REU Site: Sensor, Signal and Information Processing Devices and Algorithms

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This three year REU site will recruit and train nine undergraduate students each summer and engage them in research endeavors on the design of sensors including student training in mathematical methods for extracting information from sensor systems. The investigators along with a team of faculty advisors will supervise a series of multidisciplinary projects in the design of integrated sensor systems. In addition to the planned projects, the faculty leaders of this program will organize a series of industry collaborative training activities for the students. This REU features multidisciplinary synergies across different research labs that provide access to unique sensor and algorithm technology. The program also includes crosscutting modules, and workshops in public speaking, policy, standards, ethics, patents, SBIR planning, and outreach. Annual REU workshops will train students to communicate with stakeholders who can help establish new standards. An evaluation unit will assess REU goals annually using feedback from academia, industry and stakeholders. The program engages minority colleges to broaden participation and enhance recruitment. The REU will address STEM problems associated with sensor applications in internet of things, health monitoring and security. Specific objectives of the REU site are to: a) introduce students to general research practices by immersing them in government and industry research activities, b) engage students in integrated design of sensor devices and relevant information processing methods, c) motivate students to pursue research careers, d) provide cross cutting skills in presentation, developing patents, entrepreneurship, and building awareness on social implications, policies and standards. The REU projects are designed to introduce students to an array of sensor device design technologies that emphasize low power circuits, flexible electronics, MEMS, and embedded systems. During the same period, projects will train REU students to interpret data from sensors by studying and programming machine learning algorithms, sensor fusion methods, and techniques to interpret big data sets.