I am an MPhil researcher in Artificial Intelligence at Curtin University, Australia, with a focus on the application of machine learning in materials science, specifically metal–organic frameworks (MOFs) for hydrogen storage.
Projects
MOF
Deep Learning for Hydrogen Storage Prediction in MOFs
Developed a deep learning framework to predict hydrogen storage performance in MOFs by integrating structural and chemical features. Designed and evaluated multiple neural network architectures and implemented a multi-task learning strategy to measure storage metrics across conditions. Surfaced high-performing materials and structure–property insights to guide data-driven discovery for clean energy applications.
TBD
Project 2
In Progress...
Skills
Python
Pandas
NumPy
Scikit-learn
PyTorch
Feature Engineering
Model Evaluation
Predictive Modeling
GNN
Data Analysis
Matplotlib
Seaborn
Jupyter Notebook
R
Tableau
PostgreSQL
JIRA
Git
Education
02/2025 – Present
Curtin University – Master of Philosophy (Computing)
02/2024 – 12/2024
Curtin University – Master of Computing (Artificial Intelligence)
02/2023 – 12/2023
Curtin College – Masters Qualifying Program
