DB
Dr. BIVAS BHAUMIK
Hebrew University of Jerusalem, National Institute of Technology Rourkela, University of Calcutta, Institute of Engineering & Management
0000-0002-3168-2687
About
Traditional approaches often rely on empirical models or numerical methods by considering simplified assumptions, which may have limitations in capturing complex phenomena accurately. The main objective of my work is to leverage the power of Physics-Informed Machine Learning (PIML) algorithms to enhance non-linear blood flow models and address multi-physics problems related to cardiovascular dynamics.
Employment
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Hebrew University of Jerusalem Postdoc Fellow2026 - Present
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National Institute of Technology Rourkela Assistant Professor2024 - 2026
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Institute of Engineering & Management Assistant Professor2023 - 2024
Education
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University of Calcutta Ph.D.2018 - 2023
Projects & Funding
Projects & funding information is unavailable.
Publications (18)
- Micropolar Blood Flow Through a Stenosed Artery With Nanoparticle Aggregation and Variable Electrical Conductivity in a Porous Medium Save
- A refined physics-informed neural network framework for solving nonlinear partial differential equations and extracting analytical expressions via symbolic regression Save
- Modeling and prediction of Carreau fluid flow with generalized thermal conductivity using hybrid artificial neural network and symbolic regression Save
- Peristaltic transport of non-Newtonian hybrid nanofluid flow through an inclined porous tube under a magnetic field and thermal radiation in a fuzzy environment Save
- Mathematical and neural network analysis of peristaltic flow of a second-grade fractional hybrid nanofluid with variable viscosity in bifurcated arteries Save
- Physics-informed neural network with symbolic regression for deriving analytical approximate solutions to nonlinear partial differential equations Save
- Impacts of variable magnetic field on ternary Casson nanofluid flow through ciliated arterial walls incorporating interfacial nanolayer Save
- Nanoparticle aggregation and electro-osmotic propulsion in peristaltic transport of third-grade nanofluids through porous tube Save
- Deep learning based solution of nonlinear partial differential equations arising in the process of arterial blood flow Save
- Integrating symbolic regression with physics-informed neural networks for simulating nonlinear wave dynamics in arterial blood flow Save