Other work establishes lower bounds on the complexity of models of computation, including boolean circuits, communication complexity, and length of proofs. The work is partly practical, but mostly fundamental, because it deals with the inherent complexity of classes of computational problems. Finding methods that allow a deterministic process to simulate randomness, and using randomness for solving computational problems, including computer communication applications, and protecting privacy in information exchange over computer networks. Current research includes the synthesis of reactive modules, automatic verification of multi-process systems, and specification methods that combine transition systems with temporal logic. Research on languages for the modeling and simulation of complex reactive systems.
Work focuses on visual formalisms, based on topological and geometric constructs.
Work in this area includes the design of efficient communication patterns and efficient transmission of information between sites in a network. Recent work also include the study of parabolic resonance, and the explanation of weather balloon drift in the atmosphere by parabolic resonance. Investigating the rules that govern skill acquisition and learning in humans, and developing learning algorithms and architectures for robotic systems. In collaboration with neurologists we investigate and characterize the motor impairments manifested in Parkinson's disease. Solving the mathematical equations that describe natural phenomena in physics, chemistry, and other branches of science, is often a formidable computation task.