2020 applicants
People

Dr Zulfiqar Ali

Lecturer
School of Computer Science and Electronic Engineering (CSEE)
Dr Zulfiqar Ali
  • Email

  • Location

    Colchester Campus

  • Academic support hours

    Thursday 13:00 - 14:00

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, Department of Computer Engineering, King Saud University (14/10/2010 - 19/7/2018)

Research and professional activities

Research interests

Adaptive and Autonomic Systems

Open to supervise

Digital Speech Processing

Key words: Speech Recognition
Open to supervise

Machine Learning Applied to Biomedical Signals

Open to supervise

Privacy Protection

Key words: Watermarking
Open to supervise

Real-time Predictive Analytics

Open to supervise

Audio Forensics/Authentication

Key words: Audio Splicing
Open to supervise

Data Analytics

Open to supervise

Teaching and supervision

Current teaching responsibilities

  • Databases and Information Retrieval (CE205)

Publications

Journal articles (30)

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

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 (22)

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

Muhammad, G., Alsulaiman, M., Mahmood, A. and Ali, Z., (2011). Automatic voice disorder classification using vowel formants

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

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

z.ali@essex.ac.uk

Location:

Colchester Campus

Academic support hours:

Thursday 13:00 - 14:00

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