Themistoklis Sapsis

Full Professor, Massachusetts Institute of Technology

Joined

June 2019

Names

Themistoklis Sapsis

Emails

****@mit.edu (Confirmed)

Personal Links

Homepage

Career & Education History

Full Professor

Massachusetts Institute of Technology (mit.edu)

2013 – Present

Advisors, Relations & Conflicts

PhD Advisor

George Haller

Present

Expertise

Big Data Science &Engineering

Wireless comm & sig processing

Present

Publications

Learning Chaotic Dynamics with Embedded Dissipativity
Sunbochen Tang, Themistoklis Sapsis, Navid Azizan
- ICLR 2025 Conference Withdrawn Submission
- Readers: Everyone
Statistics of extreme events in climate models via coarse-scale simulations and machine learning correction operators based on nudged datasets
Alexis-Tzianni Charalampopoulos, Shixuan Zhang, Bryce Harrop, Ruby Leung, Themistoklis Sapsis
- 01 Aug 2023
- AAAI 2023 Spring Symposium Series ACTD Submission
- Readers: Everyone
A Gaussian moment method and its augmentation via LSTM recurrent neural networks for the statistics of cavitating bubble populations
Spencer H Bryngelson, Alexis-Tzianni Charalampopoulos, Themistoklis Sapsis, Tim Colonius
- 12 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Machine-learning energy-preserving nonlocal closures for turbulent fluid flows and inertial tracers
Alexis-Tzianni Charalampopoulos, Themistoklis Sapsis
- 12 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Uncertainty quantification of turbulent systems via physically consistent and data-informed reduced-order models
Alexis-Tzianni Charalampopoulos, Themistoklis Sapsis
- 12 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Statistics of extreme events in coarse-scale climate simulations via machine learning correction operators trained on nudged datasets
Alexis-Tzianni Charalampopoulos, Shixuan Zhang, Bryce Harrop, Ruby Leung, Themistoklis Sapsis
- 12 May 2023
- OpenReview Archive Direct Upload
- Readers: Everyone

Themistoklis Sapsis

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Learning Chaotic Dynamics with Embedded Dissipativity

Statistics of extreme events in climate models via coarse-scale simulations and machine learning correction operators based on nudged datasets

A Gaussian moment method and its augmentation via LSTM recurrent neural networks for the statistics of cavitating bubble populations

Machine-learning energy-preserving nonlocal closures for turbulent fluid flows and inertial tracers

Uncertainty quantification of turbulent systems via physically consistent and data-informed reduced-order models

Statistics of extreme events in coarse-scale climate simulations via machine learning correction operators trained on nudged datasets

Co-Authors