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I computationally model perovskite oxides and halides, with specific emphasis on capturing local and modal distortions that change the stabilities and electronic properties of these materials. Most of my investigations are high-throughput and examine many thousands of theoretical materials, identifying the most promising for renewable energy devices. I use a variety of tools and techniques, including machine-learned descriptors, simple models of chemical bonding, and quantum mechanical methods, to identify new and exciting perovskites for these applications.