Dr Molteni's interests lie at the intersection of machine learning and coma science. Her research focuses on the development of methods for effective use of neuroimaging and polysomnography in monitoring the restructuring of consciousness, sleep, and circadian rhythms at the exit from a coma after acquired brain injury. She applies statistical and machine and deep learning methods for the prediction of outcome over the continuum of care after the intensive care unit, and particularly for pediatric patients.

She is also contributing to the Deloneliness project, aiming to find advanced machine learning and sensing solutions in home care and health, to target loneliness within the aging population.