Joshua Agar

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Machine Learning

Joshua Agar, Ph.D., is an Assistant Professor of Materials Science and Engineering. His many interests include pulsed-laser deposition to synthesis to design with unit cell level control to design novel multifunctional materials, multidimensional and multifrequency in situ and in operando spectroscopies to provide unpredictable insight into structural property relations, and augmented human intelligence to distill data into digestible information to guide design of materials. He received his PhD from University of Illinois, Urbana-Champaign and M.S. in Materials Science and Engineering from Georgia Institute of Technology and B.S. in Materials Science and Engineering from University of Illinois, Urbana-Champaign. 
For the NHI initiative, Dr. Agar is leading the effort to develop “an efficient Bayesian-guided computational framework” that will guide the development of a neural network that will serve to turbo-charge the search for new and advanced materials with enhanced electrical, thermal, mechanical, and magnetic characteristics. His idea is to apply deep learning neural networks to more efficiently perform functions associated with traditional physics-based computational simulation. He intends to eventually accelerate the work of other NHI researchers in the discovery and synthesis of novel materials.
Research Interests
  • Scanning Probe Microscopy
  • Machine Learning and Data Science
  • Ferroelectrics
  • Oxide Synthesis


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