Kyle Daniel Miller
ML+DFT for materials design and discovery | PhD Candidate | Rondinelli Group
![prof_pic.jpg](/assets/img/prof_pic.jpg?c74589816292185576263bbb5593525b)
PhD anticipated Summer 2024
Materials Science & Engineering
Northwestern University
Evanston, IL, USA
Keywords
Autonomous materials design and discovery | Surrogate models for atomic simulation | Structure-property relationships | Multiferroics | Metal-insulator transitions | Active learning | Explainable AI | Physics-informed models
Motivation
- I want to create data-driven solutions for materials problems.
- I excel in collaborative, inquisitive environments.
- I prioritize efficient communication and fast failure.
Background
- B.S. in Physics, Mathematics @ University of Puget Sound
- Summer REU in perovskite synthesis @ University of Minnesota
- Summer REU in molecular dynamics @ Boise State University
Current Work
NSF Graduate Research Fellow @ Northwestern University, MTD Group
⇒ Discovering and tuning ferroelectric materials
⇒ Developing design rules for metal-insulator transition materials
Computational materials intern @ Sandia National Laboratories
⇒ Building neural network surrogate models for atomistic simulation
⇒ Contributing to the Materials Learning Algorithms (MALA) framework