Dr. Ashfaq Ahmad received his MS and PhD degree in computer Science form Abdul wali khan University Mardan, KPk, Pakistan. Earlier he obtained his BS degree in computer science form university of Peshawar. His area of interest includes Machine Learning, deep Learning, and bioinformatics. Moreover, he has more than 10 years of academic, research & management skills. During his PhD he worked in the direction of interface of deep learning, machine learning, image processing and some emerging data-rich areas such as bioinformatics. He published more than ten research papers in the reputed Q1 journals.

He also take interest in theoretically sound and empirically efficient evolutionary and machine learning algorithms to analyze, understand, and develop computational models on high volumes of multidimensional and heterogeneous data. Furthermore, he developed and novel deep learning and machine learning based models using the massive sets of biological sequences for addressing a specific challenging problem by taking full advantage of domain-specific knowledge.


  1. A Ahmad, S Akbar, M Tahir, M Hayat, F Ali,  iAFPs-EnC-GA: Identifying antifungal peptides using sequential and evolutionary descriptors based multi-information fusion and ensemble learning approach. Chemometrics and Intelligent Laboratory Systems 222, 104516 (2022)(impact factor=4.175)


  1. A Ahmad, S Akbar, M Hayat, F Ali,  S Khan, M Sohail : Identification of antioxidant proteins using a discriminative intelligent model of k-spaced amino acid pairs based descriptors incorporating with ensemble feature selection, Biocybernetics and Biomedical Engineering (2020)(Impact factor=5.687)



  1. A Ahmad, S Akbar, S Khan, M Hayat, F Ali, A Ahmed, M Tahir, Deep-AntiFP: Prediction of antifungal peptides using distanct multi-informative features incorporating with deep neural networks,

Chemometrics and Intelligent Laboratory Systems 208, 104214 (2021) (impact factor=4.175)


  1. S Akbar, A Ahmad, M Hayat, S Khan, AU Rehman, F Ali, iAtbP-Hyb-EnC: Prediction of antitubercular peptides via heterogeneous feature representation and genetic algorithm based ensemble learning model, Computers in Biology and Medicine, 137, 104778 (2021)(impact factor=6.698)


  1. A Khan, J Uddin, F Ali, A Ahmad, O Alghushairy, A Banjar, A Daud, Prediction of antifreeze proteins using machine learning, Scientific Report 12(1), 1-10, 20672 (2022)(impact factor=5.523)


  1. F Ali, H Kumar, S Patal, A Ahmad, A Babour, A Daud, Deep-GHBP: improving prediction of Growth Hormone-binding proteins using deep learning model, Biomedical signals processing And Control 78,103856 (2022)(impact factor=5.076)                                                                                                              


  1. S Akbar, A Ahmad, M Hayat, S Khan, F Ali, S. Gul :Prediction of Antiviral Peptides Using Transform Evolutionary & SHAP Analysis based Descriptors by Incorporation with Ensemble Learning Strategy, Chemometrics and Intelligent Laboratory Systems,230,  104682 (2022)(impact factor=4.175)



  1. A Ghulam, F Ali, R Sikandar, A Ahmad, Aftab A, S patal: Deep learning based model for improve prediction of anticancer peptides using 2DCNN. Chemometrics and Intelligent Laboratory Systems 226, 104589 (2022)(impact factor=4.175)


  1. J Hassan, KR Malik, G Irtaza, A Ghulam, A Ahmad : Disease Identification using Deep Learning in Agriculture: A Case Study of Cotton Plant, Transaction on software Engineering VFAST vol. 10,No.04  (2022)(Open journal system)


  1. S. Akbar, A. Ahmad, M. Hayat, Face Recognition Using Hybrid Feature Space in Conjunction with Support Vector Machine, J. Appl. Environ. Biol. Sci., 5(7)28-36, 2015 (ISI Web of science/ knowledge)


  1. S. Akbar, A. Ahmad, M. Hayat, Identification of Fingerprint Using Discrete Wavelet Transform in Conjunction with Support Vector Machine, IJCSI International Journal of Computer Science Issues, September 2014, Vol. 11, Issue 5, No 1,


  1. S. Akbar, A. Ahmad, M. Hayat, Iris detection by discrete sine transform based feature vector using random forest, J. Appl. Environ. Biol. Sci., 4(8S) 19-23, 2014 (ISI Web of science/ knowledge)


  1. ZU Khan, A. Ahmad and M. Hayat, Hourly Based Climate Prediction Using Data Mining Techniques by Comprising Entity Demean Algorithm”, Middle-East Journal of Scientific Research, 2015 23 (1): 35-40, 2015ISSN1990-9233 © IDOSI Publications.


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