Summary
Nawshad Farruque is an AI research fellow with 13 years of experience bridging academic rigor and production-grade engineering to build transparent, interpretable AI systems. Based in Edmonton, he has driven AI and computational analytics projects at the Edmonton Police Service and AMII, and completed a PhD focused on AI-powered mental health modeling. He is hands-on with PyTorch, TensorFlow, scikit-learn, Pandas, Databricks and LangChain, and has a history of shipping practical software—from Moodle plugins and e-learning analytics to high-performance reporting systems. Nawshad combines deep domain modeling skills with a pragmatic engineering mindset, often translating complex research into auditable, deployable solutions for public-sector and healthcare contexts. Beyond core ML, he brings full-stack experience and a track record of optimizing real-world workflows, such as dramatically speeding SCORM reporting and building configurable themes to reduce deployment time. Colleagues describe him as a researcher who deliberately hunts for the smallest insight that unlocks larger, explainable system improvements.
13 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy - PhD, Artificial Intelligence, Outstanding thesis award nominee, Doctor of Philosophy - PhD, Artificial Intelligence, Outstanding thesis award nominee at University of Alberta
BSc, Computer Science and Information Technology, BSc, Computer Science and Information Technology at Islamic University of Technology
MSc (Thesis), Computer Science, MSc (Thesis), Computer Science at The University of Lethbridge
English, Bengali