Machine Learning and Neural Network Applications in Engineering

Scope

This symposium is designed for undergraduate and graduate students, researchers, academicians, and industry professionals interested in Artificial Intelligence, machine learning, and engineering applications. The session will cover machine learning fundamentals, neural network concepts, deep learning techniques, and major architectures such as CNNs, RNNs, LSTMs, and Transformers. Participants will learn how machine learning and neural network methods are applied in predictive maintenance, fault detection, energy forecasting, reservoir modeling, smart manufacturing, autonomous systems, and infrastructure monitoring.

The symposium will include visual presentations, engineering case studies, workflow diagrams, and application-oriented discussions to provide practical insight into AI and machine learning implementation in engineering systems. Basic knowledge of mathematics and programming is beneficial but not mandatory. By the end of the symposium, participants will gain foundational knowledge of machine learning and neural networks and understand how AI technologies are shaping the future of engineering research, industrial automation, intelligent systems, and data-driven decision-making.