Dr. Isaac Tamblyn holds adjunct positions at the University of Ottawa (Physics), University of Waterloo (Electrical and Computer Engineering), and Ontario Technology University (Physics)
Isaac held post doctoral fellowships at the Lawrence Livermore National Laboratory and UC Berkeley, and was a Killam Scholar.
The main objective of his research is to apply computational methods to applied problems in material science. Recently, his group has been focused on applying the tools of “data science” to the problem of materials. Of particular interest is using recent advances in deep learning learning and A.I. to develop computationally tractable solutions to hard problems in condensed matter physics, with a focus on applications in the space of renewable energy materials.
Selected Publications
Crystal Site Feature Embedding Enables Exploration of Large Chemical Spaces
Authors: H. Choubisa, M. Askerka, K. Ryczko, O. Voznyy, K. Mills, I. Tamblyn, E. H. Sargent
Volume/Number: Matter, DOI:10.1016/j.matt.2020.04.016
Year: 2020
Controlled Online Optimization Learning (COOL): Finding the ground state of spin Hamiltonians with reinforcement learning
Authors: K. Mills, P. Ronagh, and I. Tamblyn
Volume/Number: Nature Machine Intelligence [accepted]
Year: 2020
Evolutionary reinforcement learning of dynamical large deviations
Authors: S. Whitelam, D. Jacobson, and I. Tamblyn
Volume/Number: J. Chem. Phys [accepted]
Year: 2020
