Details of my PhD work can be found in this page.
Research Projects I’ve Been Involved In
Mathematical modeling and numerical simulation of interface-coupled models of biodegradation behavior of metallic implants and medical devices
KU Leuven, 2018–2022
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Mathematical modeling and numerical simulation of bone tissue growth process on 3D scaffolds
KU Leuven and University of Liege, 2019–2021
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Numerical modeling of oxygen consumption and cell viability for pancreatic islets
KU Leuven & Maastricht University, 2019–2021
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Development of coupled models of topology optimization and metals corrosion for optimizing the shape of biodegradable medical devices
KU Leuven & Kyoto University, 2021–2022
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Development of open-source software BioDeg for massively-parallel simulation of biodegradation and corrosion of metallic biomaterials
KU Leuven, 2020–2022
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Contribution to the development of open-source software ASLI for creating TPMS-based functionally graded scaffolds and implants
KU Leuven, 2020–2022
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Contribution to the web app development of the Skeletal Cell Atlas project
KU Leuven, 2020–2022
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Contribution to the development of open-source software TFMLab for traction force microscopy calculations of cellular movements
KU Leuven, 2020
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Numerical modeling of foam formation process using Lattice Boltzmann method and multiphase fluid simulation
Amirkabir University of Technology, 2013–2017
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Development of in-house CFD codes for simulating fluid flow and heat transfer in metal casting process
Amirkabir University of Technology, 2008–2011
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Development of coupled models of deep reinforcement learning and multiphysics parallel CFD for thermal shape optimization
KU Leuven & University of Waterloo, 2021–2022
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Development of physics-informed neural network models to solve governing equations of tissue engineering processes (cell growth and oxygen consumption)
KU Leuven, 2020–2022
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Development of Privacy-Preserving Deep Learning models using Federated Learning and Differential Privacy for healthcare IoT systems
KU Leuven & Duke University, 2019–2020
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Implementation of Machine Learning models for signal processing and anomaly detection of EEG and ECG signals
KU Leuven & Imec, 2018–2019
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