We are an interdisciplinary group of neuroscientists and computer scientists seeking to understand the human brain, improve mental health and treat mental disorders. There is a deluge of data across many scientific disciplines. Future scientific breakthroughs will rely on algorithms to explore these massive data. Our group develops and applies machine learning algorithms to generate neuroscientific discoveries from large-scale datasets comprising thousands of subjects with brain MRI, behavioral, genetic and other physiological measures. For example, we have estimated high-quality functional brain atlases, which are widely used around the world to study healthy brain network organization and mental disorders. We have also developed machine learning techniques to predict Alzheimer’s Disease progression, as well as uncover transdiagnostic mental disorder subtypes. Finally, we are one of the first groups to develop machine learning techniques to “invert” biophysical neural networks, yielding new insights into healthy brain organization and development.