Ph.D. Engineering Systems Science, University of California, San Diego
M.S./B.A. Physics , University of California, San Diego

Research

Dr. Kreutz-Delgado is interested in the development of sensor-based intelligent learning systems that can function in unstructured, nonstationary environments and has on-going research activities in the areas of statistical signal processing; statistical learning theory and pattern recognition; adaptive sensory-motor control; nonlinear dynamics and multibody systems theory. Before joining the faculty at UC San Diego, he was a researcher at the NASA Jet Propulsion Laboratory, California Institute of Technology, involved with the development of intelligent telerobotic systems for use in space exploration and satellite servicing and repair. His technical contributions in robotics include the development of a spatial operator algebra for the analysis and control of complex, multibody systems; the application of nonlinear dynamical reduction for robust sensory-motor control of multilimbed robotic systems; and the use of differential topology for the development of trainable nonlinear representations for sensory-motor control. Currently he is investigating learning sparse solutions for imaging inverse problems, particularly as applied to inferring cognitive function from various brain imaging modalities. He is also involved with research into the development of deep learning architectures combined with reinforcement learning as providing reasonable models of brain cognitive function for tasks such as situation and object recognition and sequential gaming.

Honors and Distinctions

• NSF Presidential Young Investigator Award (now know as Career Award)
• NASA Technology Achievement Award NASA Telerobotics Group Achievement Award for research in articulated body kinematics and dynamics for control of space telerobotic systems
• Senior Member of the IEEE
• Founding Associate Director, UCSD Program in Advanced Manufacturing

Last update: March 30, 2009