine Learning
  • Transfer Learning
  • Self-Supervised Learning


University of Toronto
2019 - 2024
B.Sc. Computer Science Specialist



Supervised Contrastive Learning for Improved View Labeling in Pediatric Renal Ultrasound Videos, 2023, 20th IEEE International Symposium on Biomedical Imaging (ISBI)
Stanley Hua , Irene Y. Chen , Alex X. Lu , Lauren Erdman
From Single-Visit to Multi-Visit Image-Based Models: Single-Visit Models are Enough to Predict Obstructive Hydronephrosis, 2022, 18th International Symposium on Medical Information Processing and Analysis (SIPAIM)
Stanley Hua , ... , Anna Goldenberg , Lauren Erdman
CytoImageNet: A large-scale pretraining dataset for bioimage transfer learning, 2021, NeurIPS Workshop on Learning Meaningful Representations of Life
Stanley Hua , Alex Lu , Alan Moses


Includes research projects, passion projects and hackathons.
[Passion Project] Alexandria: An AI Book Maker using ChatGPT
[Research] The Effect of PCA Dimensionality on K-Means Clustering of Medical Images (under small sample sizes)