Mehdi Ganjkhani

WORK HISTORY

EDUCATION

ABOUT MEHDI GANJKHANI

As a Data Scientist with a strong foundation in power systems engineering, machine learning, and real-time analytics, I specialize in developing intelligent, AI-driven models that support data-informed decision-making in the energy sector. At the Energy Authority (TEA), I design and implement advanced solutions that integrate big data, load forecasts, and market intelligence to optimize energy market participation, operational efficiency, and risk management for public power utilities across North America. Before joining TEA, I earned my Ph.D. in Electrical Engineering from the University of Utah, where my research focused on enhancing the resiliency and cybersecurity of power distribution systems. My doctoral work explored machine learning-based approaches for cyber-physical anomaly detection and localization, with a focus on defending against false data injection attacks on grid edge devices. I bring hands-on experience with a wide range of power system simulation tools and industrial control technologies, including OPAL-RT real-time simulators, SEL RTACs, and PLC/DCS platforms from Siemens, ABB, Yokogawa, and Delta. I’m proficient in Python, MATLAB, and R, and have built interactive visualization platforms using libraries such as Plotly and D3.js to support user-centric insights from large-scale energy data. I’m passionate about advancing grid modernization, renewable integration, and cyber-resilient infrastructure through innovative data-driven solutions. I’m always open to connecting with professionals in energy, AI, and data science—feel free to reach out here or at m••••••••@utah.edu.