Summary
Sirajum Prince is a machine learning researcher and software engineer with nine years of experience, blending deep learning research (MS in Computer Science) with practical full‑stack and data-driven systems delivery. He has developed and optimized graph neural network models—publishing two papers and submitting two more—focusing on few-shot and contrastive learning that improved node classification accuracy by 7–35% on large graphs. In parallel he has built production software and analytics, from a full‑stack loan processing system that boosted productivity and cut reporting costs to cross‑platform mobile apps and automated credit-risk reporting. Comfortable in Python, PyTorch, PyTorch Geometric, TensorFlow, Flutter/Dart, and ASP.NET Core, he bridges academic rigor and operational impact. Currently based in St. Catharines, Ontario, he balances graduate research and teaching with seasonal work in tax preparation, demonstrating a pragmatic, results‑oriented approach to complex problems. Notably, his research on defending federated graph neural networks improved resilience against backdoor attacks, showing attention to robustness as well as accuracy.
9 years of coding experience
1 year of employment as a software developer
High School, Science, High School, Science at Dhaka College
Bachelor's degree, Computer Science & Engineering, Bachelor's degree, Computer Science & Engineering at Ahsanullah University of Science and Technology
Master's degree, Computer Science, Master's degree, Computer Science at Brock University
High School, Science, High School, Science at Monipur High School & College
English, Bengali