Learning Turbulent Flows with Generative Models: Super-resolution, Forecasting, and Sparse Flow Reconstruction
Nature Communications Journal article
Scholarship
Publications & software.
Explore work in neural operators, scientific machine learning, physics-informed modeling, and generative AI. View Google Scholar ↗
23 publications
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Inception UNet (IUNet) and Multi-scale Multi-branch (M&M) UNet Plug-In Neural Operators for Online Bias Correction in E3SM.
Journal of Computational Physics Journal article
Journal article · 2026; link to earlier preprint
Improved nudging strategy for constraining humidity and temperature fields in the E3SM Atmosphere Model.
Geoscientific Model Development Journal article
Process-informed forecasting of complex thermal dynamics in pharmaceutical manufacturing.
Under review at Neural Networks Submitted / draft
Under review
When Known Physics Helps Neural PDE Models: Residual Constraints Out-Regularize Generic Priors for Nonlinear Dynamics.
Submitted to ICLR 2027 Submitted / draft
Submitted · preprint
Physics-informed offline reinforcement learning eliminates catastrophic fuel waste in maritime routing.
Submitted to Scientific Reports Submitted / draft
Submitted · preprint
Enhancing Heat Sink Efficiency in MOSFETs using Physics-Informed Neural Networks: A Systematic Study on Coolant Velocity Estimation.
Submitted to International Journal of Heat and Mass Transfer Submitted / draft
Submitted · preprint
Artificial Neural Network Method for Solving Phase Lagging Heat Transport Equation.
Manuscript in preparation Submitted / draft
In preparation
Integrating neural operators with diffusion models improves spectral representation in turbulence modeling
Proceedings of the Royal Society A Journal article
Characterization and Inverse Design of Stochastic Mechanical Metamaterials Using Neural Operators
Advanced Materials Journal article
An Artificial Neural Network Method for Simulation of Wave Propagation Based on the Rosenau-KdV-RLW Equation on Unbounded Domain.
Mathematics, 13(7), 1036 Journal article
Mitigating spectral bias in neural operators via high-frequency scaling for physical systems
Neural Networks Journal article
XAI4Climate: Attributing the role of climate change on extreme-weather precursors via interpretable machine learning.
Tackling Climate Change with Machine Learning, ICLR Workshop Conference / workshop
XAI4Extremes: An explainable AI framework for understanding extreme-weather precursors
AI4X 2025 International Conference Conference / workshop
A physics-informed neural network method for thermal analysis in laser-irradiated 3D skin tissues with embedded vasculature, tumor and gold nanorods.
International Journal of Heat and Mass Transfer, 245, 126980 Journal article
TransformerG2G: Learning temporal graph embeddings with long-range historical information.
Neural Networks, 172, 106086 Journal article
Physics-Informed Deep Neural Operator Networks
Machine Learning in Modeling and Simulation: Methods and Applications, pp. 219–254, Springer Book chapter
Learning bias corrections for climate models using deep neural operators
AAAI Spring Symposium Series Conference / workshop
Neural network method for solving nonlocal two-temperature nanoscale heat conduction in gold films exposed to ultrashort-pulsed lasers
International Journal of Heat and Mass Transfer, 190, 122791 Journal article
A New Artificial Neural Network Method for Solving Schrödinger Equations on Unbounded Domains
Communications in Computational Physics, 32, 1039–1060 Journal article
Neural Network Method for Solving Parabolic Two-Temperature Microscale Heat Conduction in Double-Layered Thin Films Exposed to Ultrashort-Pulsed Lasers
International Journal of Heat and Mass Transfer, 178, 121616 Journal article
Gradient preserved method for solving heat conduction equation with variable coefficients in double layers
Applied Mathematics and Computation, 386, 125516 Journal article
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Interested in research collaboration or joining SPARKS Lab? I welcome conversations across computer science, mathematics, physics, and engineering.
aniruddha_bora@txstate.edu ↗
Department of Computer Science · Texas State University
310D Comal · San Marcos, Texas 78666