About
 

Tess Smidt

Associate Professor, Department of Electrical Engineering and Computer Science

Publications Research

Categories

Algorithm Design Computational Design Computational Materials Science Physics

Tess Smidt is an associate professor in the Department of Electrical Engineering and Computer Science (EECS); she holds the X-Window Consortium Professor chair. Smidt leads the the Atomic Architects group at the Research Laboratory of Electronics (RLE) at MIT. Her research focuses on machine learning that incorporates physical and geometric constraints, with applications to materials design. Her research areas of interest include developing neural networks from first-principles for rich data types (e.g. scientific data and geometry), chemical and material science and design, group theory and symmetry, density functional theory, scientific computing, computational geometry, computer-aided design, and rapid prototyping. Prior to joining the MIT EECS faculty, she was the 2018 Luis W. Alvarez Postdoctoral Fellow at Lawrence Berkeley National Laboratory and interned on the Google Accelerated Sciences team, where she developed Euclidean symmetry equivariant neural networks which naturally handle 3D geometry and geometric tensor data. Tess earned her PhD and MA in physics from the University of California, Berkeley; she received her SB in physics from MIT.

Selected Publications

  • Aleksich, M., Cho, Y., Paley, D. W., Willson, M. C., Nyiera, H. N., Kotei, P. A., Oklejas, V., Mittan-Moreau, D. W., Schriber, E. A., Christensen, K., Inoue, I., Owada, S., Tono, K., Sugahara, M., Inaba-Inoue, S., Vakili, M., Milne, C. J., DallAntonia, F., Khakhulin, D., Ardana-Lamas, F., Lima, F., Valerio, J., Han, H., Gallo, T., Yousef, H., Turkot, O., Bermudez Macias, I. J., Kluyver, T., Schmidt, P., Gelisio, L., Round, A. R., Jiang, Y., Vinci, D., Uemura, Y., Kloos, M., Mancuso, A. P., Warren, M., Sauter, N. K., Zhao, J., Smidt, T., Kulik, H. J., Sharifzadeh, S., Brewster, A. S., & Hohman, J. N. (2024). Ligand-mediated quantum yield enhancement in 1-D silver organothiolate metal–organic chalcogenolates. Advanced Functional Materials, 35(6), 2414914.
  • Fu, X., Rosen, A., Bystrom, K., Wang, R., Musaelian, A., Kozinsky, B., Smidt, T., & Jaakkola, T. (2024). A recipe for charge density prediction. In Advances in Neural Information Processing Systems 37 (NeurIPS).
  • Sheriff, K., Cao, Y., Smidt, T., & Freitas, R. (2024). Quantifying chemical short-range order in metallic alloys. Proceedings of the National Academy of Sciences, 121(25), e2322962121.

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