Keynote Speaker
Saman Halgamuge, FIEEE, FIET, FAAIA, FNASSL
Professor
University of Melbourne, Australia
Keynote Title: AI in Energy: Applications in developing economies, supply side forecasting and the charging strategies for Electric Vehicles
Abstract:
Machine Learning is used to predict the energy demand including the impact of Electric Vehicles (EVs) on electricity grids and the decentralised energy production by consumers through renewable sources. This keynote shall focus on three problems: 1) forecasting the decentralised solar energy production 2) charging and discharging strategies for EVs that reduce the impact on the grid, and 3) AI applications of Energy in the developing world. Experience in using Machine Learning and AI methods used for time-series data analysis focussing on the above applications shall be shared.
Keynote Speaker’s Biography:
Prof Saman Halgamuge, Fellow of IEEE, IET, AAIA and NASSL received the B.Sc. Engineering degree in Electronics and Telecommunication from the University of Moratuwa, Sri Lanka, and the Dipl.-Ing and Ph.D. degrees in data engineering from the Technical University of Darmstadt, Germany. He is currently a Professor of the Department of Mechanical Engineering of the School of Electrical Mechanical and Infrastructure Engineering, The University of Melbourne. He is listed as a top 2% most cited researcher for AI and Image Processing in the Stanford database. He was a distinguished Lecturer of IEEE Computational Intelligence Society (2018-21). He supervised 50 PhD students and 16 postdocs on Sustainable Energy, AI and Biomedical Engineering in Australia to completion. His research is funded by Australian Research Council, National Health and Medical Research Council, US DoD Biomedical Research program and international industry. His previous leadership roles include Head, School of Engineering at Australian National University and Associate Dean of the Engineering and IT Faculty of University of Melbourne.