Faculty Directory

Duraiswami, Ramani

Duraiswami, Ramani

Professor
Computer Science
UMIACS
Electrical and Computer Engineering
Brain and Behavior Institute
3361 A.V. Williams Building
Website(s):

Perceptual Interfaces are concerned with extending human computer interaction to use all modalities of human perception. Our current research efforts are focused at including vision, audition, and touch in the process. The goal of perceptual reality is to create virtual and augmented versions of the world, that are perceptually identical to the human with the real world. The goal of creating perceptual user interfaces is to allow humans to have natural means of interacting with computers, appliances and devices using voice, sounds, gestures, and touch. In both creating virtual reality, and in acquiring multimodal input from humans, our research emphasizes physics-based algorithms, efficient computation, and real-time implementations.

 Another portion of our research is concerned with creating prosthetic devices for the vision and hearing impaired, by mapping inputs from one modality into equivalent ones in another, so that computationally augmented input streams can be created with extra content from the missing modality.

EDUCATION

Ph.D., Johns Hopkins University, 1991

B.Tech., IIT Bombay, 1985

Audio and Computational Acoustics:

Acoustics for perceptual reality:  Head Related Transfer Functions,  Room Impulse Responses, Auditory Telepresence, Reproduction of audio using headphones, Reproduction using speakers. Keynote talk at Ambisonics 2010

Microphone Arrays: Beamforming, Source Localization, Source Modeling, Spherical Microphone Arrays, Cameras and Arrays, The Audio Camera, Non-blind algorithms

Speech: Speaker ID, Large Scale Computing for Speech Processing

Auditory User Interfaces: Sonification of Data, Systems for presentation, Audio in Games

Underwater acoustics: Bubble counting, sound propagation in bubbly media and fog

Scientific and Statistical Computing:

Fast Multipole Methods: Data Structures; Adaptive Algorithms; FMM for the Laplace, Helmholtz, Biharmonic, Maxwell and Stokes kernels; General kernels; Scattering problems

High Performance Computing: GPU and Heterogeneous Parallel Computing

Computational Statistics and Learning Methods: Improved Fast Gauss Transform in high dimensions; Mean-Shift; Particle Filters; "Fast N-Body Learning"; Classification, Ranking, Gaussian Processes, Speaker ID.

Data Fitting and Modeling: RBF interpolation; Data Structures for higher dimensional data; Non Uniform Fast Fourier Transforms, Data Assimilation; Gaussian Process Regression

Boundary Element Methods: Speedup via the FMM; Computation of singular and near singular integrals; Meshless Methods; Software.

Small Angle Scattering: Small Angle X-ray and Neutron scattering, fast algorithms

Other (older stuff): Electrical Impedance Tomography; Bubble Dynamics; Free surface flow; Spectral Methods; Effective Media; Inverse problems.

Computer Vision:

Vision aware audio; Tracking; Pose; Kernel methods, Vision based prosthetics for the visually impaired, application of fast algorithms to computer vision and image processing, The Audio Camera. 


Maryland Engineering Collaborates on Three MURIs

Multidisciplinary University Research Initiative (MURI) awards support growth of newly emerging technologies.

BBI Seed Grant winners announced

Five projects selected for inaugural round of funding.

ECE Event Highlights Innovation, Entrepreneurship

Research Review Day showcases technology advancements in electrical and computer engineering.

$50K Business Plan Competition Semifinalists Announced

The 16 semifinalist teams include university faculty, students, and young alumni.