Suhail Najeeb

Suhail Najeeb

Graduate Researcher

The University of Melbourne


I am Suhail Najeeb, a Graduate Researcher at the Department of Electrical and Electronic Engineering at The University of Melbourne. Before starting my Ph.D., I worked as a lecturer at the Department of ECE, East West University in Dhaka, Bangladesh. I hold a Master of Science from Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, where I also completed my undergraduate studies in Electrical and Electronic Engineering. As an undergraduate student, I became interested in Computer Vision and Deep Learning through my participation in the IEEE Video & Image Processing Cup 2017 & 2018. Since then, I have focused my studies and research on these areas, including the development of novel techniques for volumetric segmentation of lung tumors from CT scans as part of my Master’s thesis. My current research involves Computer Vision applications involving Detection.

Download my resumé .

  • Computer Vision
  • Deep Learning
  • Machine Learning
  • Ph.D. (Ongoing), Engineering & IT

    The University of Melbourne

  • M.Sc. in Electrical and Electronic Engineering, 2022

    Bangladesh University of Engineering and Technology

  • B.Sc. in Electrical and Electronic Engineering, 2018

    Bangladesh University of Engineering and Technology


Computer Vision
Deep Learning
Machine Learning


Graduate Researcher
Aug 2022 – Present Melbourne, Australia
Carrying out research for computer vision applications involving detection.
Jan 2019 – Sep 2021 Dhaka, Bangladesh

Theory & Lab courses Instructed:

  • ETE 105: Computer Fundamentals & Programming
  • ICE 107: Object Oriented Programming
  • ETE 302: Computer Communication & Networking
  • ETE/ICE 470: Applied Numerical Methods
  • ETE/ICE 472: Speech & Image Processing
  • ETE/ICE 401: VLSI Circuit Design
Nov 2017 – May 2018 Dhaka, Bangladesh
Instructed the ‘Course on Python & Data Science’


Champions, IEEE VIP Cup 2018
Lung Cancer Radiomics - Tumor Region Segmentation
2nd Runner up, IEEE VIP Cup 2017
Traffic Sign Recognition under Challenging Conditions



Recent Publications

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(2022). Spatial feature fusion in 3D convolutional autoencoders for lung tumor segmentation from 3D CT images. Biomedical Signal Processing and Control, 78 (2022).

PDF Slides DOI Read Online

(2019). A Pipeline for Lung Tumor Detection and Segmentation from CT Scans Using Dilated Convolutional Neural Networks. In ICASSP 2019.

PDF Cite Code Dataset Project Poster DOI

(2018). Classification of Retinal Diseases from OCT scans using Convolutional Neural Networks. In ICECE 2018.

PDF Cite Code Project