Dr Tariq Rahim

About

I am an Early Career Researcher and  Lecturer in Computer Science (UX) at the Department of Computer Science. As a module leader, I am teaching a Requirements Analysis and Design course. My global academic and research journey spans nine years of working with universities and industrial-academic corporations such as the Research Institute of Communication Technology at Beijing Institute of Technology, China, Wireless and Emerging Network Systems (WENS) Lab-South Korea, and NIHR-funded project at Cardiff Metropolitan Univesity, UK. I worked as a Postdoctoral Fellow and a Researcher at ICT-CRC, KIT, South Korea for industrial academic cooperation. From May 2022 till May 2023, I worked as a senior Postdoctoral Research Fellow at Cardiff Metropolitan University, UK for a NIHR-funded project to automatically classify middle ear diseases. 

My research includes Image (natural & medical) Processing, Machine Learning (ML), Deep Learning (DL), and Video Processing. I have been working on various problems related to classification, detection, and segmentation in medical imaging. Furthermore, I have been working on the impact of high frame rates and video encodings on the perceived quality of end users.  I am a reviewer for several prestigious journals and conferences including IEEE Transactions on Circuits and Systems, Computerized Medical Imaging and Graphics, Computers in Biology and Medicine, IEEE Access, and IEEE TSP. 

I am open to supervising highly motivated self-funded Ph.D. students having interests in the areas of ML, DL, image processing, and video processing. 

Academic responsibilities

Lecturer in Computer Science (UX)

Qualifications

  • PhD in IT Convergence Engineering (Graduated in 2021 with Distinction)
  • MS in Information and Communication Engineering (Graduated in 2017 Distinction)
  • Bachelors in Electronics Engineering (Graduated in 2012)

Teaching and learning

Module Leader: CI4305 Requirements Analysis and Design

Teacher:  C14316 Requirements Analysis and Design for Game Programming

Undergraduate courses taught

Research

Areas of specialism

Machine Learning

Deep Learning

Image Processing focuses on both natural and medical imaging. 

Image Reconstruction

Video Quality Assessment

Areas of specialism

  • Machine Learning
  • Deep Learning
  • Image Processing
  • Video Processing

Scholarly affiliations

  • IEEE Member
  • Member of IEEE Communications Society (ComSoc)

Research student supervision

Publications

Number of items: 7.

Article

Hassan, Syed Ali, Rahim, Tariq and Shin, Soo Young (2022) ChildAR : an augmented reality-based interactive game for assisting children in their education. Universal Access in the Information Society, 21(2), pp. 545-556. ISSN (print) 1615-5289

Novamizanti, Ledya, Ramatryana, I Nyoman Apraz, Magdalena, Rita, Pratama, I Putu Agus Eka, Rahim, Tariq and Shin, Soo Young (2022) Compressive sampling of color retinal image using spread spectrum Fourier sampling and total variant. IEEE Access, 10, pp. 42198-42207. ISSN (online) 2169-3536

Islam, Anik, Rahim, Tariq, Masuduzzaman, MD and Shin, Soo Young (2021) A blockchain-based artificial intelligence-empowered contagious pandemic situation supervision scheme using internet of drone things. IEEE Wireless Communications, 28(4), pp. 166-173. ISSN (print) 1536-1284

Han, Seung Heon, Chae, Seog, Park, Jae Han, Hassan, Syed Ali, Rahim, Tariq and Shin, Soo Young (2020) Video-based traffic accident prevention safety system using deep learning. The Journal of Korean Institute of Communications and Information Sciences, 45(8), pp. 1399-1406. ISSN (print) 1226-4717

Conference or Workshop Item

Choi, Yeon Ji, Rahim, Tariq, Ramatryana, Nyoman Apraz and Shin, Soo Young (2021) Improved CNN-based path planning for stairs climbing in autonomous UAV with LiDAR sensor. In: International Conference on Electronics, Information, and Communication (ICEIC) 2024; 31 Jan - 3 Feb 2021, Taipei, Taiwan.

Yang, Shu, Zhao, Junzhe, Jiang, Tingting, Wang, Jing, Rahim, Tariq, Zhang, Bo, Xu, Zhaoji and Fe, Zesong (2017) An objective assessment method based on multi-level factors for panoramic videos. In: 2017 IEEE Visual Communications and Image Processing (VCIP); 10-13 Dec 2017, St. Petersburg, U.S..

Jing, Wang, Zedong, Wang, Fei, Wang, Rahim, Tariq and Zesong, Fei (2016) A no-reference video quality assessment method for VoIP applications. In: 2016 IEEE 13th International Conference on Signal Processing (ICSP); 06-10 Nov 2016, Chengdu, China.

This list was generated on Tue Apr 30 06:48:24 2024 BST.