Research experience in graph machine learning on heterogeneous knowledge graphs, including graph neural networks, graph transformers, link prediction, node classification, and graph self-supervised learning (e.g., masked graph autoencoders, joint-embedding predictive architectures (JEPA)). Currently pursuing a PhD in Computer Science, Machine Learning, Data Science, Civil Engineering, Construction Informatics, or a related field with a graduation date no sooner than April 2027.