Faculty Members

Perception for autonomous robotic manipulation and grasping; developing methods that are goal-directed, real-time and multi-modal such that they can provide meaningful feedback for execution and learning.

Nanoscale electronic and photonic materials and devices. Guiding and manipulation of light in metal-optic structures. - Optical properties of semiconductor nanocrystals. - Optical sensors for bio-applications.

Compressive sensing, mathematical signal processing, computational harmonic analysis, statistics, scientific computing

Functional circuitry of the primate retina and design of retinal prosthesis.

Theoretical and computational statistics, signal processing and harmonic analysis. Applications include methods for the construction of low-dimensional representations for high-dimensional data problems (multiscale geometric analysis), developments of wavelets for denoising and compressed sensing.

Network information theory, Field Programmable Gate Array, and digital imaging devices and systems.

Computational fluid dynamics and solid mechanics, computer graphics, computer vision and computational biomechanics

Communication of digital images, including compression and transmission of video over the Internet, digital watermarking to protect intellectual property, 3-D image analysis and synthesis, and architecture of multimedia systems.

Fourier Optics, Statistical Optics and the study of speckle. Prof. Goodman and Prof. Wandell initiated the Image Systems Engineering Program at Stanford in 1996.

Computational geometry, geometric modeling, computer graphics, computer vision, robotics, ad hoc communication and sensor networks, biocomputation, and discrete algorithms.

Rendering algorithms, high performance graphics architectures, and systems support for graphical interaction; raster graphics systems, computer animation and modeling and scientific visualization, in particular, volume rendering.

Multiprocessor design, graphics IO, and high-speed electrical and photonic links, and circuit issues in scaled technology; EE analysis methods to biological systems.

Brain function, development and repair with emphasis on 1) regeneration to prevent and cure blindness, and 2) neural circuits that control visual fear and anxiety

Research Interests: Computer graphics, computer sound, physically based modeling and animation, and reduced-order physics models.

Human Computer Interaction, Haptics, and Human Robot Interaction exploring the design of novel tactile physical interfaces and novel robotic devices.

Computer vision and human vision, with emphasis on object recognition, scene categorization and understanding, human motion recognition, material recognition, etc.

Artificial Intelligence, Machine learning, Unsupervised feature learning and Deep learning, Neuroscience-informed AI.

High-performance visual computing systems that enable immersive and intelligent visual computing applications.

New acquisition and processing techniques for improved medical imaging.

Interaction between visual experience and the structure and function of the brain using a combination of direct, but non-invasive measures of the brain's electrical activity along with psychophysics to study how the brain processes visual images.

Haptics, teleoperation, virtual environments and simulators, medical robotics, neuromechanics and rehabilitation, prosthetics, and engineering education.

Efficient sampling and reconstruction techniques for discrete signals Geometry and combinatorics for families of higher dimensional Bezier curves Analysis and geometry of two-dimensional harmonic maps and their lifts to minimal surfaces.

Interaction of electric field and light with biological cells and tissues, and their applications to medicine and biology.

Medical imaging, and magnetic resonance imaging (MRI) in particular, Image reconstruction algorithms, Cardiac imaging, Image guided minimally invasive therapies.

Research interests include computer vision, robotic perception and machine learning.

Image system engineering and visual neuroscience Prof. Wandell and Prof. Goodman initiated the Image Systems Engineering Program at Stanford in 1996.

Information theory and its applications to data compression and communications, and statistical signal processing.

Computational imaging and display systems, as well as computational light transport.

Neuroscience, artificial intelligence, psychology and large-scale data analysis.

Spaceborne radar systems and the application of remote sensing data to problems in geophysics. His current emphasis is on interferometric radar for topographic and surface deformation studies of earthquakes, volcanoes, and global environmental problems.