Hossein Azizpour

Azizpour group’s machine learning research can help life science applications by making data-driven models more effective, reliable and explainable. The current directions include (i) “interpretable modeling” and “uncertainty estimation” to improve trustworthiness, (2) “under-supervised learning”, “feature selection”, and “knowledge transfer” to handle imperfect and/or low data, and (3) “generative modeling” for robust predictive modeling, design tasks, and understanding biological mechanisms.