Matthias Ihme

Full Professor, Stanford University

Joined

July 2019

Names

Matthias Ihme (Preferred)

Emails

****@stanford.edu (Confirmed)

Personal Links

Homepage

DBLP

ORCID

Career & Education History

Full Professor

Stanford University (stanford.edu)

2021 – Present

Advisors, Relations & Conflicts

PhD Advisor

Heinz Pitsch

2002 – 2008

Expertise

No areas of expertise listed

Publications

Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data
Wai Tong Chung, Bassem Akoush, Pushan Sharma, Alex Tamkin, Ki Sung Jung, Jacqueline Chen, Jack Guo, Davy Brouzet, Mohsen Talei, Bruno Savard, Alexei Y Poludnenko, Matthias Ihme
- NeurIPS 2023 Datasets and Benchmarks Poster
- Readers: Everyone
Flamelet regime characterization for non-premixed turbulent combustion simulations
Wai Lee Chan, Matthias Ihme
- 15 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Assessment of model assumptions and budget terms of the unsteady flamelet equations for a turbulent reacting jet-in-cross-flow
Wai Lee Chan, Hemanth Kolla, Jacqueline Chen, Matthias Ihme
- 15 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
A multi-scale asymptotic scaling and regime analysis of flamelet equations including tangential diffusion effects for laminar and turbulent flames
Arne Scholtissek, Wai Lee Chan, Hongbin Xu, Franziska Hunger, Hemanth Kolla, Jacqueline Chen, Matthias Ihme, Christian Hasse
- 15 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
A TensorFlow simulation framework for scientific computing of fluid flows on tensor processing units
Qing Wang, Matthias Ihme, Yi-Fan Chen, John Anderson
- 12 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Accelerating large-eddy simulations of clouds with Tensor Processing Units
Sheide Chammas, Qing Wang, Tapio Schneider, Matthias Ihme, Yi-Fan Chen, John Anderson
- 12 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Accelerating large-eddy simulations of clouds with Tensor Processing Units
Sheide Chammas, Qing Wang, Tapio Schneider, Matthias Ihme, Yi-Fan Chen, John R. Anderson
- Published: 01 Jan 2023, Last Modified: 12 May 2023
- CoRR 2023
- Readers: Everyone
The Bearable Lightness of Big Data: Towards Massive Public Datasets in Scientific Machine Learning
Wai Tong Chung, Ki Sung Jung, Jacqueline Chen, Matthias Ihme
- Published: 15 Jun 2022, Last Modified: 30 Dec 2025
- ICML-AI4Science Poster
- Readers: Everyone
A TensorFlow simulation framework for scientific computing of fluid flows on tensor processing units
Qing Wang, Matthias Ihme, Yi-Fan Chen, John R. Anderson
- Published: 01 Jan 2022, Last Modified: 12 May 2023
- Comput. Phys. Commun. 2022
- Readers: Everyone
The Bearable Lightness of Big Data: Towards Massive Public Datasets in Scientific Machine Learning
Wai Tong Chung, Ki Sung Jung, Jacqueline H. Chen, Matthias Ihme
- Published: 01 Jan 2022, Last Modified: 06 Jun 2023
- CoRR 2022
- Readers: Everyone

View all 32 publications

Co-Authors

View all 51 co-authors