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

Hi! My name is Stan, and I want to create machine learning models that generalize.

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 (Expected)
B.Sc. Computer Science Specialist, Statistics Minor



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)