Home
Code and Papers
Bio and CV
Previous talks
Teaching
Mischief
Tess Smidt is an Assistant Professor of Electrical Engineering and Computer Science at MIT. Tess earned her SB in Physics from MIT in 2012 and her PhD in Physics from the University of California, Berkeley in 2018. Her research focuses on machine learning that incorporates physical and geometric constraints, with applications to materials design. Prior to joining the MIT EECSÂ faculty, she was the 2018 Alvarez Postdoctoral Fellow in Computing Sciences at Lawrence Berkeley National Laboratory and a Software Engineering Intern on the Google Accelerated Sciences team where she developed Euclidean symmetry equivariant neural networks which naturally handle 3D geometry and geometric tensor data.
Ph.D. in Physics, U.C. Berkeley (2018) [Dissertation]
M.A. in Physics, U.C. Berkeley (2014)
S.B in Physics with Minor in Architecture, MIT (2012)
Department of Electrical Engineering and Computer Science, MIT
Principal Investigator, Research Laboratory of Electronics
(Fall 2021 - present)
Computational Chemistry, Materials, and Climate Group
Computational Research Division, Berkeley Lab
(Summer 2018 - Summer 2021)
Google Accelerated Science
(Spring 2017 - Spring 2018)
Neaton Group, U.C. Berkeley and Molecular Foundry @ Berkeley Lab
(Fall 2013 - Spring 2018)
Analytis Group, U.C. Berkeley
(Spring 2012 - Spring 2013)
Compact Muon Solenoid, MIT and CERN
(Summer 2012)
Conrad Group, MIT and Fermilab
(Fall 2010 - Spring 2012)