Ugur Halden

Conducted strategic modeling and techno-economic assessments of national energy systems, forecasting costs under various scenarios. Engineered AI-driven automation, implementing multi-agent systems (LangChain, RAG) and LLM solutions that reduced report generation from 8 hours to 15 minutes. Built FastAPI backends with ML models and developed interactive Power BI dashboards to translate complex data into actionable business intelligence for stakeholders.

Collaborated with major energy firms like Statnett to develop and productionize AI solutions, including cybersecurity POCs for national grid monitoring involving threat modeling and defense algorithms. For Hafslund, deployed a predictive maintenance model, reducing downtime by 45% and saving €280K annually. Built explainable energy forecasts, awarded the Microsoft AI for Earth Award. Implemented end-to-end MLOps pipelines (Azure DevOps, Docker, Kubernetes) for scalable, robust AI systems.

Delivered AI/ML features in cross-functional agile teams for customer-facing SaaS applications. Architected and deployed scalable production AI solutions, designing ETL pipelines for Power BI/Tableau dashboards and implementing CI/CD with Docker/Kubernetes. Developed KPI frameworks and visualization logic to translate data into actionable business intelligence.

Developed and productionized AI models using sensor data (CO₂, humidity) to infer building occupancy for HVAC control and energy optimization. Applied ML techniques, including Hidden Markov Models, to estimate human presence and behavior patterns. Created Python dashboards for data visualization and operational insights, contributing to smarter, more efficient buildings.

Applied physics-based modeling and ANSYS analysis for offshore wind turbines, performing critical load and buoyancy calculations. Modeled AI-based wake losses and optimized cable layouts to enhance energy yield. Developed early insights into integrating data-driven simulations with mechanical modeling for renewable energy infrastructure.

Conducted production efficiency and supply chain analysis for Enercon E-126 wind turbine manufacturing. Evaluated SCADA system interfaces from a cybersecurity perspective, developing an early understanding of OT/IoT and cyber-physical security in critical energy infrastructure. Bridged industrial engineering with security principles.

Evaluation of sonochemically grown 1 dimensional ZnO Nanostructures. Helping of peer-reviewing of scientific papers. Project documentation and presentation for business partners. Implementation of manufactures ZnO nanostructures to CO sensors.

PhD Thesis Title: Advancing Power Systems: Harnessing the Potential of Artificial Intelligence and Distributed Ledger Technology

Building energy efficiency, Smart grids, Energy Informatics.

Renewable energy technologies, Data analysis, Electrical engineering.