This Major Research Instrumentation (MRI) award supports the acquisition of state-of-the-art Automatic Test Equipment at San Francisco State University (SFSU) to accelerate research, expand research training capacity, and build new programs on electronic design and testing as well as collaborative robotics. This industry-standard test system will bring new experimental capability to test a variety of integrated circuits and circuit boards and will enable functional tests, parametric measurements, memory tests, scan tests, and speed tests. This MRI equipment acquisition will create new research opportunities and enhance existing research capabilities at an urban, Hispanic-serving, non-Ph.D. granting institution in the critical areas of hardware security, machine learning hardware, neural machine interface, wearable robotics, and artificial intelligence in robotics. The equipment will catalyze the establishment of an expert testing center that will benefit the broader research community and promote extensive collaborations with academic and industry partners. It will provide opportunities for Master’s and undergraduate students to engage in frontier research using cutting-edge technologies, which is critical for them to compete successfully for positions in industry or entrance into Ph.D. programs. The Automatic Test Equipment will provide a new tool for recruiting, retaining, and engaging students and faculty members from underrepresented groups in engineering and computer science at SFSU.
The Automatic Test Equipment acquisition will greatly advance the research programs of faculty members and student researchers enabling them to test and characterize circuits ranging from simple digital circuits to complex system-on-chips. In hardware security research, the instrument will catalyze progress in designing reconfigurable circuits for hardware obfuscation. It will be used for testing the functionality, performance, and security of circuits and design techniques to enhance the security of Integrated Circuits. In the area of machine learning hardware, it will be used to test and characterize the functionality, power, frequency, and reliability of memristor-based pattern recognition circuits. The focus will be on testing analog integrated circuits interfaced with memristor crossbar arrays and determining memristor properties in pattern recognition applications. In the neural-machine interfaces area, the Automatic Test Equipment will enable collecting and interpreting bioelectric signals from human neural control systems to identify human states, including emotion, intention, and motion; and to control external devices, including power prostheses and virtual input devices. It will allow testing of embedded neural-machine interface prototypes with integrated microcontrollers, Radio Frequency chips, and biosensors. In the robotics area, the Automatic Test Equipment will be used to: (1) test and debug electronics used in wearable robotics to improve the mobility and quality of life for the disabled population; and (2) verify the functionality and security of sensors, including cameras and range and positioning sensors employed in autonomous robots and cyber-physical systems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
