Summary
Mario Malavé is a Senior Software Engineer with a PhD in Electrical Engineering from Stanford and over a decade of experience applying deep learning, signal processing, and systems engineering to image and video reconstruction problems. He has shipped production-focused ML solutions at Apple and Google and led research projects that sped up MR image reconstruction by 20x on CPU and 3x on GPU through unrolled model-based deep learning architectures. His work spans acquisition design, iterative and learning-based reconstruction, and efficient undersampling patterns for non-Cartesian 3D imaging, with real patient studies and cross-modality potential (e.g., CT). Comfortable in Python/TensorFlow, MATLAB and low-level scanner code (EPIC), he bridges research and product requirements to deliver deployable, high-performance implementations. Notably, his background includes embedded/DSP experience at Texas Instruments and early systems work at NASA, giving him uncommon depth across hardware, algorithms and clinical imaging. Based in San Jose, he combines rigorous academic publishing with hands-on engineering at scale.
10 years of coding experience
17 years of employment as a software developer
PhD, Electrical Engineering, PhD, Electrical Engineering at Stanford University
Non-degree seeking, Physics, Non-degree seeking, Physics at Texas A&M University
Non-degree seeking, Electrical Engineering, Non-degree seeking, Electrical Engineering at Georgia Tech-Europe
M.S., Electrical Engineering, M.S., Electrical Engineering at Georgia Institute of Technology
Non-degree seeking, Math, Non-degree seeking, Math at University of Houston-Clear Lake
Spanish, French, English