Dr. Zar Nawab Khan Swati

Dr. Zar Nawab Khan Swati

Designation: Assistant Professor

Phone: 03459462491

Email: zarnawab@kiu.edu.pk

Status: Permanent

Qualification

  • MS in Computer Science COMSATS Institute of Information Technology Abbottabad Pakistan
  • PhD in Computer Science and Technolgy Computer Science and Engineering, Nanjing University of Science and Technology, P.R. China
  • BS (CS) Hazara University Mansehra KPK, Pakistan

Experience

  • Assistant Professor (BPS-19) Karakoram International University Gilgit-Baltistan, Pakistan
  • Research Associate COMSATS Institute of Information Technology Abbottabad Pakistan
  • Research Associate COMSATS Institute of Information Technology Abbottabad Pakistan
  • Chairman, Department of Computer Science Karakoram International University Gilgit-Baltistan, Pakistan

Projects

  • Deep Learning

Research Interests

  • Artificial Intelligence
  • Deep Learning

  • Computer Vision
  • Image Processing
  • Pattern Recognition and Machine Learning
  • Brain Image analysis
  • BioInformatics

Publications

  • On REE and EER Methods for Mining Corner Points on the Images, Sarfraz, M. and Swati, Z. (2014) On REE and EER Methods for Mining Corner Points on the Images. Journal of Computer and Communications, 2, 91-96. doi: 10.4236/jcc.2014.22016.
  • Mining Corner Points on the Generic Shapes, M. Sarfraz and Z.N.K Swati, "Mining Corner Points on the Generic Shapes," Open Journal of Applied Sciences, Vol. 3 No. 1B, 2013, pp. 10-15. DOI: 10.4236/ojapps.2013.31B003.
  • A Novel Corner Detector Approach using Sliding two Ellipses and one rectangle, Swati, Z.N.K.; Sarfraz, M.; Zaman, S.; A Novel Corner Detector Approach using Sliding two Ellipses and one rectangle, International Conference on Frontier of Information TechnologyFIT’09, December 16–18, 2009, CIIT, Abbottabad, Pakistan. ACM. ISBN: 978-1-60558-642-7 DOI: 10.1145/1838002.1838086
  • A Novel Corner Detector Approach using Sliding Ellipses, Sarfraz, M.; Swati, Z.N.K.; Zaman, S.; A Novel Corner Detector Approach using Sliding Ellipses, Computer Graphics, Imaging and Visualization, 2009. CGIV '09. Sixth International Conference on 11-14 Aug. 2 009 Page(s): 193 - 198 Sponsored by IEEE Computer Society. ISBN: 978-0-7695-3789-4. DOI:10.1109/CGIV.2009.33
  • Improving prediction of extracellular matrix proteins using evolutionary information via a grey system model and asymmetric under-sampling technique, Kabir, M., Ahmad, S., Iqbal, M., Swati, Z. N. K., Liu, Z., & Yu, D. J. (2018). Improving prediction of extracellular matrix proteins using evolutionary information via a grey system model and asymmetric under-sampling technique. Chemometrics and Intelligent Laboratory Systems, 174, 22-32.
  • DBPPred-PDSD: Machine Learning Approach for Prediction of DNA-binding Proteins using Discrete Wavelet Transform and Optimized Integrated Features Space, DBPPred-PDSD: Machine Learning Approach for Prediction of DNA-binding Proteins using Discrete Wavelet Transform and Optimized Integrated Features Space F Ali, M Kabir, M Arif, ZNK Swati, ZU Khan, M Ullah… - Chemometrics and Intelligent Laboratory Systems, 2018
  • Intelligent computational method for discrimination of anticancer peptides by incorporating sequential and evolutionary profiles information, Intelligent computational method for discrimination of anticancer peptides by incorporating sequential and evolutionary profiles information M Kabir, M Arif, S Ahmad, Z Ali, ZNK Swati, DJ Yu - Chemometrics and Intelligent Laboratory Systems, 2018
  • Prediction of membrane protein types by exploring local discriminative information from evolutionary profiles, M Kabir, M Arif, F Ali, S Ahmad, ZNK Swati, DJ Yu - Analytical Biochemistry, 2018
  • Improving secretory proteins prediction in Mycobacterium tuberculosis using the unbiased dipeptide composition with support vector machine, Saeed Ahmed, Muhammad Kabir, Muhammad Arif, Zakir Ali, Farman Ali, Zar Nawab Khan Swati Improving secretory proteins prediction in Mycobacterium tuberculosis using the unbiased dipeptide composition with support vector machine International Journal of Data Mining and Bioinformatics, March 2019
  • Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning, Z. N. K. Swati et al., "Content-Based Brain Tumor Retrieval for MR Images Using Transfer Learning," in IEEE Access, vol. 7, pp. 17809-17822, 2019.
  • Investigating Executive Control Network and Default Mode Network Dysfunction in Major Depressive Disorder, Zhao, Q., Swati, Z. N.K, Metmer, H., Sang, X., & Lu, J. (2019). Investigating Executive Control Network and Default Mode Network Dysfunction in Major Depressive Disorder. Neuroscience Letters.
  • DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information, Ali, F., Ahmed, S., Swati, Z. N. K., & Akbar, S. (2019). DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information. Journal of Computer-Aided Molecular Design, 1-14.
  • Functional Segregation of Executive Control Network and Frontoparietal Network in Alzheimer's disease, Zhao, Q., Sang, X., Metmer, H., Swati, Z. N. K., Lu, J., & Alzheimer's Disease NeuroImaging Initiative. (2019). Functional Segregation of Executive Control Network and Frontoparietal Network in Alzheimer's disease. Cortex.
  • Brain tumor classification for MR images using transfer learning and fine-tuning, Swati, Z. N. K., Zhao, Q., Kabir, M., Ali, F., Ali, Z., Ahmed, S., & Lu, J. (2019). Brain tumor classification for MR images using transfer learning and fine-tuning. Computerized Medical Imaging and Graphics.
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