About Me
I am a Transportation Engineer and registered Engineer-in-Training (EIT) with a multidisciplinary background in Industrial Engineering, experienced in optimization for bus and rail transit systems using machine learning methods and AVL, APC, AFC, and GTFS data. I have taken transportation initiatives from data-driven analysis through to executive-approved strategy, including leading the University of Calgary's first campus EV charging infrastructure strategy planning, feasibility analysis, cost-recovery modeling, and rollout presentation to senior leadership. I combine deep domain expertise with technical fluency to translate complex operational data and KPIs into clear, actionable insights for diverse stakeholders, with hands-on experience across Canadian, Australian, New Zealand, Polish, and Iranian transit networks.
Professional Affiliations: Engineer-in-Training (EIT), Association of Professional Engineers and Geoscientists of Alberta (APEGA) · Member, Institution of Civil Engineers (ICE)
Core Competencies
Transportation & Rail Systems
Transit and rail operations planning, network/schedule performance analysis, service reliability and resilience, and rail dwell-time and infrastructure planning studies across Canadian, Australian, New Zealand, Polish, and Iranian transit networks.
Strategic Delivery & Leadership
Led infrastructure strategy planning end-to-end; experienced coordinating cross-functional stakeholders, mentoring junior researchers as a thesis advisor, and presenting technical findings to non-technical audiences.
Deep Reinforcement Learning & Optimization
Deep Reinforcement Learning (DRL) for real-time transit control (holding, stop-skipping, speed adjustment), quantum and quantum-inspired optimization (QUBO/QUDO), mixed-integer programming, and metaheuristics (GA, NSGA-II).
Tools & Platforms
Python, R, MATLAB; Power BI, Tableau, ArcGIS; PTV Visum, EMME; Streamlit dashboard development; AWS/Azure cloud services.