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Moslem Sadeghi Goughari

Postdoctoral fellow
Moslem Sadeghi Goughari
Location: Engineering 5 3020

Education

  • BSc, Mechanical Engineering, Shahid Bahonar University of Kerman, Iran (2012)
  • MSc, Mechanical Engineering, K. N. Toosi University of Technology, Iran (2015)
  • PhD, Mechanical and Mechatronics Engineering, University of Waterloo (2020)

Research interests

  • High intensity focused ultrasound

Moslem Sadeghi Goughari's Google Scholar

Yanjun Qian

Postdoctoral fellow
Yanjun

Education

  • BSc, Vehicle Engineering, (Automobile), Tongji University (2013)
  • PhD, Mechanical and Mechatronics Engineering, University of Waterloo (2020)

Research interests

  • Ultrasonic non-destructive testing (NDT)
  • Field-programmable gate array (FPGA)-SoC system development
  • Practical AI in manufacturing

More about Yanjun Qian

Yanjun received his PhD degree in Mechanical and Mechatronics Engineering at the University of Waterloo under the supervision of professor Hyock Ju Kwon. During his PhD studies, he developed two devices which were related to the non-destructive testing. The first one was a vibro-tactile sensor which can differentiate the stiffness of the soft material; and the second one was an ultrasonic non-destructive testing (NDT) device based on the FPGA-SoC platform. He worked closely with local industry during his study and accomplished several collaborative mechatronics-related projects, such as the development of a digital anglometer on the testing machine. Currently, he is working on practical AI solutions which can be applied to the production line.

Yanjun Qian's Google Scholar

Ali Rafiei

Postdoctoral fellow
Ali

Biography:

  • BSc - Shiraz Electrical Engineering, Communications, Shiraz University, Iran (2004)
  • MSc - Electrical Engineering, Communication Systems, Shiraz University, Iran (2007)
  • PhD -Engineering, Wireless Communications, University of Technology Sydney, Australia (2017)

Research Interest:

Artificial Intelligence and Machine Learning, Robotics and Mobile Robots, Practical AI in manufacturing, (smart) Sensors, Ultrasonic non-destructive testing (NDT), Embedded Systems, Edge Computing, High performance computing (HPC)

More About Ali Rafiei:

Ali Received his PhD degree in Engineering, in Communications Networks. He was working on recovery of wireless communications and emergent cooperation in wireless sensor networks under supervision of A/Prof. Mehran Abolhasan at University of technology Sydney, Australia.  

Currently he is working on (smart) Sensors and Practical AI in manufacturing, NDT. 

‪Ali Rafiei - ‪Google Scholar