Intensive workshop on Machine Learning and Artificial Neural Networks

The Centre for Intelligent Systems and Emerging Technologies (CISET) and the Centre for Substation Automation and Energy Management Systems (CSAEMS) recently co-hosted a successful two-day intensive workshop on the theory, implementation, and applications of machine learning and artificial neural networks.

The event, which was coordinated by Prof Senthil Krishnamurthy from the Department of Electrical, Electronic, and Computer Engineering, formed part of the French Embassy AI Frugal Grant Research Project, a collaborative initiative involving Linda Zhang from IÉSEG School of Management, France, and Thabo Keotje (National University of Lesotho), together with Krishnamurthy from CISET, CPUT.

Krishnamurthy said the workshop attracted postgraduate students, researchers, and industry professionals seeking to develop practical skills in artificial intelligence, machine learning, and neural network applications using MATLAB. “It was designed to bridge the gap between theoretical foundations and real-world engineering applications, offering hands-on experience in developing intelligent computational models.”

Head of the Department of Operations and Management and Senior Advisor to CISE, Prof Bingwen Yan, opened the two-day event where participants engaged in interactive lectures and practical sessions covering machine learning fundamentals, artificial intelligence concepts, neural network architectures, deep learning, data preprocessing, model development, and optimization techniques.

Krishnamurthy led several technical sessions focusing on neural network training, deep learning applications, the Levenberg–Marquardt algorithm, and engineering case studies in power systems and renewable energy. International expertise was contributed by Prof Bishwajit Dey from India, who covered foundational machine learning concepts and neural networks, and Dr Oludamilare Bode Adewuyi from the United States, who presented best practices in machine learning model development and energy systems applications.

Dr Carl Kriger, Senior Advisor from CSAEMS, provided insightful technical discussions and shared his experience on neural network engineering applications with delegates during the workshop.

A dedicated practical session on data processing and cleaning using MATLAB was jointly facilitated by Krishnamurthy and David Ruhaya, a Master of Engineering student, equipping participants with essential skills for preparing datasets for machine learning applications.

The workshop concluded with demonstrations of neural network applications in power systems, including transformer condition monitoring, transmission loss prediction, and photovoltaic maximum power point tracking. Participants actively engaged in practical exercises and received certificates during the closing ceremony, which was led by Prof VeruschaFester, Assistant Dean for Research, Technology Innovation and Partnerships within the Faculty of Engineering and Built Environment.

“The workshop reflects CISET’s and CSAEMS's continued commitment to advancing research capacity development in artificial intelligence, intelligent systems, smart energy technologies, and emerging digital innovations. The strong participation and engagement demonstrated growing interest in AI-driven solutions for engineering and scientific applications,” noted Krishnamurthy.

Written by CPUT News
Email: news@cput.ac.za