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.
- 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
- 2019 – onward: Professor, RMIT University.
- 2015 – 2018: Associate Professor, RMIT University.
- 2009 – 2014: Senior Lecturer, RMIT University.
- 2003 – 2009: Nissan (Japan), Vehicle Body Design Lead Engineer.
- 2000 – 2003: Teaching Assistant, Tohoku University, Japan.
- 2013 to 2017: NHK Spring (Japan) and CRC (Australian National Organization).
Title: Development of New Method to Predict Occupied Seat Vibration and Comfort.
- 2013 to 2016: General Motors (Australia):
Title: Development of a Smartphone Application for Diagnosing Vehicle Interior Noise.
- 2014 to 2016: Futuris Automotive Interiors (Australia):
Title: Development of a Method to Predict Acoustic Properties of Vehicle Cabin.
- 2015 to 2018: Ford Motor Company (Australia):
Title: Development of CAE Concept Modelling Method for Vehicle Body-In-White.
- 2016 to 2019: NHK Spring and CRC (Australian National Organization).
Title: Development of a Method to Control the High Frequency Vehicle Seat Structural Vibration Using Piezo-Actuators.
- 2018 (six months): AMSI Intern Program Aurecon Group.
Data Analytics and Machine Learning for system diagnostics, condition and assessment and operation modelling.
- 2018 to 2019: iMOVE Research Project Agreement.=
Title: Algorithm Development for “Squeaks and Rattles” Identification Using Sound Pattern Recognition.
- 2018 to 2022: USG Boral Company (A new contract).
Title: The Impact Sound Signature of Lightweight Construction.
- 2021 to 2024: ARC Discovery Project (DP210101249).
- 2021 to 2024: Optimization of Racing Track Crash Safety, Fédération Internationale de l'Automobile (FIA)
- Professor Fard's publications can be viewed on Google Scholar.
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)
Professor Fard's cross-disciplinary research team from the schools of Engineering, Health and Biomedical Sciences, Science, and Media and Communication achieved significant international media (TV, Radio, and Newspapers) coverage in Australia, Europe, Canada, Japan, and USA about their research on the effects of road vibration on driver drowsiness and road safety (July 2018).
- The Age – Bad vibrations: how our cars could be lulling us to deadly sleep
- The Age video - How your car’s vibration can make you sleepy
- ‘Bad vibrations’ in cars found to have dangerous, soporific effect on drivers
- New study: car vibrations make drivers sleepy
- Canadian Broadcasting Commission - Your car might be trying to kill you by lulling you with sleep-inducing vibrations
- Not-So-Good Vibrations? How Your Car Could Be Making You Sleepy
- Car Vibrations Could Cause Drivers to Feel Sleepy at The Wheel
- Researchers find natural vibrations of cars make drivers sleepy
- Can a car lull you to sleep behind the wheel?
- Vehicle vibrations may make drivers drowsy: study
Our paper, “The Effects of Physical Vibration on Heart Rate Variability as a Measure of Drowsiness” (DOI 10.1080/00140139.2018.1482373) was published in the Ergonomics journal and it was chosen as “article of the month” in July 2018. This paper has received a very high Altmetric Attention Score. It is the top paper in the Ergonomics journal and is ranked in the top 0.2% of all research outputs ever tracked by Altmetric in all disciplines.
- PhD, Mechanical Engineering, Graduate School of Information Sciences, Tohoku University, Japan, 2003.
Professor Fard worked at Nissan Motor Company (JAPAN) on Vehicle Body Design [CAE and NVH] as a lead engineer prior to joining RMIT University. His experience at Nissan, as a member of a highly competitive and constantly innovative team of engineers that focused on real-world applications of research was inspiring. His significant achievements at Nissan focused mostly on reducing the vehicle body structural noise and vibration using CAE (FEM) and NVH techniques. These contributions resulted in multiple discoveries for Nissan and translated into innovations in vehicle body design.
- Technical Chair for Autonomous Vehicle Technology Conference (autonomous2022.com)
- Faculty Advisor for RMIT FSAE Racing Team.
- Program Manager for Bachelor of Automotive Engineering.
- RMIT University Representative and Coordinator for iMOVE UG Projects.
- Discipline Leader for Automotive Engineering.
- Zhao, Y.,Xu, J.,Davy, J.,Liu, Z.,FARD, M. (2022). Prediction of random incidence sound absorption coefficients of porous materials In: Applied acoustics, 189, 1 - 14
- FARD, M.,Yao, J.,Kato, K.,Davy, J. (2021). The geometric mean is a superior frequency response averaging method for human body vibration In: Ergonomics, 64, 273 - 283
- Yao, J.,FARD, M.,Davy, J.,Kato, K. (2021). The prediction of vehicle vibration transmitted to the occupant using a modular transfer matrix In: JVC/Journal of Vibration and Control, , 1 - 14
- Zou, K.,FARD, M.,Davy, J.,Robinson, S. (2021). Effects of Vibration on Seated Human Drowsiness/Alertness In: Vibration Engineering for a Sustainable Future, Sydney, Australia, 18-20 November 2019
- Abeysinghe, A.,FARD, M.,Nakhaie Jazar, R.,Zambetta, F.,Davy, J. (2021). Mel frequency cepstral coefficient temporal feature integration for classifying squeak and rattle noise In: The Journal of the Acoustical Society of America, 150, 193 - 201
- Liu, Z.,FARD, M.,Davy, J. (2020). Prediction of the acoustic effect of an interior trim porous material inside a rigid-walled car air cavity model In: Applied Acoustics, 165, 1 - 10
- Pogorilyi, O.,FARD, M.,Taylor, D.,Davy, J. (2020). Landmark-based audio fingerprinting system applied to vehicle squeak and rattle noises In: Noise Control Engineering Journal, 68, 113 - 124
- FARD, M.,Yao, J.,Taube, R.,Davy, J. (2020). The Concept modeling method: An approach to optimize the structural dynamics of a vehicle body In: Institution of Mechanical Engineers. Proceedings. Part D: Journal of Automobile Engineering, 234, 2923 - 2932
- Pogorilyi, O.,FARD, M.,Davy, J. (2020). Squeak and rattle noise classification using radial basis function neural networks In: Noise Control Engineering Journal, 68, 283 - 293
- Pang, T.,FARD, M. (2020). Reverse engineering and topology optimization for weight-reduction of a bell-crank In: Applied Sciences, 10, 1 - 16
10 PhD Current Supervisions12 PhD Completions and 3 Masters by Research Completions
- Excellerate Australia Industry Placement Scholarship: Algorithm Development for “Squeaks and Rattles” Identification. Funded by: Excellerate Australia Industry Placement Scholarship for PhD Students from (2019 to 2020)
- Diagonal Distortion of Liftgate Openings - Bodies. Funded by: Ford Motor Company Grant 2015 from (2015 to 2018)