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Description: Accelerating materials design, synthesis prediction, and chemical machine learning
Incoming Assist. Prof. @ UCLA, Lawrence Fellow @ LLNL
dskoda [a] llnl [.] gov About me: I am an incoming Assistant Professor (starting March 2024) in the Department of Materials Science and Engineering at UCLA Samueli ( news ). Currently, I work as a Lawrence Fellow at the Lawrence Livermore National Laboratory ( QSG , MSD ). I obtained a PhD in Materials Science and Engineering from MIT in 2022. Prior to MIT, I graduated with an MSc in Physics and a BSc in Electronics Engineering from the Aeronautics Institute of Technology, Brazil .
Research interests: I develop digital synthesis methods using high-throughput simulations, machine learning, and materials theory to accelerate materials discovery beyond property prediction. My projects range from improving the robustness of neural networks for atomistic simulations to designing new synthesis routes for heterogeneous catalysts. I work closely with experimental colleagues to validate theoretical predictions in the lab, and help accelerating experimentation using data-driven approaches.
🪁 mkite docs