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Themistoklis Sapsis

Assistant Professor

Massachusetts Institute of Technology

United States

Research Interests

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Articles (20)

Collaborators (4)

Malin Göteman

Uppsala University

Dixia Fan

Assistant Professor

Westlake University

Spencer Bryngelson

Associate Prof

University of Texas at Austin

UNITED STATES

Ioannis G. Kevrekidis

Johns Hopkins University

UNITED STATES

ApplyKite TwinLearns as you apply

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Themistoklis Sapsis

Research Interests

Make your next move.

Explore related searches

Articles (20)

Collaborators (4)

Malin Göteman

Dixia Fan

Spencer Bryngelson

Ioannis G. Kevrekidis

Make your next move.

Themistoklis Sapsis

Research Interests

Make your next move.

Explore related searches

Articles (20)

Learning dissipative chaotic dynamics with boundedness guarantees

Extreme Event Aware (η-) Learning

A Probabilistic Framework for Learning Non‐Intrusive Corrections to Long‐Time Climate Simulations From Short‐Time Training Data

Reduced order modeling of wave energy systems via sequential Bayesian experimental design and machine learning

Active search for bifurcations

Deep learning vortex-induced vibrations: Time-space forecasting with transformers

Reconstructing Ocean Flow from Observed Lagrangian Trajectories

Data‐Driven Modeling of 4D Ocean and Coastal Acidification in the Massachusetts and Cape Cod Bays From Surface Measurements

Sampling Low-Fidelity Outputs for Estimation of High-Fidelity Density and Its Tails

Can diffusion models capture extreme event statistics?

Harnessing Instability Mechanisms in Airfoil Flow for Data-Driven Forecasting of Extreme Events

Discovering and forecasting extreme events via active learning in neural operators

Data-driven prediction and study of vortex induced vibrations by leveraging hydrodynamic coefficient databases learned from sparse sensors

Wave episode based Gaussian process regression for extreme event statistics in ship dynamics: Between the Scylla of Karhunen–Loève convergence and the Charybdis of transient features

Hybrid quadrature moment method for accurate and stable representation of non-Gaussian processes applied to bubble dynamics

Optimal criteria and their asymptotic form for data selection in data-driven reduced-order modelling with Gaussian process regression

Optimized parametric hydrodynamic databases provide accurate response predictions and describe the physics of vortex-induced vibrations

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

Generative Stochastic Modeling of Strongly Nonlinear Flows with Non-Gaussian Statistics

Output-weighted sampling for multi-armed bandits with extreme payoffs

Collaborators (4)

Malin Göteman

Dixia Fan

Spencer Bryngelson

Ioannis G. Kevrekidis

Make your next move.