Ugochukwu Orji
Ugochukwu Orji, MSc
PhD candidate
- Research profile: Specializing in developing AI-driven models for accurate and reliable forecasting of energy demand and renewable energy sources (RES) in dynamic electricity grids.
- Research expertise: AI for Energy Forecasting, Graph Neural Networks, Uncertainty Quantification, Renewable Energy Integration, Time Series Analysis, Energy Analytics.
Biography
Ugochukwu is a PhD candidate whose research focuses on developing advanced AI models for power load and renewable energy forecasting in electricity grids, aiming to enhance forecast accuracy and reliability.
With an MSc. in Computer Science (AI Major) and having worked as an Energy Analyst, Ugochukwu has practical industrial experiences that now informs his research, leveraging deep learning algorithms, particularly Graph Neural Networks (GNNs), sequence processing models like (LSTMs) and uncertainty quantification methods, to drive innovations in energy forecasting.
Relevant academic links
Research Projects
JADS also participates in several (international) projects, which contribute to grand societal challenges like health, food security, smart transport and secure societies. Together with companies, government, NGO’s and other knowledge institutions, JADS works on solutions by using data.