About

I am a first-year PhD student at MIT CSAIL, where I am advised by Dr. Marzyeh Ghassemi. In my research, I am interested in methods to construct robust machine learning models that maintain their performance and fairness across unseen and out-of-distribution environments, as well as applications of such models in the healthcare domain. I previously completed my MSc at the University of Toronto under the co-supervision of Dr. Marzyeh Ghassemi and Dr. Quaid Morris.

Publications

Preprints

• A Comparison of Approaches to Improve Worst-Case Predictive Model Performance over Patient Subpopulations
  Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah
  [Paper] [Code]

• Reading Race: AI Recognises Patient's Racial Identity In Medical Images
  Imon Banerjee, Ananth Reddy Bhimireddy, [...], Zachary Zaiman, Haoran Zhang, Judy W Gichoya
  [Paper] [Code]

• Self-Supervised Contrastive Learning of Protein Representations By Mutual Information Maximization
  Amy Lu, Haoran Zhang, Marzyeh Ghassemi, Alan Moses
  [Paper] [Code]

2021

• Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing
  Sindhu C.M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi
  Conference on Information and Knowledge Management (CIKM) 2021
  [Paper] [Code]

• An Empirical Framework for Domain Generalization in Clinical Settings
  Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi
  ACM Conference on Health, Inference, and Learning (CHIL) 2021
  [Paper] [Code]

2020

• An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare
  Taylor Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi
  Machine Learning for Health Workshop at NeurIPS 2020 (Proceedings Track)
  [Paper] [Code]

• Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings
  Haoran Zhang*, Amy Lu*, Mohamed Abdalla, Matthew McDermott, Marzyeh Ghassemi
  ACM Conference on Health, Inference, and Learning (CHIL) 2020
  [Paper] [Code] [Poster]

• Identifying Transitional High Cost Users from Unstructured Patient Profiles Written by Primary Care Physicians
  Haoran Zhang, Elisa Candido, Andrew S. Wilton, Raquel Duchen, Liisa Jaakkimainen, Walter Wodchis, Quaid Morris
  Pacific Symposium on Biocomputing (PSB) 2020
  [Paper] [Poster]