MRI: Acquisition of Automatic Test Equipment to Enhance Research and Research Training in Engineering and Computer Science at San Francisco State University

该主要研究仪器（MRI）奖支持旧金山州立大学（SFSU）购买最先进的自动测试设备，以加速研究，扩大研究培训能力，并建立电子设计和测试以及协作机器人的新项目。这个行业标准测试系统将带来新的实验能力，以测试各种集成电路和电路板，并将实现功能测试、参数测量、内存测试、扫描测试和速度测试。此次核磁共振成像设备的收购将创造新的研究机会，并提高城市，西班牙裔服务，非博士现有的研究能力。在硬件安全、机器学习硬件、神经机器接口、可穿戴机器人和机器人中的人工智能等关键领域授予机构。该设备将催化建立一个专家测试中心，这将有利于更广泛的研究界，并促进与学术和行业合作伙伴的广泛合作。它将为硕士生和本科生提供使用尖端技术从事前沿研究的机会，这对他们成功竞争行业职位或进入博士课程至关重要。自动测试设备将为旧金山州立大学工程和计算机科学领域代表性不足的学生和教职员工的招聘、保留和参与提供一种新工具。自动测试设备的收购将极大地推进教师和学生研究人员的研究计划，使他们能够测试和表征从简单的数字电路到复杂的片上系统的电路。在硬件安全研究中，该仪器将促进硬件混淆可重构电路设计的进展。它将用于测试电路的功能，性能和安全性以及设计技术，以提高集成电路的安全性。在机器学习硬件领域，它将用于测试和表征基于忆阻器的模式识别电路的功能、功率、频率和可靠性。重点将是测试与忆阻器交叉棒阵列接口的模拟集成电路，并确定模式识别应用中的忆阻器特性。在神经-机器接口领域，自动测试设备将能够收集和解释来自人类神经控制系统的生物电信号，以识别人类的状态，包括情绪、意图和运动；并控制外部设备，包括动力假肢和虚拟输入设备。它将允许测试集成微控制器、射频芯片和生物传感器的嵌入式神经机器接口原型。在机器人领域，自动测试设备将用于：(1)测试和调试可穿戴机器人中使用的电子设备，以改善残疾人的行动能力和生活质量；(2)验证传感器的功能和安全性，包括自主机器人和网络物理系统中使用的摄像头、测距和定位传感器。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.