I received my PhD in Cognitive Science in 2001 from the University of California, San Diego and did my Post-Doctoral training in electrophysiology at CALTECH. I have been on the faculty at Rutgers since 2008. My research combines theory and experiments to study how primates plan, execute, learn and adapt to natural voluntary motions. Clinical application is an integral part of my research effort. I study stroke patients, Parkinson’s patients and derive general indexes of performance that emerge from geometric and topological relations between extra-personal and internal representations of the primate brain. My clinical research has shown that these indexes are under cognitive control. They consequently facilitate the measurements and the diagnosis of specific sensory-motor deficits, the identification of their source and the design of therapies to improve motor learning and performance in activities of every-day life.

Recently I am extending these computational measures of sensory-motor performance in adults to the developmental stages of pre-pubertal individuals. In particular my laboratory will assess a broad range of natural voluntary behaviors in children who suffer from autism and other developmental disabilities. The main goal of this component of my research is to provide early intervention therapies to improve communication skills and social interactions in these young individuals.

Because research from my laboratory must have translational value I focus on natural (unconstrained) movements. I aim for scalable algorithms and general computational principles that remain conserved independently of the form in which the data was originally collected. This approach has stimulated various collaborative efforts and facilitated independent assessments of movement and neural data collected by other research groups. In this regard I will further develop the theoretical component of my research on motor learning, motor adaptation and motor planning of natural movements in a collaborative effort that includes electrophysiology, computer science and behavioral experiments involving both normal subjects and subjects with a compromised system. The main objective of this interdisciplinary collaborative effort is to identify general principles and laws of mental operations required in voluntary behavior that generate testable predictions at different levels of abstraction.