About

I am a Professor of Data Science at the University of Derby, School of Computing and Engineering, College of Science and Engineering and Head of the Data Science Research Centre. As such, my role is mainly on leading and developing research and innovation in the areas of Data Science and Artificial Intelligence. As the chair of the college research committee (CRC), I am overseeing the implementation of the university’s research strategy within the college and issues regarding Postgraduate Research students' progress.

I am working with colleagues in the DSRC to provide innovative solutions to local and national industries in the areas of data science and artificial intelligence.

Teaching responsibilities

I am currently teaching the Natural Language Processing module offered as part of the MSc in Big Data Analytics. I am also supervising final year projects at bachelor’s level and MSc dissertations.

Professional interests

My interests are in developing impactful research to solve real-life problems using data science and AI techniques. Domains of interest include e-commerce and targeted marketing, health informatics with special emphasis on the classification of medical imaging and Natural language processing.

Research interests

My research interests are mainly in the fields of data science applications and Natural Language Processing. Specifically, over the last few years I have developed research in:

• Medical Image classification using machine learning
• Standardisation of radiology reports using natural language techniques
• Sentiment analysis
• Natural language processing

Membership of professional bodies

• Follow of the British Computer Society
• BCS Chartered Information Technology Professional (CITP)
• Member of the ACM

Qualifications

• PhD, University of Salford, UK.

Recent conferences

I am the co-chair of the international conference on the application of Natural Language to Information Systems (NLDB) that I have organised a few times in the past and which will be hosted by the University of Derby in June 2023. I am regularly invited as a guest speaker at international conferences.

As a guest speaker at the Fifth International Conference on Advanced Intelligent Systems and Informatics (AISI’19) organised in Cairo, Egypt from October 26-28, 2019, I spoke about the research developed on the standardisation of radiology reports using rhetorical structure theory.

At the International Conference on Information and Education Innovations (ICIEI 2018) organised in London in June 2018, I was invited to give a talk as a guest speaker on the work on developing an adaptable and personalised E-learning system using freely available resources on the Web with a special application to computer science programmes design.

I am on the programme committee and am a regular reviewer of over ten international conferences.

International experience

At the University of Salford, I was the associate dean for international development from 2011 to 2019. In this position, I gained a lot of experience in developing international collaborations with HEI in the Middle East, Malaysia, France and India. I have represented the university in many international events including India, China, France and the Middle East.

I am a regular reviewer for the French Research Agency (ANR) in their research activities. In 2020, I was appointed as the vice president of the Computer science and Maths international jury for the evaluation for their EQUIPEX programme.

I am regularly review programmes and promotion applications for overseas universities mainly in the Middle East.

In the media

• Taking AI to the battlefront (blog post)

Recent publications

• Mohamed Seghir Hadj Ameur, Farid Meziane and Ahmed Guessoum (2020), Arabic Machine Translation: A survey of the latest trends and challenges, Computer Science Review, Volume 38, November 2020, 100305.
• Ali M. Hasan, Hamid A. Jalab, Rabha W. Ibrahim, Farid Meziane, Ala’a R. AL-Shamasneh and Suzan J. Obaiys (2020), MRI Brain Classification Using the Quantum Entropy LBP and Deep-Learning-Based Features, Entropy 22(9), 1033.
• Jinghui Peng, YiJing Jiang, Shanyu Tang and Farid Meziane (2019), Security of Streaming Media Communications with Logistic Map and Self-Adaptive Detection-Based Steganography, IEEE Transactions on Dependable and Secure Computing.
• Mohamed Seghir Hadj Ameur, Ahmed Guessoum and Farid Meziane (2019), Improving English-to-Arabic Neural Machine Translation via n-best list Re-ranking, Machine Translation, 33(4):279–314, December 2019, Springer.
• Nur Zareen Zulkarnain and Farid Meziane (2019), A Methodology for Ontology Reuse: The Case of the Abdominal Ultrasound Ontology, International Journal of Intelligent Information Technology, Volume 15 • Issue 4 • October-December 2019.
• Ali M. Hasan, Hamid A. Jalab, Farid Meziane, Hasan Kahtan and Ahmad Salah Al-Ahmad (2019). Combining Deep and Handcrafted Image Features for MRI Brain Scan Classification. IEEE Access, 7(1): 79959-79967. DOI: 10.1109/ACCESS.2019.2922691.
• Sinan S. AlSheikh, Khaled Shaalan and Farid Meziane (2019). Exploring the Effects of Consumers’ Trust: A Predictive Model for Satisfying Buyers’ Expectations Based on Sellers’ Behaviour in the Marketplace. IEEE Access, 7(1):73357-73372. DOI: 10.1109/ACCESS.2019.2917999.
• Nur Zareen Zulkarnain and Farid Meziane (2019), Ultrasound Reports Standardisation Using Rhetorical Structure Theory and Domain Ontology, Journal of Biomedical Informatics-X, Elsevier, Volume 1, March 2019, 100003
• Asaad F. Qasim, Rob Aspin, Farid Meziane and Peter Hogg (2019), ROI-Based Reversible Watermarking Scheme for Ensuring the Integrity and Authenticity of DICOM MR Images, Multimedia Tools and Applications, Volume 78, Issue 12, pp 16433–16463, Springer, June 2019.
• Eiman Aeiad and Farid Meziane (2019), An Adaptable and Personalised E-Learning System Applied to Computer Science Programmes Design, Education and Information Technologies, Volume 24, Issue 2, pp 1485–1509 March 2019, Springer.
• Asaad F. Qasim, Rob Aspin, Farid Meziane and Peter Hogg (2019), Assessment of Perceptual Distortion Boundary Through Applying Reversible Watermarking to Brain MR Images, Signal Processing: Image Communication, 70 (2019) 246–258, Elsevier.
• Jawad Sadek and Farid Meziane (2018), Learning Causality for Arabic – Proclitics, Procedia Computer Science, Volume 142, pp. 141-149, Elsevier.
• Manuel Pozo, Raja Chiky, Farid Meziane and Elisabeth Metais (2018), Exploiting past users' interests and predictions in an active learning method for dealing with cold start in recommender systems, Informatics, Volume 5, Issue 3. DOI: 10.3390/informatics5030035.
• Asaad F. Qasim, Farid Meziane and Rob Aspin (2018). Digital Watermarking: Applicability for Developing Trust in Medical Imaging Workflows State of the Art Review, Computer Science Review, Volume 27, pp. 45-60, February 2018, Elsevier.
• Abdelhafid Boussouar, Farid Meziane and Gillian Crofts (2017), Plantar Fascia Segmentation and Thickness Estimation in Ultrasound Images, Computerized Medical Imaging and Graphics 56(2017) pp.60–73, Elsevier.
• Jawad Sadek and Farid Meziane (2016), A Discourse-Based Approach for Arabic Question Answering, ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 16 Issue 2, December 2016, Article No. 11
• Ali Hasan and Farid Meziane (2016), Automated screening of MRI brain scanning using grey level statistics. Computers & Electrical Engineering, Volume 53, July 2016, Pages 276–291
• Ahmed Abbache, Farid Meziane, Ghalem Belalem and Fatma Zohra Belkredim (2016), Arabic Query Expansion Using WordNet and Association Rules, International Journal of Intelligent Information Technology, 12(3):52-64.
• Jawad Sadek and Farid Meziane (2016), Extracting Arabic causal relations using linguistic patterns, ACM Transactions on Asian and Low-Resource Language Information Processing. Vol 15 No 3, Article 14 (March 2016), pages 14-1 to 14-20.

For a full list of publications see:

• Google Scholar
• Research Gate