Umit Cali

About

Umit Cali is a Professor / Chair in Digital Engineering for Future Technologies in University of York, UK and Professor (part time) of Energy Informatics at NTNU. Umit Cali is a technology researcher conducting academic-based research activities in energy analytics, blockchain, and economics. Umit has 20 years international experience in the fields of energy systems, data science, blockchain technologies, ICT, energy markets and economics. He has worked for IBM International (Istanbul/Turkey) as a network engineer and project manager, a senior researcher in energy informatics and economics (Fraunhofer Institute – Germany), an Energy Consultant (Lahmeyer International- Germany), a Manager in wind energy project development and energy markets/energy economics (EnBW –Utility in Germany), Chief Technology Officer for an international service provider in energy efficiency (KREEN Renewables GmbH- Germany/Switzerland) and assistant professor in three universities (Gediz University- Turkey, the University of Wisconsin at Platteville and the University of North Carolina at Charlotte).

He serves as Vice Chair of the IEEE Blockchain in Energy Standards WG (P2418.5).

Employment

• University of York Professor of Digital Engineering
  2024 - Present
• Norwegian University of Science and Technology
  2020 - Present
• University of North Carolina at Charlotte Assistant Professor
  2016 - 2020

Education

• University of Kassel Dr-Ing
  2005 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (79)

• A review of community-centric power system resilience: Strategies, data-driven methods, and techno-legal perspectives
  Electric Power Systems Research 2026 DOI: 10.1016/j.epsr.2026.113285
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• An interpretable and uncertainty-aware hybrid framework for short-term load forecasting in modern energy systems
  Energy Reports 2026 DOI: 10.1016/j.egyr.2026.109462
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• Virtual Power Plants in Modern Power Systems: A Comprehensive Review of Uncertainty Management and Market Bidding Strategies
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3691418
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• Feasibility Analysis of PV-Wind-Based EMS for Grid-Tied Battery Storage System Under Variable Atmospheric Scenario
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3697163
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• Energy-aware hierarchical fractional-order terminal sliding mode control with hybrid learning observer for enhanced gait comfort in active prosthetics
  Biomedical Signal Processing and Control 2026 DOI: 10.1016/j.bspc.2025.108933
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• Optimizing cost and reliability in off-grid microgrids: A hybrid paradigm utilizing k-medoids for scenario reduction
  Energy Conversion and Management: X 2026 DOI: 10.1016/j.ecmx.2026.101848
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• Towards reliable solar power forecasting in Sub-Saharan Africa: An explainable hybrid AI approach for Chad
  Energy Reports 2026 DOI: 10.1016/j.egyr.2025.108997
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• Cyber-resilient control based on soft reinforcement learning for inverter-based PV/FC systems: Real-time implementation and validation
  Energy Reports 2026 DOI: 10.1016/j.egyr.2026.109241
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• Comparative analysis of AI-based regression models for solar power forecasting: Techniques, preprocessing, and evaluation
  Energy Reports 2026 DOI: 10.1016/j.egyr.2026.109071
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• A multi-layered framework for stability analysis in power grids with incomplete harmonic data
  Energy Reports 2026 DOI: 10.1016/j.egyr.2026.109281
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