Grid AI · Electric Utilities IT/OT · Data Engineering
Building AI solutions for Electric Utilities IT/OT. Power systems engineer turned production AI/data leader — from IEEE-published grid research at Waterloo to deploying LLM pipelines at Hydro One. Ex–Big 5 banks.
I'm a Data & AI Engineer with a rare combination: a formal electrical engineering background in power systems (BUET, Waterloo ECE) and deep hands-on experience building production ML and data pipelines in industry.
My research spans power quality analysis, EV wireless charging, connected autonomous vehicles, and machine learning for AC optimal power flow — all published and cited in IEEE venues and Springer.
My career spans electric utilities (Hydro One), Big 5 banking (RBC), and academic research — giving me an unusually broad perspective on production AI systems, regulated data environments, and critical infrastructure.
Applying machine learning to power system problems — from ML for AC optimal power flow (IEEE-9 bus) to EV charging infrastructure design. Bridging domain physics with data-driven models.
Built and deployed LLM-based NLP pipelines using locally-run Mistral 7B for intent classification on enterprise contact center data. Full lifecycle: prompt engineering, GGUF optimization, Parquet I/O.
Led cloud data migration and platform engineering on Azure + Snowflake, including medallion architecture, RBAC design, and ingestion pipelines from multiple API sources into a modern data warehouse.
I'm actively exploring Grid AI, ML Engineering, and Data Engineering roles at energy software companies, utilities, and grid tech startups. If your team sits at the intersection of power systems and data — let's talk.