Professor of Electrical and Computer Engineering
Associate Dean for Graduate Studies
Ph.D. - University of Tennessee
Electrical and Computer Engineering
M.S. - Florida State University
Electrical Engineering
B.S. - Florida State University
Electrical Engineering
Contact Information
Office: 110 Riggs Hall
Office Phone: 864.656.2119
Fax: 864.656.5910
Email: smithmc@clemson.edu
Professional
Before her appointment at Clemson in 2006, Dr. Smith was a research associate at the Oak Ridge National Laboratory (ORNL). While at ORNL, her research activities including high-energy and nuclear physics instrumentation (the Spallation Neutron Source at ORNL, the PHENIX particle physics experiment at Brookhaven National Laboratory (BNL), and the Nuclear Weapons Inspection System (NWIS) program), sub-micron CMOS circuit design (analog, digital, and mixed-signal), fault-tolerant sensor networks, software-defined radio, machine learning, and high-performance and reconfigurable computing for real-time systems and scientific computation. She continues to collaborate with some of the top research scientists at ORNL and across the country in areas of heterogeneous high-performance computing, machine learning and AI, System Performance Modeling and Analysis, and High-Speed Data Acquisition Systems.
Research Interests:
• Machine Learning, Deep Learning, and Artificial Intelligence
• Reconfigurable, GPUs, and High-Performance Computing
• Embedded Computing
• System Performance Modeling and Analysis
Dr. Smith has over 25 years of experience developing and implementing scientific workloads and machine learning applications across multiple domains, including 12 years as a research associate at ORNL. Her current research focuses on performance analysis and optimization with emerging heterogeneous computing architectures (GPGPU- and FPGA-based systems) for various application domains, including machine learning, high-performance or real-time embedded applications, and image processing. Her group collaborates with researchers in other fields to develop new approaches to the application/architecture interface, providing interdisciplinary solutions that enable new scientific advancements and capabilities.