01 / Solid-state physics
Solid-state thermodynamics
Making accurate thermodynamic predictions accessible, from quantum effects at low temperature to strongly anharmonic solids.
Computational scientist · DOE CSGF fellow
Ethan Meitz
Computational scientist
I’m a mechanical engineering PhD researcher at Carnegie Mellon. I use physics, machine learning, and high-performance computing to understand the world—from vibrating atoms to interacting proteins.
I’m exploring AI-for-science research roles, with a focus on scientific discovery through machine learning and high-performance computing.
Carnegie Mellon UniversityMechanical Engineering PhDExpected Spring 2027 · Exploring AI-for-science roles
Highlights
Research & software
All research ↗
02 / Scientific computing
cuNumeric.jl
A Julia interface to NVIDIA’s cuPyNumeric stack, making multi-node, multi-GPU computation easier to use.
Illustration: PINDER paper ↗
03 / AI for biology
Protein interaction modeling
Building richer datasets and models to study protein binding, with explicit attention to intrinsic disorder.
Writing
All writing ↗
Essay · September 2026
Good vibrations ↗
My essay on atomic motion and modeling solids, published in DEIXIS. Honorable Mention in the 2026 Communicate Your Science & Engineering (CYSE) contest.
Cover image: Ethan Meitz
Conference · Pittsburgh
JuliaCon 2025 ↗
David and I presented cuNumeric.jl at JuliaCon 2025 in Pittsburgh. I also served as a local liaison, helping coordinate spaces and reservations with CMU and Pitt.
Watch our talk ↗Forthcoming · Podcast
cuNumeric.jl and the CSGF experience
A conversation about cuNumeric.jl, working with NVIDIA, and having an advisor who was a CSGF fellow too.
