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Anwar Shah

Anwar Shah

Assistant Professor
  • Department of Computer Science
  • Anwar.Shah@nu.edu.pk
  • (041) 111-128-128
  • Ext: 131

Introduction

Dr. Anwar Shah is an Assistant Professor in Computer Science at the National University of Computer and Emerging Sciences. He holds a PhD in Computer Science, specializing in Three-way Clustering (Machine Learning) from FAST – National University of Computer and Emerging Science, Pakistan. Adding to his accolades, he holds an MS in Computer Science with distinction, focusing on image processing, from Abasyn University Peshawar and an MSc in computer science from the University of Peshawar. Furthermore, his diverse educational journey extends to an MBA in Human Resource Management from the Institute of Management Studies, University of Peshawar.
Dr. Shah’s professional journey commenced as an Instructor cum Team leader (Developer & Trainer) at e Soft Technologies in Dubai, the United Arab Emirates, where he demonstrated exceptional skills from 2008 to 2015. In May 2021, he joined the esteemed FAST – National University of Computer and Emerging Science, Peshawar Campus, as a Research Assistant. During his tenure, he diligently contributed to the research project titled “Three-way Clustering Approaches for Open World Classification” from May 2021 to April 2022. His noteworthy work has been recognized and published in renowned journals such as Information Sciences, Journal of Applied Intelligence, Journal of Approximate Reasoning, and Journal of King Saud University – Computer and Information Sciences.
Dr. Shah’s research interests encompass a broad spectrum, including Three-way Decisions, Machine Learning, Information Security, Blockchain, Bioinformatics, and Image Processing. He aims to make significant contributions to these fields through his dedication and expertise.

Education

PhD Computer Sciences, FAST-NUCES, Peshawar

MS Computer Sciences (Distinction), Abasyn University, Peshawar, Peshawar

MBA Human Resource Management, University of Peshawar, Peshawar

MSc Computer Sciences University of Peshawar, Peshawar

Publications

  1. Anwar Shah, Bahar Ali, Fazal Wahab, Inam Ullah, Kassian T.T. Amesho, Muhammad Shafiq, “Entropy Based Grid Approach for Handling Outliers: A Case Study to Environmental Monitoring Data”, Environmental Science and Pollution Research, Springer,

https://doi.org/10.1007/s11356-023-26780-1, (IF=5.190), June 12, 2023, Springer.

  1. Anwar Shah, Bahar Ali, Masood Habib, Jaroslav Frnda, Inam Ullah, Muhammad Shahid Anwar; An Ensemble Face Recognition Mechanism based on Three-way Decisions, Journal of King Saud University – Computer and Information Sciences.

https://doi.org/10.1016/j.jksuci.2023.03.016, (IF=9.006), March 30, 2023, Elsevier.

  1. Fazal Wahab, Inam Ullah, Anwar Shah, Rehan Ali Khan, Ahyoung Choi, and Muhammad Shahid Anwar, “Design and implementation of real-time object detection system based on single-shoot detector and OpenCV”, Frontiers in Psychology, Frontiers.

https://doi.org/10.3389/fpsyg.2022.1039645, (IF. 4.232), Nov 02, 2022, Frontiers.

  1. Shah, N. Azam, E. Alanazi, J. T. Yao, Image blurring and sharpening inspired three-way clustering approach. Applied Intelligence, 2022, 1-25,

https://doi.org/10.1007/s10489-021-03072-0, (IF 5.019), April 09, 2022, Springer.

  1. Shah, J. I. Bangash, A. W. Khan, I. Ahmed, A. Khan, A. Khan, et al., “Comparative analysis of median filter and its variants for removal of impulse noise from gray scale images”, J. King Saud Univ.– Computer and Information Sciences, 34 (3), Pages 505-519,

https://doi.org/10.1016/j.jksuci.2020.03.007, (IF 9.006), March 2022, Elsevier.

  1. Shah, N. Azam, B. Ali, M. T. Khan. J. T. Yao, A three-way clustering approach for novelty detection. Information Sciences. 569, 2021, 650–668,

https://doi.org/10.1016/j.ins.2021.05.021, (IF 8.233), August 2021, Elsevier.

  1. Ali, N. Azam, A. Shah, J.T. Yao, A spatial filtering inspired three-way clustering approach with application to outlier detection, International Journal of Approximate Reasoning, 130, 2021, 1-21,

https://doi.org/10.1016/j.ijar.2020.12.003, (IF 4.452), March 2021, Elsevier.

Collaborations at National and International Level

Detail of Funded Projects