Tess Smidt joined the Department of Electrical Engineering and Computer Science as an Assistant Professor in September 2021. She earned her SB in Physics from MIT in 2012 and her PhD in Physics from the University of California, Berkeley in 2018. She is the principal investigator of the Atomic Architects group at the Research Laboratory of Electronics (RLE), where she works at the intersection of physics, geometry, and machine learning to design algorithms that aid in the understanding and design of physical systems. Her research focuses on machine learning that incorporates physical and geometric constraints, with applications to materials design. Prior to joining the MIT EECS 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.