Khondaker Tasrif Noor

Khondaker Tasrif Noor

Khondaker Tasrif Noor is a researcher at Deakin University with a focus on Deep Learning, Computer Vision, and Machine Learning. He is a recipient of the prestigious Deakin University Postgraduate Research Scholarship (DUPR). He has published numerous papers in top-tier journals and conferences. He is also a member of the Australian Pattern Recognition Society (APRS). He is a reviewer of several top-tier journals and conferences.

Experience

Casual Academic Staff

Published:

I worked as a sessional academic staff member at Deakin University, contributing to the Deep Learning (SIT319, SIT744) and Artificial and Computational Intelligence (SIT215) units. My responsibilities included conducting tutorials and workshops, as well as marking assignments. During the workshops, I:

  • Designed, demonstrated, and explained deep learning models in Keras and TensorFlow as part of the workshop.
  • Addressed student queries to enhance understanding and engagement.
  • Provided academic consultation and contributed to the development of course materials.

Firmware Engineer

Published:

EMVision is an innovative medical device company developing portable electromagnetic microwave imaging solutions. My responsibilities included:

  • Inspecting, developing, and validating device testing plans.
  • Designing a GUI for device testing and automating the test bench analysis process.
  • Documenting product specifications, installation procedures, and testing protocols.
  • Researching emerging technologies and optimising processes to improve testing workflows and foster innovation.

Testing Engineer

Published:

RF Technology is a leading Australian manufacturer of wireless communication products. My responsibilities included:

  • Programming, testing, and ensuring the quality of digital radios, power amplifiers, and power supplies.
  • Documenting, implementing, and verifying testing processes for all products.
  • Enhancing product quality by refining hardware designs and advancing RF module expertise.
  • Guiding the production team and ensuring timely product status updates.