On The Right Track: PhD Proves New Methods For Railroad Safety
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ON THE RIGHT TRACK: PhD PROVES NEW METHODS FOR RAILROAD SAFETY
Railway engineering consultant, MRX Technologies (now Siemens Mobility), is just one industry leader leveraging AI to enhance business efficiency. When the team identified machine learning as a potential game-changer for railroad safety, they partnered with APR.Intern to access PhD-level expertise on the subject.
Looking to improve measurement accuracy and defect detection, machine learning also presented an opportunity for MRX to optimise software development time.
Through APR.Intern, MRX was matched with Lian Xu, an engineering PhD student from the University of Western Australia (UWA). With a background in computer science and a keen understanding of machine learning techniques, Lian was the perfect candidate to investigate the effectiveness on MRX’s automated visual inspection system.
Guided by her Academic Mentor, UWA’s Professor Mohammed Bennamoun, Lian’s research outlined the effectiveness of machine learning in detecting train features, providing accurate measurements and more.
“The project was incredibly successful in demonstrating the potential of machine learning techniques. Based on the findings, we will be moving forward with techniques demonstrated by Lian to optimise our system,”
Justin Niven, MRX Technologies Development Engineer and Lian’s Industry Supervisor
For Lian, the internship was an opportunity to broaden her fields of interest in the AI technique.
“My time at MRX inspired me to rethink previous research with a fresh perspective and apply this to future thinking. I also gained transferable skills such as communication and teamwork. Within the university, PhD students usually work independently, whereas this industry internship allowed me to experience cooperative research in a more dynamic environment,”
Lian Xu, PhD Intern at MRX Technologies
“The research project was a success and found machine learning can be a strong tool for railroad safety. I’m grateful for this opportunity and would like to thank the team for a great experience,” Lian added.
This internship was supported by the Australian Government Department of Education, through the ‘Supporting more women in STEM careers: Australian Mathematical Sciences Institute (AMSI) – National Research Internship Program’.
