Dr. Jules White is an Assistant Professor of Computer Science in the Dept. of Electrical Engineering and Computer Science at Vanderbilt University. He was previously a faculty member in Electrical and Computer Engineering at Virginia Tech and won the Outstanding New Assistant Professor Award at Virginia Tech. His research has won 5 Best Paper and Best Student Paper Awards. He has also published over 85 papers.
Dr. White’s research focuses on securing, optimizing, and leveraging data from mobile cyber-physical systems. His mobile cyber-physical systems research spans four key focus areas: (1) mobile security and data collection, (2) high-precision mobile augmented reality, (3) mobile device and supporting cloud infrastructure power and configuration optimization, and (4) applications of mobile cyber-physical systems in multi-disciplinary domains, including energy-optimized cloud computing, smart grid systems, healthcare/manufacturing security, next-generation construction technologies, and citizen science.
Dr. White's research has been licensed and transitioned to industry, where it won an Innovation Award at CES 2013, attended by over 150,000 people, was a finalist for the Technical Achievement at Award at SXSW Interactive, and was a top 3 for mobile in the Accelerator Awards at SXSW 2013. His research is conducted through the Mobile Application computinG, optimizatoN, and secUrity Methods (MAGNUM) Group at Vanderbilt University, which he directs.
Through his research efforts in model-driven engineering, Dr. White became the project leader of the Eclipse Foundation’s Generic Eclipse Modeling System (GEMS). GEMS is a part of the Eclipse Modeling Project that also contains the Eclipse Modeling Framework (EMF). GEMS is distributed by over 45 mirrors in North America, Europe, Asia, and South America. The development of GEMS has been supported by industrial partners, such as IBM, Lockheed Martin, Raytheon, and PrismTech.
In collaboration with Lockheed Martin Aeronautics, Dr. White has developed highly scalable particle swarm optimization techniques for optimizing the deployment of software in real-time aeronautics platforms to reduce network traffic. Initial results from applying his algorithms to a representative aeronautics platform have shown the potential to reduce network traffic by over 25% and overall hardware footprint by ~40%. Dr. White has also worked on deployment modeling and optimization projects in the automotive and medical imaging domains for Siemens AG. Dr. White’s current work on deployment optimization for multi-core processors is supported by the National Science Foundation, Lockheed Martin, and the Air Force Research Laboratories.