Date: 09 July 2026 A seminar on Machine Learning-Based Electricity Consumption Prediction was held. As part of the weekly scientific seminars of Doğuş University Faculty of Engineering and Natural Sciences, we hosted Dr. Menekşe Yeşim Çakırlı at our faculty on June 25, 2026. In her seminar titled “An Integrated Approach to Machine Learning-Based Electricity Consumption Forecasting and Cost-Emission Optimization,” the importance of accurately forecasting electricity demand for the efficient operation of energy production and distribution systems was discussed. The seminar compared the forecasting performance of Linear Regression, Decision Tree, Random Forest, Extra Trees, and XGBoost algorithms using hourly electricity consumption data for Istanbul. The success of models developed through data preprocessing, feature engineering, time series validation, and hyperparameter optimization processes was evaluated. Furthermore, an approach to integrating the obtained demand forecasts into a linear programming-based optimization model for use in energy production planning was shared. The contributions of machine learning methods to energy production planning, cost management, emission optimization, and decision support systems were discussed. We thank Dr. Çakırlı for her contributions. We would like to thank Menekşe Yeşim Çakırlı, and all the academics and students who participated.