Mohamad Riad Salman

- Developing a deep learning framework for day-ahead wind power forecasting under data-scarcity conditions using Transfer Learning (TL) and Continual Learning (CL). - Designing and optimizing LSTM-based forecasting models for sequential meteorological and wind-power time-series prediction. - Implementing feature-extraction transfer learning to transfer temporal knowledge between wind turbines with limited historical data. - Investigating the impact of source–target similarity on transfer learning performanc

. Academic Support: Assisting students with subject-related questions and study content . Study Organization Guidance: Offering advice on time management, learning strategies, and exam preparation . Introduction to University Platforms: Guiding students in using Moodle, campus management systems, and university email . Support with Scientific Work: Helping with LaTeX, citation formats, and literature research . Mentoring & Motivation: Providing support during challenging academic phases and promoting st

- Developed ML–based wind power forecasting models using real-world SCADA and numerical weather prediction (GFS-US) data from multiple wind turbine sites. - Designed and implemented non-linear neural network models in Python using PyTorch framework to predict short-term wind power output. - Performed data preprocessing and feature engineering on large-scale NetCDF datasets, including normalization, chronological splitting, and outlier handling. - Applied Transfer Learning to improve forecasting performan

Handling Large Action Spaces for Power Grid Topology Optimization - Developed AI-based methods for power grid topology optimization to enhance grid stability and prevent cascading failures. - Modeled substation reconfiguration and remedial actions as a large discrete action space problem in electrical power networks. - Designed and implemented Genetic Algorithms (GA) to efficiently reduce and explore large action spaces for grid control agents. - Integrated Reinforcement Learning concepts with evolution

Senior Project: PID Room Temperature Control System Control Systems: Applied control engineering concepts including feedback controller design, system modeling, and dynamic response analysis. Electronics: Worked with electronic circuits, microcontrollers, sensors, and power semiconductor devices