Associate Professor Hamid Khayyam earned his B.Sc. (Hons.) from the University of Isfahan, his M.Sc. from the Iran University of Science and Technology, and his Ph.D. from Deakin University. With over a decade of experience in automation and energy productivity across various industrial companies, Dr. Khayyam previously led efforts at Deakin University on modeling, control, and optimization of energy systems for the carbon fiber production line at Carbon Nexus.
Currently, Dr. Khayyam is an Associate Professor in the School of Engineering at RMIT University. He has made significant scholarly contributions, including over 130 articles published in professional journals and conferences, 4 books as sole editor, 10 book chapters, and editorial or reviewer roles for more than 400 journal papers. Dr. Khayyam also serves on the editorial boards of several Q1-ISI journals. His research focuses on developing innovative technologies that integrate Artificial Intelligence and Machine Learning to address complex systems, creating simplified and procedural solutions for end-users.
Associate Professor Khayyam has been recognized among the Top 2% of World Scientists by Stanford University and Elsevier in the fields of Applied Sciences – Enabling and Strategic Technologies and Energy from 2019 to the present .
Dr. Khayyam is an academic member of the Intelligent Automation Research Group (IARG) at RMIT as well as The Materials and Manufacturing Research Institute (MMRI) at The University of British Columbia in Canada.
During the past 10 years of his service in academia, he has collaborated with several universities including The Ohio State University, Texas A&M University, National University of Singapore, The University of British Columbia, and FH Aachen universities.
As an HDR supervisor, Associate Professor Khayyam has successfully supervised the graduation of 14 Ph.D. students, who are now contributing to academia and industry. Currently, he leads a team comprising 14 Ph.D. students and two research fellows, focused on solving complex systems in engineering subjects.
Dr. Hamid Khayyam has over ten years of experience in automation and energy productivity, working with several large-scale industrial companies.
In his previous role, he led efforts on machine learning modeling, control, and intelligent optimization of energy systems for the carbon fiber production line at Carbon Nexus, Deakin University.
Associate Professor Khayyam has secured more than $12 million in research funding from the ARC, CRCs, and industry-sponsored projects, including:
1- ARC Training Centre in Electrifying Australia for a Net-zero Future - $6.6 million
2- NexusCharge: Intelligent Charging and Fleet Management for Electric Vehicles $4.7 million
3- A Data-Driven Optimisation Approach to Enhance Energy Efficiency of the Metropolitan Railway Traction Power Systems $0.5 million
Professional Interests:
- Senior Member of IEEE and actively involved in Power and Energy and Intelligent Transportation Systems Societies.
- Editor of IEEE Transaction on Vehicular Technology.
- Editor of IEEE Transaction on Intelligent Transportation Systems.
- Reviewers of IEEE TVT, ITS, TIE, TII, Nano Energy.
- Organizing Committee and Member of the Academic Board for more than 10 international conferences.
Mechanical Engineering, Automotive Engineering, Electrical Engineering, Manufacturing Engineering, Cognitive Science such as AI and Machine Learning.
Modelling, Control and Optimization of Complex Engineering Systems: Energy and Power, Autonomous Vehicle/ Robots, Vehicle to X, EV, HEV, Internet of Vehicle and ITS. Artificial Intelligence, Machine Learning and Adaptive Intelligent Systems. Limited and Big Data Modelling, Industry 4.0.
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