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Hector Santos-Villalobos

Hector Santos

Hector Santos-Villalobos

Assistant Professor


Contact Information

Hector Santos

  • Office Address: 352 Min H. Kao Building
  • Phone: 865-974-3076
  • E-mail: hsantosv@utk.edu

Education

  • PhD, Electrical and Computer Engineering. Purdue University, West Lafayette, Indiana, 2005 - 2010

  • MS, Computer Engineering. University of Puerto Rico Mayagüez, Puerto Rico, 2003 - 2005

  • BS, Computer Engineering. University of Puerto Rico Mayagüez, Puerto Rico, 1998 - 2003


Biography

Hector Santos

Hector J. Santos-Villalobos is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee. He joins the department after 13 years of industry and national laboratory research experience. As an Applied Science Manager at Amazon’s Prime Video and Studios, he led a team in the exploration of computer vision and machine learning techniques for cinematic content understanding, summarization, and generation. Before Amazon, Hector was a Group Leader, Program Manager, and Senior R&D Staff for the National Security Sciences Directorate at Oak Ridge National Laboratory (ORNL). He received BS and MS degrees in 2003 and 2005, respectively, from the Department of Computer and Electrical Engineering at the University of Puerto Rico—Mayaguez. In 2010, he received a Ph.D. from the School of Electrical and Computer Engineering at Purdue University. In 2011, he was one of the JIST & JEI Itek Award recipients for an outstanding and original research publication on imaging science and engineering concerning his doctorate work. In 2020, Santos-Villalobos received the Great Minds in STEM HENAAC Outstanding Technical Achievement award for his significant technological contributions to the STEM field. His cross-cutting research focuses on the design, development, and explainability of multi-modal artificial intelligence systems.


Research

Hector Santos

  • Computational Imaging
  • Multi-Modal Fusion and Learning
  • Biometric Recognition
  • Self-supervised Machine Learning
  • AI-Driven Precision Health (Alzheimer’s Disease and Cancer Detection)
  • Human Cognition-Inspired AI Systems
  • Embodied Artificial Intelligence
  • Content Understanding and Summarization
  • Model Explainability
Google Scholar