Miguel Liu-schiaffini
Graduate Research Assistant
Palo Alto, California, United States
Summary
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Rockstar🎓
Top SchoolMiguel Liu-schiaffini is a computer scientist and Stanford Graduate Research Assistant focused on developing physically-guided, principled deep learning methods for scientific applications. A Caltech alumnus and former NVIDIA Research intern, he specializes in neural operator approaches to solving PDEs and brings hands-on experience from the Anandkumar Lab. Since 2020 he has applied ML to geoscience—most notably proposing and leading a project at UTIG that produced an IEEE Transactions paper on automatically mapping ice-bedrock interfaces and led to methods for characterizing the Martian surface relevant to life-search and rover landing-site selection. Based in Palo Alto with four years of research experience, he blends rigorous theory with applied, high-impact scientific problems.
5 years of coding experience
4 years of employment as a software developer
California Institute of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Stanford University
Chinese, Spanish
Github Skills (13)
self-organizing-map10
transform10
partial-differential-equations10
fourier-transform10
tensorly10
uno10
pytorch10
differential-equations10
pde10
neural-operator10
near4
deep-learning2
cuda2
Programming languages (3)
Github contributions (5)
neuraloperator/markov_neural_operator
Sep 2022 - Dec 2022
Contributions:16 commits, 4 pushes, 2 comments in 3 months
mliuschi/neuraloperator-updates
Jun 2023 - Nov 2024
Updating neuraloperator package with MNO code and examples.
Contributions:43 pushes, 3 branches in 1 year 5 months
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