Differentiable neural-network solver for data assimilation of ice shelves in JAX
Y. Wang and C.-Y. Lai. (2025). "Differentiable neural-network solver for data assimilation of ice shelves in JAX." Journal of Open Source Software, 10, 7254.
CV
Education
- Ph.D in Version Control Theory, GitHub University, 2018 (expected)
- M.S. in Jekyll, GitHub University, 2014
- B.S. in GitHub, GitHub University, 2012
Work experience
- Spring 2024: Academic Pages Collaborator
- Github University
- Duties includes: Updates and improvements to template
- Supervisor: The Users
- Fall 2015: Research Assistant
- Github University
- Duties included: Merging pull requests
- Supervisor: Professor Hub
- Summer 2015: Research Assistant
- Github University
- Duties included: Tagging issues
- Supervisor: Professor Git
Skills
- Skill 1
- Skill 2
- Sub-skill 2.1
- Sub-skill 2.2
- Sub-skill 2.3
- Skill 3
Publications
Deep learning the flow law of Antarctic ice shelves
Y. Wang, C.-Y. Lai, D. J. Prior, and C. Cowen-Breen. "Deep learning the flow law of Antarctic ice shelves." Science, 387, 1219-1224.
Theoretical stability of ice shelf basal crevasses with a vertical temperature profile
N. B. Coffey, C.-Y. Lai, Y. Wang, et al. (2024). "Theoretical stability of ice shelf basal crevasses with a vertical temperature profile." Accepted at Journal of Glaciology.
Theoretical analysis of stress perturbations from a partially-lubricated viscous gravity current
J. Rhines, C.-Y. Lai and Y. Wang. "Theoretical analysis of stress perturbations from a partially-lubricated viscous gravity current." arXiv preprint arXiv:2407.20565.
Spectrum-informed multistage neural nework: Multiscale function approximator of machine precision
J. Ng, Y. Wang, C.-Y. Lai. (2024). "Spectrum-informed multistage neural nework: Multiscale function approximator of machine precision." ICML2024-AI4Science Workshop.
Euler operators for mis-specified physics-informed neural networks
C. Cowen-Breen, Y. Wang, C.-Y. Lai. (2024). "Euler operators for mis-specified physics-informed neural networks." ICML2024-AI4Science Workshop.
Multi-stage Neural Networks: Function Approximator of Machine Precision
Y. Wang, C.-Y. Lai. (2024). "Multi-stage Neural Networks: Function Approximator of Machine Precision." Journal of Computational Physics, 504, 112865.
Asymptotic self-similar blow-up profile for three-dimensional axisymmetric Euler equations using neural networks
Y. Wang, C.-Y. Lai, J.Gómez-Serrano, and T. Buckmaster. (2023). "Asymptotic self-similar blow-up profile for three-dimensional axisymmetric Euler equations using neural networks." Physical Review Letters, 130, 244002.
Non-Galilean Taylor–Culick law governs sheet dynamics in unsteady fragmentation
Y. Wang, L. Bourouiba. (2023). "Non-Galilean Taylor–Culick law governs sheet dynamics in unsteady fragmentation." Journal of Fluid Mechanics, 969, A19.
Mass, momentum and energy partitioning in unsteady fragmentation
Y. Wang, L. Bourouiba. (2022). "Mass, momentum and energy partitioning in unsteady fragmentation</i>, 935, A29.
Growth and breakup of ligaments in unsteady fragmentation
Y. Wang, L. Bourouiba. (2021) "Growth and breakup of ligaments in unsteady fragmentation." Journal of Fluid Mechanics, 910, A39.
Unsteady sheet fragmentation: droplet sizes and speeds
Y. Wang, L. Bourouiba. (2018). "Unsteady sheet fragmentation: droplet sizes and speeds." Journal of Fluid Mechanics, 848, 946-967.
Universal Rim Thickness in Unsteady Sheet Fragmentation
Y. Wang, R. Dandekar, N. Bustos, S. Poulain, and L. Bourouiba. (2018). "Universal rim thickness in unsteady sheet fragmentation." Physical Review Letters, 120, 204503.
Non-isolated drop impact on surfaces
Y. Wang, L. Bourouiba. (2018). "Non-isolated drop impact on surfaces." Journal of Fluid Mechanics, 755, 24-44.
Drop impact on small surfaces: thickness and velocity profiles of the expanding sheet in the air
Y. Wang, L. Bourouiba. "Drop impact on small surfaces: thickness and velocity profiles of the expanding sheet in the air." Journal of Fluid Mechanics, 814, 510-534.
Talks
Recent Progress in Physics-Informed Neural Networks for Self-Similar Blow-Up Solutions
Talk at Department of Mathematics, University of Minnesota Twin Cities, Minneapolis, MN
Multi-stage neural networks achieving machine precision
Talk at Monthly seminar at ANSYS, (Virtual)
Multi-stage neural networks for discovering self-similar blow-up solutions
Talk at FRG conference of PDEs of incompressible fluid flows, computer assisted proofs and neural networks, Minneapolis, MN
Conference Proceeding talk 3 on Relevant Topic in Your Field
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA
Talk 2 on Relevant Topic in Your Field
Talk at London School of Testing, London, UK
Tutorial 1 on Relevant Topic in Your Field
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA
Teaching
Service and leadership
- Currently signed in to 43 different slack teams