Director: Prof. Athina Petropulu
Location: 96 Frelinghuysen Road, Room 532, Piscataway, NJ 08854
CSPL focuses on research in theoretical issues in statistical signal processing, system modeling, system identification. Applications of interest include wireless communications, networking, radar systems, biomedicine. Recent project include cooperative approaches for low power wireless communications, physical layer security, mobile beamforming, and compressive sensing based MIMO radar.
Email: waheed.bajwa @ rutgers.edu
Research conducted at the Information, Networks, and Signal Processing Research (INSPIRE) Lab provides a fundamental mathematical understanding of and theoretically optimal, computationally efficient, and algorithmically robust solutions for some of the most pressing problems arising in information processing—an umbrella term that subsumes mathematical signal processing, high-dimensional statistics and machine learning—and networked systems, such as (online) social networks, wireless sensor networks, communication networks, multiagent systems, and brain networks.
Email: laleh.najafizadeh @ rutgers.edu
a. Neuroimaging: Functional Brain Imaging, Diffuse Optical Brain Imaging, Brain Connectivity, Cognitive Neuroscience, Brain Computer Interface, Cognitive Rehabilitation; and
b. Analog, Mixed-Signal, VLSI, and mmw Circuit Design: Ultra Low-Power Circuits for Biomedical Applications, Ultra Fast Circuits, System on Chip.
Director : Prof. Peter Meer
Location: 96 Frelinghuysen Road, Room 531, Piscataway, NJ 08854
The laboratory is under the supervision of Prof. Peter Meer from the Electrical and Computer Engineering Department.
Using rigorous statistical concepts in computer vision, we look to fundamental problems which have been not yet completely solved. We introduced the mean shift algorithm, a nonparametric clustering in vector spaces. Beside segmentation and tracking of objects, we also generalized it to non-vector spaces, based on results from group theory. We developed a semi-supervised kernel clustering algorithm which exceeds other results, even without knowing the number of clusters.
Using linearization of nonlinear problems, to which almost all the computer vision problems belong, we described a new errors-in-variables, robust regression algorithm without user defined parameters.
All publications from 1996 on are on the webpage.
Email: burdea @ jove.rutgers.edu
Phone: (848) 445-5309
Tele-rehabilitation is the provision of therapy at a distance. To realize its full potential, it needs better computing and communication technology and well as better prepared medical professionals.
The Tele-rehabilitation Institute mission is three-fold, in areas of Research, Clinical Development and Education:
• Research - to develop highly innovative technology that allows fun and efficacious therapy to occur in the home. This alleviates the need to go to clinics, while therapists remotely monitor and adjust your home treatment;
• Clinical Development - to measure the efficacy and improve the new systems based on patient clinical use in a controlled and safe environment;
• Education - to form the new generation of therapists that understand and fully exploit the capabilities of the new Tele-rehabilitation therapy.