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Mehdi Mahdaviara

Utrecht University

Research Interests

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Articles (14)

Collaborators (3)

Amir Raoof

Associate Professor

Utrecht University

Nima Shokri

Hamburg University of Technology

Patrick Huber

Professor and Institute Director

Universität Hamburg

ApplyKite TwinLearns as you apply

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Mehdi Mahdaviara

Research Interests

Make your next move.

Explore related searches

Articles (14)

Collaborators (3)

Amir Raoof

Nima Shokri

Patrick Huber

Make your next move.

Mehdi Mahdaviara

Research Interests

Make your next move.

Explore related searches

Articles (14)

Combined Effects of Salt and Microplastics on Evaporation and Crystallization Dynamics in Porous Media

Improving numerical fluid flow modeling by resolving under-resolution pores from X-ray images of porous media: a hybrid deep reinforcement learning framework

Capsule Network for Prediction of Permeability Tensor from X-ray Images of Porous Media

Soft computing models for predicting polymer viscosity across wide thermal and ionic-strength conditions

Improving Numerical Fluid Flow Simulation by Ring Artifact Removal in Micro-CT Images of Porous Media Using Attention Autoencoder–Decoders

Segmentation of two-phase flow X-ray tomography images to determine contact angle using deep autoencoders

PoreSkel: Skeletonization of grayscale micro-CT images of porous media using deep learning techniques

Deep learning for multiphase segmentation of X-ray images of gas diffusion layers

PoreSeg: An unsupervised and interactive-based framework for automatic segmentation of X-ray tomography of porous materials

Prediction of spontaneous imbibition in porous media using deep and ensemble learning techniques

On the evaluation of the interfacial tension of immiscible binary systems of methane, carbon dioxide, and nitrogen-alkanes using robust data-driven approaches

On the evaluation of permeability of heterogeneous carbonate reservoirs using rigorous data-driven techniques

Toward evaluation and screening of the enhanced oil recovery scenarios for low permeability reservoirs using statistical and machine learning techniques

Smart learning strategy for predicting viscoelastic surfactant (VES) viscosity in oil well matrix acidizing process using a rigorous mathematical approach

Collaborators (3)

Amir Raoof

Nima Shokri

Patrick Huber

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