Upadesh Subedi

I am Upadesh Subedi, a doctoral researcher in computational materials science. My work focuses on integrating machine learning (ML) and phase field (PF) methods to develop virtual digital twins for laser processing in multi-component alloys. My PhD project, titled "Towards Digital Twins for Quantifying Laser-Microstructure Interface in Multicomponent Alloys Using Thermodynamic Tensor Model." is funded by the National Science Centre, Poland. 

Previously, I developed GUI-based software toolkits, including pyMPEALab, and IMCATHEA, which leverage ML models to predict alloy phases and their physical properties. As a strong advocate for open-source research, I make all my research outputs, including codes and preprints, publicly available on my GitHub.

During my PhD, I received several accolades, including the University's Best PhD Student Award 2022/2023 (€8.5k) and the Departmental Research Grant for Young Scientists 2023, 2024, and 2025 (€5k).