A Novel MIMO Radar Approach Based on Sparse Sensing and Matrix Completion

Prof. A. Petropulu received a 3-year NSF grant for the project entitled: "A Novel MIMO Radar Approach Based on Sparse Sensing and Matrix Completion".

The abstract is as follows:

In both civilian and military applications, there is increasing interest in networked radars which are inexpensive and easily deployable, while at the same time enabling reliable surveillance of an area.

Polymer-Probe-Based Scanning Probe Microscope for Noninvasive, High-Speed, Broadband Investigation of Live Mammalian Cell

Prof. Jaeseok Jeon is part of a team that has been awarded an NSF grant of $636,557 for 3 years for the project   Development of a Polymer-Probe-Based Scanning Probe Microscope for Noninvasive, High-Speed, Broadband Investigation of Live Mammalian Cell.   This is a collaborative project with Profs. Qingze Zou (PI) of Mechanical and Aerospace Engineering and Nan Gao of Biological Sciences.

Active Feature Learning and Classifier Training for Object Recognition

ECE faculty Waheed Bajwa, Anand Sarwate and Athina Petropulu have received a one-year, $125,526 award from General Dynamics under an Army Research Lab Collaborative Technology Alliance (CTA) on Robotics. This basic research award is titled "Active Feature Learning and Classifier Training for Object Recognition." As part of this project, the Rutgers team will work together with other consortium members to develop algorithms for analyzing behaviors and activities from video and LADAR data, which will eventually help the Army develop future highly autonomous unmanned systems.

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