Dr. Nicolas Schweighofer co-founded Computational Neurorehabilitation, an emerging field at the intersection of Neurorehabilitation, Computational Neuroscience, Motor Control and Learning, and Artificial Intelligence (AI). The overarching goals of Computational Neurorehabilitation are to understand and to further improve motor recovery following neurologic injury by mathematically modeling and simulating the neural processes underlying the change in behavior due to rehabilitation. In his current research, he is investigating how predictive models of recovery, informed by the neuroscience of stroke recovery and motor learning, as well as large datasets, can provide the basis for AI methods that suggest timing, dosage, and content of rehabilitation. Such an approach will transform neurorehabilitation by guiding clinicians, patients, and health providers in the optimization of treatments via precision rehabilitation.