Alexis-Tzianni Charalampopoulos

Researcher, Bayer Ag

Joined

April 2023

Names

Alexis-Tzianni Charalampopoulos (Preferred)

Emails

****@gmail.com (Confirmed)

****@bayer.com (Confirmed)

Personal Links

Google Scholar

DBLP

Career & Education History

Researcher

Bayer Ag (bayer.com)

2023 – Present

PhD student

Massachusetts Institute of Technology (mit.edu)

2019 – 2023

MS student

Massachusetts Institute of Technology (mit.edu)

2017 – 2019

Undergrad student

National Technical University of Athens (ntua.gr)

2011 – 2016

Advisors, Relations & Conflicts

PhD Advisor

Themistoklis Sapsis

2019 – 2023

Expertise

Physics-Consistent Neural Networks

2017 – 2023

Publications

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
Implementation of a fully nonlinear Hamiltonian Coupled-Mode Theory, and application to solitary wave problems over bathymetry
Christos Papoutsellis, Alexis-Tzianni Charalampopoulos, Gerassimos Athanassoulis
- 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
Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes and their dynamics
Alexis-Tzianni Charalampopoulos, Spencer H. Bryngelson, Tim Colonius, Themistoklis P. Sapsis
- Published: 01 Jan 2021, Last Modified: 12 May 2023
- CoRR 2021
- Readers: Everyone

Alexis-Tzianni Charalampopoulos

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

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

Implementation of a fully nonlinear Hamiltonian Coupled-Mode Theory, and application to solitary wave problems over bathymetry

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

Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes and their dynamics

Co-Authors