Romit Maulik

Assistant Professr

Pennsylvania State University

United States

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Research Interests

Fluid Mechanics

40%

Aerodynamics

30%

Large Eddy Simulation

30%

Atmospheric Dynamics

20%

Uncertainty Analysis

20%

Environmental Physics

20%

Computational Physics

20%

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Articles20

Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems

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Year:

2025

Leveraging interpolation models and error bounds for verifiable scientific machine learning

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2025

Differentiable turbulence: Closure as a partial differential equation constrained optimization

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2025

Scientific machine learning for closure models in multiscale problems: A review

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2025

Augmenting insights from wind turbine data through data-driven approaches

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2024

Data-driven physics-informed neural networks: A digital twin perspective

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2024

Robust experimental data assimilation for the Spalart-Allmaras turbulence model

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2024

Divide and conquer: Learning chaotic dynamical systems with multistep penalty neural ordinary differential equations

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2024

Politics of problem definition: Comparing public support of climate change mitigation policies using machine learning

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2024

Reduced-order modeling on a near-term quantum computer

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2024

Differentiable physics-enabled closure modeling for Burgers’ turbulence

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2023

Quantifying uncertainty for deep learning based forecasting and flow-reconstruction using neural architecture search ensembles

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Year:

2023

Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

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2022

Efficient data acquisition and training of collisional-radiative model artificial neural network surrogates through adaptive parameter space sampling

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2022

Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression

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2022

PythonFOAM: In-situ data analyses with OpenFOAM and Python

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2022

Learning the temporal evolution of multivariate densities via normalizing flows

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2022

Machine learning accelerated turbulence modeling of transient flashing jets

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Year:

2021

Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning

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Year:

2021

Simple, low-cost and accurate data-driven geophysical forecasting with learned kernels

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Year:

2021

Collaborators9

David Schmidt

University of Massachusetts Amherst

UNITED STATES

Qi Tang

Assistant Professor

Georgia Institute of Technology

UNITED STATES

S. Ashwin Renganathan

Assistant Professor

The Pennsylvania State University - University Park Campus

UNITED STATES

Giacomo Valerio Iungo

Assistant Professor

University of Texas at Dallas

UNITED STATES

Nathan Garland

Griffith University

AUSTRALIA

S. Letizia

UNITED STATES

Kwanjung Yee

Seoul National University

SOUTH KOREA

Namwoo Kang

Assistant Professor

Korea Advanced Institute of Science and Technology

SOUTH KOREA

Venkatasubramanian Viswanathan

Associate Professor

Carnegie Mellon University

UNITED STATES

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