University of Illinois at Urbana-Champaign (UIUC)

2017 - Present

Ph.D. student in Materials Science and Engineering - CSE concentration

Advisor: Dallas Trinkle (MatSE)

GPA: 3.50/4.00

University of Arizona (UofA)

2013 - 2017

B.S. in Materials Science and Engineering, B.S. in Mathematics

GPA: 3.68/4.00


Skills: Python, PyTorch, Bash, C++, MPI, LAMMPS, Dask, MongoDB

Classes: Deep Learning, Applied Machine Learning, Atomic Scale Simulations, Parallel Programming, Numerical Analysis, Mathematical Methods in Physics, Advanced Applied Mathematics, Object-Oriented Programming and Design


UIUC: Ph.D. Researcher -- Urbana, IL

Aug 2017 - Present

  • Designed a machine learning model for describing atomic interactions (interatomic potential) using spline-based atomic environment descriptors with speeds up to 10x faster than models with similar accuracy.

  • Developed a novel method for constructing universal interatomic potentials by using generative models (variational autoencoders) for building transferable and interpretable latent spaces.

  • Wrote parallel, scalable fitting software from scratch using Python, PyTorch, and Dask; wrote software patches in C++ for existing production-level molecular simulation software (LAMMPS).

ColabFit (University of Minnesota): Ph.D. Research Intern -- remote

Sep 2021 - Present

  • Contributed to research community and enabled large-scale analysis of materials data by leading a community-wide effort to design and construct an open-source database of electronic structure calculations.

  • Established a standard for storing first-principles simulation data in an efficient and queryable format, and constructed Python and web APIs to a Mongo database of user-contributed datasets.

  • Directed a team of researchers in design and development of software framework, and interfaced with users in the field to guide research direction and collect feedback.

UofA: Undergraduate Research Assistant -- Tucson, AZ

Sep 2016 - Aug 2017

  • Analyzed mechanical and thermal properties of self-assembled buckminsterfullerene (C60) structures using computational methods.

  • Designed, executed, and interpreted molecular dynamics simulations of bulk C60 molecular solids.

  • Applied basic statistical techniques to analyze simulation results, and wrote software tools in Python to aid in supercell construction.

Sandia National Laboratories: Student Intern (year-round) -- Albuquerque, NM

June 2016 - March 2017

  • Developed object recognition software for addressing unique challenges associated with X-ray images by experimenting with various feature detector and descriptor algorithms in Python and MATLAB.

  • Summarized and presented results at the 2016 SPIE Optics + Photonics conference.

UofA: Undergraduate Research Assistant -- Tucson, AZ

Jan 2015 - Aug 2016

  • Contributed to NASA research project analyzing directional solidification of aluminum - 7% silicon alloys on the International Space Station to study the effects of convection on macrosegregation and dendrite arm spacing.

  • Performed fundamental metallography tasks of Al-Si alloys, including sample polishing and preparation, imaging, image analysis. Wrote basic image analysis software in Python for quantifying dendrite growth.

UofA: Undergraduate Teaching Assistant -- Tucson, AZ

Jan 2015 - March 2016

  • Helped prepare incoming freshmen for college-level algebra by conducting a weekly online classroom and facilitating in-person office hourse to provide math tutoring and academic advisement.

  • Trained new teaching assistants by coordinating and leading training sessions about teaching best-practices and communication skills.


  1. Joshua A. Vita, Dallas R. Trinkle, "Exploring the necessary complexity of interatomic potentials", Computational Materials Science, Volume 200 (2021), 110752,

  2. A. Alsayoud et al., "Atomistic insights into the effect of polymerization on the thermophysical properties of 2-D C60 molecular solids", Carbon (2018): DOI: 10.1016/j.carbon.2018.01.044

  3. J. Vita et al., "Hybrid object detection system for x-ray radiographs", SPIE Optical Engineering + Applications Proceedings, Volume 9969, Radiation Detectors: Systems and Applications XVII; 996909 (2016): DOI:

  4. A. Wantuch et al., "Exploration of available feature detection and identification systems and their performance on radiographs", SPIE Optical Engineering + Applications Proceedings, Volume 9969, Radiation Detectors: Systems and Applications XVII; 996907 (2016): DOI:


  • "Interpretability in Deep Learning Models for Atomic-Scale Simulations", Lawrence Livermore National Lab Data Science Institute, virtual, July 2022 (link)

  • "Interpretability in Deep Learning Models for Atomic-Scale Simulations", Los Alamos National Lab, Los Alamos, NM, July 2022

  • "Exploring the Necessary Complexity of Interatomic Potentials", 2022 Spring Materials Research Society Meeting, Honolulu, HI, May 2022

  • "ColabFit: Collaborative Development of Data-Driven Interatomic Potentials", APS March Meeting 2022, Chicago, IL, March 2022


  • UIUC NSF DIGI-MAT fellow (link)

    • Fellow and leadership board member -- NSF-funded Ph.D. training program for promoting data science in materials research; served as student/professor liaison to aid in program development, course design, and student on-boarding

  • 2018 African School on Electronic Structure: Methods and Applications (ASESMA)

    • Student instructor in two-week workshop in Ethiopia to promote research using DFT at African universities. Led workshops and discussions to teach students how to design and run molecular dynamics simulations

  • The Hacker Within

    • Computational science student club for promoting collaboration and open discussion of various topics including programming, machine learning, cybersecurity, and data visualization. Software Carpentry Leader: conducted training sessions teaching Python fundamentals, introductions to Github, and code optimization.