The goal of our research is to develop machine learning methods for real-world settings and use them to enable new discoveries in biology and medicine. We work towards inventing machine learning methods that are applicable to complex and heterogeneous real-world data and have the ability to generalize to novel scenarios that have never been encountered during model training. We apply our methods to solve cutting-edge problems in biomedical research.