Professor Mohammad FARD
Professor
Details
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College: School of Engineering
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Department: School of Engineering
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Campus: Bundoora East Australia
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mohammad.fard@rmit.edu.au
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ORCID: 0000-0002-5242-9162
Open to
- Masters Research or PhD student supervision
About
Mohammad Fard is a professor of Mechanical Engineering and Intelligent Systems at RMIT University. He leads a research team investigating advanced technology, including sound pattern recognition and sound source localisation using artificial intelligence. His team has utilised human bio-signals and artificial intelligence to create driver monitoring systems. Mohammad is also leading an industry project to develop an advanced crash simulation platform for Formula One racing track safety. Mohammad’s cross-disciplinary research team from the schools of Engineering, Health and Biomedical Sciences, and Science achieved a significant international media coverage of their research on the effects of road vibration on driver drowsiness and road safety.
Mohammad received his PhD from the Laboratory of Intelligent Control Systems, Tohoku University, Japan, in 2003. He worked at the Nissan Technical Centre on vehicle body design as a lead engineer for six years. With his international industry and academic experience, Mohammad leads a successful research team at RMIT University.
Research areas
Autonomous vehicles
Advanced Vehicle Crash Safety
Driver State Monitoring and Simulation
Sound Pattern Identification Using Deep Learning and Audio Fingerprinting
Application of AI Technology in Noise and Vibration
Human Factors and Ergonomics
Mohammad received his PhD from the Laboratory of Intelligent Control Systems, Tohoku University, Japan, in 2003. He worked at the Nissan Technical Centre on vehicle body design as a lead engineer for six years. With his international industry and academic experience, Mohammad leads a successful research team at RMIT University.
Research areas
Autonomous vehicles
Advanced Vehicle Crash Safety
Driver State Monitoring and Simulation
Sound Pattern Identification Using Deep Learning and Audio Fingerprinting
Application of AI Technology in Noise and Vibration
Human Factors and Ergonomics
Supervisor projects
- Enhanced Squeak and Rattle Detection in Automotive Engineering: A Novel Algorithmic Approach to Improve Automotive Safety and Quality
- 8 Aug 2024
- Control Seat Structural Vibrations to Improve Dynamic Comfort
- 24 May 2024
- Development of A System to Control Vehicle Driver/Occupant Emotion
- 29 Feb 2024
- Development of a Machine Learning Based Algorithm for Characterising the Vehicle Interior Noise
- 29 Feb 2024
- Development of a Machine Learning Based Algorithm for Characterising the Vehicle Interior Noise
- 24 Mar 2023
- Development of Audio Sensing for Autonomous Cars
- 8 Jun 2022
- Characterisation And Prevention Of Vibration-Induced Drowsiness In Drivers (ARC DP210101249)
- 22 Jun 2021
- Safety Barrier for Formula One Racing: Design and Optimization
- 19 Mar 2021
- Crashworthiness Analysis for Electric Vertical Take-Off and Landing Vehicles
- 15 Sep 2020
- Preparing Next-Gen Drivers: The Roles of Standardised Terminology, Regular Training and Large Language Models in Driver Education for Autonomous Vehicles
- 15 Jul 2020
- Prediction of Random Incidence Sound Absorption Coefficients of Sound-absorbing Materials
- 12 Dec 2019
- Acoustic Signal Based Fault Diagnosis Using Machine Learning
- 17 Oct 2019
- Development of a Method to Restore Driver Alertness
- 13 Feb 2018
- Application of CAE Modeling to Establish the Interior Seating Dynamics of Autonomous Driving Passenger Vehicles
- 19 Jun 2017
- The Effect of Vehicle Seat Vibration and its Control
- 1 Mar 2017
- Identification of Vehicle Seat Occupant Vibration Discomfort
- 1 Mar 2017
- Characterisation of the Driver Drowsiness Induced by Vibration
- 18 Jul 2016
- Development of an Algorithm for Squeak and Rattle Identification
- 4 Aug 2015
- Development of a Human Body Finite Element Model for Occupied Seat Vibration and Comfort
- 21 Jul 2014
- Acoustical prediction of the effect of porous materials on the noise level inside a coupled structural and acoustic system
- 3 Mar 2014
Teaching interests
Human Body Response to Vibration, Effects of Vibration on Discomfort and Fatigue, Vehicle Body CAE Concept Modelling, Vehicle NVH
Teaching responsibilities
With nearly six years of international working experience with Nissan (Japan) and ten years at RMIT University, Professor Fard has the experience and skills to design and instruct lectures directly connected to industry and real-world applications. He has developed a project-based approach for teaching two major Mechanical and Automotive engineering subjects – Advanced CAE. This project includes novel methods using the latest tools in 3D modelling and CAE technology for teaching a subject, which allows the students to receive hands-on practice in a computer laboratory without any need to attend workshops. It can be impractical for large class sizes. In this course delivery, each student learns the course practically by developing a CAE model of his/her selected car.
Automotive Advanced CAE (AUTO1026)
Advanced CAE for Mechanical Engineering (MIET2491)
Vehicle Noise, Vibration, and Harshness (MIET1192)
Automotive Research Project (AUTO1035, AUTO1027)
Motor Vehicles, Society, and Sustainability (AUTO1012)
Teaching responsibilities
With nearly six years of international working experience with Nissan (Japan) and ten years at RMIT University, Professor Fard has the experience and skills to design and instruct lectures directly connected to industry and real-world applications. He has developed a project-based approach for teaching two major Mechanical and Automotive engineering subjects – Advanced CAE. This project includes novel methods using the latest tools in 3D modelling and CAE technology for teaching a subject, which allows the students to receive hands-on practice in a computer laboratory without any need to attend workshops. It can be impractical for large class sizes. In this course delivery, each student learns the course practically by developing a CAE model of his/her selected car.
Automotive Advanced CAE (AUTO1026)
Advanced CAE for Mechanical Engineering (MIET2491)
Vehicle Noise, Vibration, and Harshness (MIET1192)
Automotive Research Project (AUTO1035, AUTO1027)
Motor Vehicles, Society, and Sustainability (AUTO1012)
Research interests
Mechanical Engineering, Automotive Engineering, Classical Physics, Architecture, Aerospace Engineering, Engineering Design
