Ashesh Chattopadhyay

Assistant Professor

University of California, Santa Cruz

United States

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Ashesh Chattopadhyay is an Assistant Professor at the University of California, Santa Cruz, United States. His research focuses on the integration of machine learning and data assimilation in meteorology and turbulence modeling. Recent work includes developments in interpretable structural model errors, data-driven weather forecasting, and the application of deep learning in climate-related studies.

Articles (10)

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2022

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2022

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2022

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2021

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2021

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2021

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2020

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2020

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2020

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2020

Collaborators (5)

Eviatar Bach

California Institute of Technology

UNITED STATES

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Devika Subramanian

Professor

Rice University

UNITED STATES

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Rambod Mojgani

Rice University

UNITED STATES

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Yifei Guan

Assistant Professor

Union College

UNITED STATES

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Jin-Long Wu

UNITED STATES

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Ashesh Chattopadhyay

Research Interests

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Articles (10)

Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case

Stable a posteriori LES of 2D turbulence using convolutional neural networks: Backscattering analysis and generalization to higher Re via transfer learning

Towards physics-inspired data-driven weather forecasting: Integrating data assimilation with a deep spatial-transformer-based U-NET in a case study with ERA5

Data-driven subgrid-scale modeling of forced Burgers turbulence using deep learning with generalization to higher Reynolds numbers via transfer learning

Physics-informed machine learning: Case studies for weather and climate modelling

Transfer learning of deep neural networks for predicting thermoacoustic instabilities in combustion systems

Analog Forecasting of Extreme-Causing Weather Patterns Using Deep Learning

Data-Driven Super-Parameterization Using Deep Learning: Experimentation With Multiscale Lorenz 96 Systems and Transfer Learning

Data-driven predictions of a multiscale Lorenz 96 chaotic system using machine-learning methods: Reservoir computing, artificial neural network, and long short-term memory network

Predicting clustered weather patterns: A test case for applications of convolutional neural networks to spatio-temporal climate data

Collaborators (5)

Eviatar Bach

Devika Subramanian

Rambod Mojgani

Yifei Guan

Jin-Long Wu

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