Walter Simson is a Senior AI Engineer at NVIDIA and a Research Scientist at Stanford with 11 years of experience specializing in deep learning for medical imaging, particularly ultrasound perception and sound speed imaging as a potential biomarker. He holds a PhD from TUM under Prof. Nassir Navab and has a track record of translating research to clinical-grade systems, including in-vivo sound speed estimation within 10 m/s using Python, PyTorch, and CUDA. At TUM he led interdisciplinary teams, supervised students, built a 10-node Kubernetes scientific cluster and released open-source tooling (UFF.py) that supported large-scale ultrasound experiments. Comfortable bridging academia and industry, he combines rigorous computational skills (C++, CUDA, Julia) with systems engineering and ethics experience, having authored IRB-approved proposals and managed significant compute procurement. Based in Menlo Park, he brings a pragmatic, product-minded approach to pushing ultrasound AI from simulation to real-world devices.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Technical University of Munich
Contributions:1 release, 1 review, 62 commits in 1 year 5 months
file-formatpythonultrasoundpython-readerreader
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