Postdoctoral Scholar · Stanford University

Carlos Castillo-Passi

I am a postdoctoral scholar at Stanford working at the intersection of mathematics, physics, computing, and medical imaging. I develop high-performance, open-source methods that turn first-principles MRI models into practical tools for simulation, sequence design, and image reconstruction. My current research uses compiler technology and AI to build efficient, physically consistent methods for medical imaging.

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Projects

Open-source MRI simulation

KomaMRI.jl

2022–Present · Currently at Stanford University

Fast, accurate, Pulseq-compatible MRI simulation, with a student-friendly GUI and an extensible API for advanced research.

Overview (17 outputs)

GPU-accelerated inverse problems

Differentiable Physics for MRI

2025–Present · Currently at Stanford University

Automatic differentiation through GPU-accelerated MRI simulations for inverse problems, from RF pulse and sequence design to simulation-based reconstruction.

Overview (3 outputs)

Low-field cardiovascular MRI

Whole-heart MRI at 0.55T

2023–2025

Free-breathing whole-heart MRI at 0.55T, combining coronary angiography with CMRA and simultaneous lumen and vessel-wall imaging with iT2prep-BOOST.

Overview (4 outputs)

Quantitative MRI

Magnetic Resonance Fingerprinting

2024–2025

Motion-compensated diffusion encoding for simultaneous T1, T2, and ADC mapping, with liver validation, 0.55T feasibility studies, and open-source Julia code.

Overview (5 outputs)

Distinctions