Leo Beck

Computational Materials Scientist

Graduate Researcher @ Heinz Interfaces Lab

Welcome to my website!

I am a Materials Science & Engineering PhD student at CU Boulder. My research is focused on using molecular dynamics and machine learning to predict structural features of hybrid organic inorganic semiconducting materials.

I worked at the Air Force Research Lab (AFRL) as a High Performance Computing researcher Summer of 2024 & 2026, focused on calculating shear and thermal properties of MXenes using molecular dynamics.

I have a B.S. in Mathematics and a B.S. in Materials Science & Engineering from Clemson University, where I worked on a variety of projects including DFT calculations of High Entropy Alloys (HEAs), multi-objective optimization of PDEs, and fabrication of 3-terminal memristors. Additionally, I was a member of the Formula SAE team.

I enjoy music, hiking, climbing, geography games, and reading in my free time.

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Technical Toolkit

Methods I use to build computational materials workflows, from crystal structures and molecular simulations to machine learning models.

Simulation

Building, running, and analyzing atomistic models for materials systems.

LAMMPSNAMDInterface Force FieldHPCbashSlurmmolecular dynamics

Machine Learning

Turning small, structured materials datasets into validated predictive models.

PythonXGBoostfeature extractionSMOTEscikit-learnPandas

Scientific Computing

Writing numerical workflows for simulation, optimization, and high-performance analysis.

scientific computingnumerical PDEsconvex optimizationnumerical optimizationparallel C++MATLAB

Experimental Context

Connecting computational work to fabrication, characterization, and collaborator needs.

photolithographydevice fabricationelectrical characterizationorganic memristors