Dr Zulfiqar Ali
-
Email
z.ali@essex.ac.uk -
Location
3A.529, Colchester Campus
-
Academic support hours
During Autumn Term my Academic Support Hours are 11:00 - 12:00 on Mondays and 14:00 - 15:00 on Fridays. I will be in my office, 2NW.4B.526. I can also meet on zoom by request at these times (I will check email during these support hours and respond with a link).
Profile
Biography
Dr. Zulfiqar Joined School of Computer science and Electronic Engineering at the University of Essex in 2020 as a Lecturer(R). He undertook his Ph.D. study to develop intelligent systems for screening of disorders at the Centre of Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Malaysia. His Ph.D.’s proposed work was approved for funding of 0.5 million US dollars after the external review of the American Association for the Advancement of Science (AAAS). Zulfiqar obtained a Master's degree in Computational Mathematics from the University of the Punjab and a Master's degree in System Engineering from the University of Engineering and Technology, Lahore. He served in the School of Computing at Ulster University from 2018 to 2020 as a Research Fellow in BTIIC (British Telecom Ireland Innovation Centre), where he worked on various funded projects including Smarter Customer Analytics, Intelligent Process Analytics, Adaptive and Autonomic Systems. He also served King Saud University, Riyadh from 2010 to 2018 as a Senior Researcher where he submitted and completed three funded projects, reviewed and approved by AAAS and King Abdulaziz City for Science and Technology. Continued with Ph.D. research interest, Zulfiqar has developed various intelligent systems using machine learning approaches for the screening of disorders. Secure transmission of medical data (speech/image) collected through the Internet of Things using encryption and zero-watermarking is also included in his area of expertise. Recently, a project " Cloud-Based Privacy Protected Computer-Aided Diagnosis System for Routine Breast Cancer Screening" has been accepted for funding. He has also provided consultancy in various funded projects. He has published extensively in the domain of speech/speaker recognition, biomedical engineering, security and privacy in healthcare applications, and multimedia forensics.
Qualifications
-
PhD Electrical and Electronic Engineering Universiti Teknologi Petronas,
-
Master System Engineering University of Engineering and Technology,
-
Master Computational Mathematics University of the Punjab,
Appointments
University of Essex
-
Lecturer (R), School of Computer Science and Electronic Engineering, University of Essex (31/3/2020 - present)
Other academic
-
Research Fellow, School of Computing, University of Ulster (17/7/2018 - 29/3/2020)
-
Senior Researcher/Assistant professor, Department of Computer Engineering, King Saud University (14/10/2010 - 19/7/2018)
Research and professional activities
Research interests
Adaptive and Autonomic Systems
Digital Speech Processing
Machine Learning Applied to Biomedical Signals
Privacy Protection
Real-time Predictive Analytics
Audio Forensics/Authentication
Data Analytics
Teaching and supervision
Current teaching responsibilities
-
Team Project Challenge (CE101)
-
Databases and Information Retrieval (CE205)
Publications
Journal articles (51)
Farhat, T., Akram, S., AlSagri, HS., Ali, Z., Ahmad, A. and Jaffar, A., (2024). Facial Image-Based Autism Detection: A Comparative Study of Deep Neural Network Classifiers. Computers, Materials & Continua. 78 (1), 105-126
Rahman, A., Wadud, MAH., Islam, MJ., Kundu, D., Bhuiyan, TMA-U-H., Muhammad, G. and Ali, Z., (2024). Internet of medical things and blockchain-enabled patient-centric agent through SDN for remote patient monitoring in 5G network. Scientific Reports. 14 (1), 5297-
Kundu, D., Rahman, MM., Rahman, A., Das, D., Siddiqi, UR., Alam, MGR., Dey, SK., Muhammad, G. and Ali, Z., (2024). Federated Deep Learning for Monkeypox Disease Detection on GAN-Augmented Dataset. IEEE Access. 12, 32819-32829
Muhammad, G., Sattar, F. and Ali, Z., (2024). Guest Editorial Insights of Machine Learning into Medical Decision Making Systems: From Research to Practice. IEEE Journal of Biomedical and Health Informatics. 28 (4), 1801-1802
Ahmad, J., Akram, S., Jaffar, A., Ali, Z., Bhatti, SM., Ahmad, A. and Rehman, SU., (2024). Deep learning empowered breast cancer diagnosis: Advancements in detection and classification. PLOS ONE. 19 (7), e0304757-e0304757
Singamaneni, KK., Muhammad, G. and Ali, Z., (2024). A novel quantum hash-based attribute-based encryption approach for secure data integrity and access control in mobile edge computing-enabled customer behavior analysis. IEEE Access. 12, 37378-37397
Naseer, I., Masood, T., Akram, S., Ali, Z., Ahmad, A., Rehman, SU. and Jaffar, A., (2024). Empowering Diagnosis: Cutting-Edge Segmentation and Classification in Lung Cancer Analysis. Computers, Materials and Continua. 79 (3), 4963-4977
Magsi, AH., Yovita, LV., Ghulam, A., Muhammad, G. and Ali, Z., (2023). A Content Poisoning Attack Detection and Prevention System in Vehicular Named Data Networking. Sustainability. 15 (14), 10931-10931
Butt, NA., Gull, H., Ali, Z., Muhammad, G. and AlQahtani, SA., (2023). A multi-prefecture study applying multivariate approaches for predicting and demystifying weather data variations affect COVID-19 spread. Information Systems and e-Business Management
Almogahed, A., Mahdin, H., Omar, M., Zakaria, NH., Muhammad, G. and Ali, Z., (2023). Optimized Refactoring Mechanisms to Improve Quality Characteristics in Object-Oriented Systems. IEEE Access. 11, 99143-99158
Hussain Magsi, A., Muhammad, G., Karim, S., Memon, S. and Ali, Z., (2023). Push-Based Content Dissemination and Machine Learning-Oriented Illusion Attack Detection in Vehicular Named Data Networking. Computers, Materials & Continua. 76 (3), 3131-3150
Udoy, AI., Rahaman, MA., Islam, MJ., Rahman, A., Ali, Z. and Muhammad, G., (2023). 4SQR-Code: A 4-state QR code generation model for increasing data storing capacity in the Digital Twin framework. Journal of Advanced Research, S2090-1232(23)00298-9-1232(23)00298
Ahmad, N., Muhammad, G., Yadav, KS., Laskar, RH., Hossain, A. and Ali, Z., (2023). A cascaded deep learning framework for iris centre localization in facial image. Expert Systems. 41 (2)
Singamaneni, KK., Muhammad, G. and Ali, Z., (2023). A Novel Multi-Qubit Quantum Key Distribution Ciphertext-Policy Attribute-Based Encryption Model to Improve Cloud Security for Consumers. IEEE Transactions on Consumer Electronics. 70 (1), 1092-1101
Ali, Z., Imran, M. and Shoaib, M., (2022). An IoT-based smart healthcare system to detect dysphonia. Neural Computing and Applications. 34 (14), 11255-11265
Ali, Z., Amin, F-E. and Hussain, M., (2022). A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images. Electronics. 11 (5), 710-710
Hussain, I., Ullah, I., Ali, W., Muhammad, G. and Ali, Z., (2022). Exploiting lion optimization algorithm for sustainable energy management system in industrial applications. Sustainable Energy Technologies and Assessments. 52C, 102237-102237
Benarous, L., Benarous, K., Muhammad, G. and Ali, Z., (2022). Deep learning application detecting SARS-CoV-2 key enzymes inhibitors.. Cluster Computing. 26 (2), 1169-1180
Andreu-Perez, J., Perez-Espinosa, H., Timonet, E., Kiani, M., Giron-Perez, MI., Benitez-Trinidad, AB., Jarchi, D., Rosales, A., Gkatzoulis, N., Reyes-Galaviz, OF., Torres, A., Alberto Reyes-Garcia, C., Ali, Z. and Rivas, F., (2022). A Generic Deep Learning Based Cough Analysis System from Clinically Validated Samples for Point-of-Need Covid-19 Test and Severity Levels. IEEE Transactions on Services Computing. 15 (3), 1220-1232
Mubeen, Z., Afzal, M., Ali, Z., Khan, S. and Imran, M., (2021). Detection of impostor and tampered segments in audio by using an intelligent system. Computers and Electrical Engineering. 91, 107122-107122
Awais, M., Raza, M., Ali, K., Ali, Z., Irfan, M., Chughtai, O., Khan, I., Kim, S. and Ur Rehman, M., (2019). An Internet of Things Based Bed-Egress Alerting Paradigm Using Wearable Sensors in Elderly Care Environment. Sensors. 19 (11), 2498-2498
Ali, Z., Imran, M., McClean, S., Khan, N. and Shoaib, M., (2019). Protection of records and data authentication based on secret shares and watermarking. Future Generation Computer Systems. 98, 331-341
Ali, A., Yaqoob, I., Ahmed, E., Imran, M., Kwak, KS., Ahmad, A., Hussain, SA. and Ali, Z., (2018). Channel Clustering and QoS Level Identification Scheme for Multi-Channel Cognitive Radio Networks. IEEE Communications Magazine. 56 (4), 164-171
Ali, Z. and Talha, M., (2018). Innovative Method for Unsupervised Voice Activity Detection and Classification of Audio Segments. IEEE Access. 6, 15494-15504
Ali, Z., Imran, M., Alsulaiman, M., Shoaib, M. and Ullah, S., (2018). Chaos-based robust method of zero-watermarking for medical signals. Future Generation Computer Systems. 88, 400-412
Ali, Z., Hossain, MS., Muhammad, G. and Sangaiah, AK., (2018). An intelligent healthcare system for detection and classification to discriminate vocal fold disorders. Future Generation Computer Systems. 85, 19-28
Ali, Z., Hossain, MS., Muhammad, G., Ullah, I., Abachi, H. and Alamri, A., (2018). Edge-centric multimodal authentication system using encrypted biometric templates. Future Generation Computer Systems. 85, 76-87
Ali, Z., Imran, M., Alsulaiman, M., Zia, T. and Shoaib, M., (2018). A zero-watermarking algorithm for privacy protection in biomedical signals. Future Generation Computer Systems. 82, 290-303
Ali, Z., Hossain, MS., Muhammad, G. and Aslam, M., (2018). New Zero-Watermarking Algorithm Using Hurst Exponent for Protection of Privacy in Telemedicine. IEEE Access. 6, 7930-7940
Al-Nasheri, A., Muhammad, G., Alsulaiman, M., Ali, Z., Malki, KH., Mesallam, TA. and Farahat Ibrahim, M., (2018). Voice Pathology Detection and Classification Using Auto-Correlation and Entropy Features in Different Frequency Regions. IEEE Access. 6, 6961-6974
Mesallam, TA., Farahat, M., Malki, KH., Alsulaiman, M., Ali, Z., Al-nasheri, A. and Muhammad, G., (2017). Development of the Arabic Voice Pathology Database and Its Evaluation by Using Speech Features and Machine Learning Algorithms. Journal of Healthcare Engineering. 2017, 1-13
Abdul, W., Ali, Z., Ghouzali, S. and Alsulaiman, M., (2017). Security and Privacy for Medical Images Using Chaotic Visual Cryptography. Journal of Medical Imaging and Health Informatics. 7 (6), 1296-1301
Ali, Z., Alsulaiman, M., Muhammad, G., Elamvazuthi, I., Al-Nasheri, A., Mesallam, TA., Farahat, M. and Malki, KH., (2017). Intra- and Inter-database Study for Arabic, English, and German Databases: Do Conventional Speech Features Detect Voice Pathology?. Journal of Voice. 31 (3), 386.e1-386.e8
Ali, Z., Imran, M. and Alsulaiman, M., (2017). An Automatic Digital Audio Authentication/Forensics System. IEEE Access. 5, 2994-3007
Al-nasheri, A., Muhammad, G., Alsulaiman, M., Ali, Z., Mesallam, TA., Farahat, M., Malki, KH. and Bencherif, MA., (2017). An Investigation of Multidimensional Voice Program Parameters in Three Different Databases for Voice Pathology Detection and Classification. Journal of Voice. 31 (1), 113.e9-113.e18
Al-Nasheri, A., Muhammad, G., Alsulaiman, M. and Ali, Z., (2017). Investigation of Voice Pathology Detection and Classification on Different Frequency Regions Using Correlation Functions.. Journal of Voice. 31 (1), 3-15
Muhammad, G., Alsulaiman, M., Ali, Z., Mesallam, TA., Farahat, M., Malki, KH., Al-nasheri, A. and Bencherif, MA., (2017). Voice pathology detection using interlaced derivative pattern on glottal source excitation. Biomedical Signal Processing and Control. 31, 156-164
Imran, M., Ali, Z., Bakhsh, ST. and Akram, S., (2017). Blind Detection of Copy-Move Forgery in Digital Audio Forensics. IEEE Access. 5, 12843-12855
Abdul, W., Ali, Z., Ghouzali, S., Alfawaz, B., Muhammad, G. and Hossain, MS., (2017). Biometric Security Through Visual Encryption for Fog Edge Computing. IEEE Access. 5, 5531-5538
Ali, Z., Muhammad, G. and Alhamid, MF., (2017). An Automatic Health Monitoring System for Patients Suffering From Voice Complications in Smart Cities. IEEE Access. 5, 3900-3908
Ali, Z., Talha, M. and Alsulaiman, M., (2017). A Practical Approach: Design and Implementation of a Healthcare Software for Screening of Dysphonic Patients. IEEE Access. 5, 5844-5857
Ali, Z., Elamvazuthi, I., Alsulaiman, M. and Muhammad, G., (2016). Detection of Voice Pathology using Fractal Dimension in a Multiresolution Analysis of Normal and Disordered Speech Signals. Journal of Medical Systems. 40 (1), 1-10
Ali, Z., Elamvazuthi, I., Alsulaiman, M. and Muhammad, G., (2016). Automatic Voice Pathology Detection With Running Speech by Using Estimation of Auditory Spectrum and Cepstral Coefficients Based on the All-Pole Model.. Journal of Voice. 30 (6), 757.e7-757.e19
Muhammad, G., Altuwaijri, G., Alsulaiman, M., Ali, Z., Mesallam, TA., Farahat, M., Malki, KH. and Al-nasheri, A., (2016). Automatic voice pathology detection and classification using vocal tract area irregularity. Biocybernetics and Biomedical Engineering. 36 (2), 309-317
Alhussein, M., Ali, Z., Imran, M. and Abdul, W., (2016). Automatic Gender Detection Based on Characteristics of Vocal Folds for Mobile Healthcare System. Mobile Information Systems. 2016, 1-12
Ali, Z., Alsulaiman, M., Elamvazuthi, I., Muhammad, G., Mesallam, TA., Farahat, M. and Malki, KH., (2016). Voice pathology detection based on the modified voice contour and SVM. Biologically Inspired Cognitive Architectures. 15, 10-18
Elamvazuthi, I., Zulkifli, Z., Ali, Z., Khan, MKAA., Parasuraman, S., Balaji, M. and Chandrasekaran, M., (2015). Development of Electromyography Signal Signature for Forearm Muscle. Procedia Computer Science. 76, 229-234
Elamvazuthi, I., Duy, NHX., Ali, Z., Su, SW., Khan, MKAA. and Parasuraman, S., (2015). Electromyography (EMG) based Classification of Neuromuscular Disorders using Multi-Layer Perceptron. Procedia Computer Science. 76, 223-228
Ali, Z., Muhammad, G., Alsulaiman, M., Elamvazuthi, I. and Al-Mutib, K., (2015). Oriented and Interpolated Local Features for Speech Recognition of Vocal Fold Disordered Patients. International Journal for Computers and Their Applications. 22 (1), 1-11
Ali, Z., Muhammad, G., Alsulaiman, M., Elamvazuthi, I. and Al-Mutib, K., (2015). Oriented and interpolated local features for speech recognition of vocal fold disordered patients. International Journal of Computers and their Applications. 22 (1), 3-11
Alsulaiman, M., Muhammad, G., Bencherif, MA., Mahmood, A. and Ali, Z., (2013). KSU rich Arabic speech database. Information (Japan). 16 (6 B), 4231-4253
Books (1)
Kijima, H. and WSEAS (Organization), (2014). Recent Advances in Intelligent Control, Modelling and Simulation: Proceedings of the 2nd International Conference on Intelligent Control, Modelling and Systems Engineering (ICMS'14) Cambridge, MA, USA, January 29-31, 2014. WSEAS Press. 9789604743650
Conferences (24)
Ali, Z., Seco De Herrera, AG., Mesallam, TA. and Muhammad, G., (2023). Computer-based Blind Diagnostic System for Classification of Healthy and Disordered Voices
E Amin, F., Hussain, M., Ali, Z., Busaleh, M. and Al Sultan, S., (2022). Development of a Secure Cloud-based Breast Cancer Diagnosis System
Ali, Z., Virginas, B., Scotney, B., Charles, D. and Ramezani, A., (2019). Design and Implementation of Autonomic Simulator
Khan, N., McClean, S., Ali, Z., Ali, A., Charles, D., Taylor, P. and Nauck, D., (2019). Predictive Process Monitoring using a Markov Model Technique
Khan, N., Ali, Z., Ali, A., McClean, S., Charles, D., Taylor, P. and Nauck, D., (2019). A Generic Model for End State Prediction of Business Processes Towards Target Compliance
Ali, Z., Imran, M., Abdul, W. and Shoaib, M., (2018). An Innovative Algorithm for Privacy Protection in a Voice Disorder Detection System
Ali, Z., Alsulaiman, M., Muhammad, G., Al-nasheri, A. and Mahmood, A., (2017). Clinical informatics: mining of pathological data by acoustic analysis
Al-nasheri, A., Ali, Z., Muhammad, G., Alsulaiman, M., Almalki, KH., Mesallam, TA. and Farahat, M., (2015). Voice pathology detection with MDVP parameters using Arabic voice pathology database
Algabri, M., Alsulaiman, M., Muhammad, G., Zakariah, M., Bencherif, M. and Ali, Z., (2015). Voice and unvoiced classification using fuzzy logic
Al-Nasheri, A., Ali, Z., Muhammad, G. and Alsulaiman, M., (2015). An investigation of MDVP parameters for voice pathology detection on three different databases
Ali, Z., Muhammad, G., Alsulaiman, M., Elamvazuthi, I. and Al-Mutib, K., (2014). Automatic speech recognition for dysphonic patients by using oriented local features
Al-nasheri, A., Ali, Z., Muhammad, G. and Alsulaiman, M., (2014). Voice pathology detection using auto-correlation of different filters bank
Alsulaiman, M., Ali, Z., Muhammad, G., Al Hindi, A., Alfakih, T., Obeidat, H. and Al-Kahtani, S., (2014). Pronunciation errors of non-Arab learners of Arabic language
Ali, Z., Alsulaiman, M., Muhammad, G., Elamvazuthi, I. and Mesallam, TA., (2013). Vocal fold disorder detection based on continuous speech by using MFCC and GMM
Alsulaiman, M., Ali, Z., Muhammed, G., Bencherif, M. and Mahmood, A., (2013). KSU Speech Database: Text Selection, Recording and Verification
Alsulaiman, M., Ali, Z. and Muhammad, G., (2012). Voice intensity based gender classification by using Simpson's rule with SVM
Bencherif, MA., Alsulaiman, M., Muhammad, G., Ali, Z., Mahmood, A. and Faisal, M., (2012). Gender effect in trait recognition
Alsulaiman, MM., Muhammad, G., Bencherif, MA., Mahmood, A., Ali, Z. and Aljabri, M., (2011). Building a Rich Arabic Speech Database
Alsulaiman, M., Muhammad, G. and Ali, Z., (2011). Comparison of voice features for Arabic speech recognition
Alsulaiman, M., Muhammad, G., Alomari, MA., Alshehri, MA., Ali, Z. and Mahmood, A., (2011). An automatic diagnostic system for medically disordered voice
Alsulaiman, M., Ali, Z. and Muhammad, G., (2011). Gender Classification with Voice Intensity
Muhammad, G., Alsulaiman, M., Mahmood, A. and Ali, Z., (2011). Automatic voice disorder classification using vowel formants
Zulfiqar, A., Muhammad, A., Martinez-Enriquez, AM. and Escalada-Imaz, G., (2010). Text-Independent Speaker Identification Using VQ-HMM Model Based Multiple Classifier System
Zulfiqar, A., Muhammad, A. and A.M., ME., (2009). A Speaker Identification System Using MFCC Features with VQ Technique
Reports and Papers (1)
Andreu-Perez, J., Pérez-Espinos, H., Timone, E., Girón-Pérez, MI., Kiani, M., Benitez-Trinidad,, AB., Jarchi, D., Rosales-Pérez, A., Ali, Z., Gatzoulis, N., Reyes-Galaviz, OF., Torres-García, AA., Reyes-García, CA. and Rivas, F., (2020). A Novel Deep Learning Based Recognition Method and Web-App for Covid-19 Infection Test from Cough Sounds with a Clinically Validated Dataset
Dataset (1)
Alsulaiman, M., Muhammad, G., Abdelkader, B., Mahmood, A. and Ali, Z., (2014).King Saud University Arabic Speech Database
Contact
Academic support hours:
During Autumn Term my Academic Support Hours are 11:00 - 12:00 on Mondays and 14:00 - 15:00 on Fridays. I will be in my office, 2NW.4B.526. I can also meet on zoom by request at these times (I will check email during these support hours and respond with a link).
