Dr. Syed Saud Naqvi

COMSATS University Islamabad (CUI)

Department of Electrical and Computer Engi-

neering

Academic Block I

Park Road, Chak Shahzad 45550

Phone: (92-334-*******

Email: adovo4@r.postjobfree.com

Introduction

I have more than 10 years of teaching, research and industrial experience in computer science and engineering. My main research interests are in the area of computer vision with an emphasis on machine vision. My research focuses on object detection, recognition and intelligent vision systems targeted to industrial visual inspection, machine vision systems for visual recognition and medical image analysis. I am also interested in real-time embedded vision systems, data science and predictive analytics. I have been serving as a peer reviewer for international journals and conferences, supervising graduate students, undergraduate students, and summer project students. To date I have authored more than 20 international publications, including top journal publications in IEEE Transactions on Image Processing (ARC/ERA Tier A*, IF = 4.828), Pattern Recognition (ARC/ERA Tier A*, IF = 4.582), Expert Systems with Applications (Q1, IF = 3.768), Neurcomputing (Q1, IF = 3.241) and two best paper awards at the Genetic and Evolutionary Computation Conference (ARC/ERA Tier A) and NZCSRSC in 2014 and 2013, respectively. I am currently supervising four PhD students. Previously, four MSc students have successfully completed their thesis under my supervision.

I currently have over $250,000.00 research funding under a New Zealand based industrial project in col- laboration with Ministry of Business, Innovation and Employment. I have recently secured an international research grant under the KSA International Collaboration Grant for the project "Machine Learning based State-of-the-Art Eye Diseases Classi cation System (MEDiCS)", worth $0.47M as part of the research team. I have successfully completed a research project under a research grant ($20,000) from E at University UAE. Previously, I have received more than 60K NZD funding in various research projects and roles. Industrial Experience and Enterprise

Since October 2017, I am having responsibilities of a managing director/chief scienti c o cer of Visual Com- puting Technologies (VC-Tech) Islamabad Pakistan.

As part of VC-Tech, I am providing consultancy services to Leather and Shoe Research Association (LASRA) New Zealand on a six year research and development project. The project involves design and development of a machine vision system for real-time leather defect detection and is worth $250,000.00. Under this project I am supervising a PhD student and a research programmer. To date, the rst phase of the project is completed. The outcomes of the rst phase include two publications (one is under review at IEEE Access journal, while the second one is submitted to IEEE Transactions on Industrial Informatics). De- sign of the machine vision system for data acquisition is also completed. A cloud based platform for data mining is also developed as per the rst phase of the project. The platform hosts the prototype of the in-house arti cial intelligence capability to categorize and identify defects in leather samples from over the world. http://www:mbie:govt:nz/info-services/science-innovation/funding-info-opportunities/ investment-funds/strategic-science-investment-fund/funded-programmes/nz-leather-shoe-research- association

During my role at VC-Tech, I have successfully delivered a project named "E at Eye Diagnostics" to E at University Jeddah Saudia Arabia worth $20,000, which involved design and development of a Smart An- Dr. Syed Saud Naqvi 2

droid based opthalmoscope for Cataract screening. The project is in currently under clinical trials. Currently two projects namely, SMART Eye and Face Secure are in the nal stages of seed fund raising. SMART Eye is a complete solution for analyzing in-class student performance through facial expressions and activity recognition of students. Face Secure is aimed at large-scale unconstrained facial recognition for high security applications.

Awards

Received $0.47M) under the KSA International Collaboration Grant from Ministry of Education, Saudia Arabia

Member of research project from MBIE New Zealand under a SSIF agreement 2018 $250,000.00

Seed funding of around $20,000 from E at University UAE.

Received 7000 NZD funding under faculty strategic research grant program

University Research Fund from VUW 2015 (above 40k NZD)

Best Paper Award (EML Track) at the Genetic and Evolutionary Computation Conference (ARC/ERA Tier A) 2014

Faculty Strategic Research Grant from VUW ($3000 NZD) 2014

Faculty Strategic Research Grant from VUW ($3000 NZD) 2013

Best paper award at NZCSRSC 2013, Hamilton New Zealand (1500 NZD travel grant)

Victoria Doctoral Scholarship (23K NZD p. a. plus tuition fee for three years) 2012

Faculty Development Scholarship for MS Studies University of She eld United Kingdom ($7.5k GBP p. a. plus tuition fee for an year)

Research Experience

Member Image and Video Processing Research Group: COMSATS University Islamabad (CUI)

(March 2016 { Continuing)

Published 8 ISI journal publications, 4 of which are Q1 journals; supervised 4 MS students

Research on developing a machine vision system for leather defect detection and leather quality grading.

Computer aided detection and diagnosis of retinopathy related complications using machine learning and deep learning techniques.

Computer aided detection and diagnosis of Glaucoma using deep learning techniques

Research on automated early detection and diagnosis for brain tumor detection in FLAIR MRI using machine learning techniques.

Research Assistant: Victoria University of Wellington (VUW), New Zealand

(August 2015 { February 2016)

Research on human visual attention modeling for place recognition in robotic navigation. Dr. Syed Saud Naqvi 3

Presented the results of the robotic navigation work in an international conference IVCNZ 2015.

Research on learning classi er systems for feature fusion in saliency detection.

The results were published in top ranked computer vision journal Pattern Recognition Journal (ARC/ERA Tier A*, IF = 4.582). PhD Scholar: VUW New Zealand

(August 2012 { September 2015)

Published 2 high impact factor journal publications and 8 international conference publications

Research on learning feature fusion strategies for salient object detection.

Research results were published in three international journals and seven international conferences. Publications

Published Articles

Total Impact Factor: 85.56

1. Naveed, Imran Uddin Afridi, Syed Saud Naqvi, Imran Raazak, Width-wise vessel bifurcation for improved retinal vessel segmentation, Biomedical Signal Processing and Control, Volume 71, Part A, 2022, 103169, ISSN 1746-8094. (IF:3.880)

2. A. Shah, S. S. Naqvi, K. Naveed, N. Salem, M. A. U. Khan and K. S. Alimgir, "Automated Diag- nosis Of Leukemia: A Comprehensive Review," in IEEE Access, doi: 10.1109/ACCESS.2021.3114059.

(IF:3.367)

3. Aslam, M., Khan, T.M., Naqvi, S.S., Holmes, G. and Na a, R., 2021. Learning to Recognize Irregular Features on Leather Surfaces. Journal of the American Leather Chemists Association, 116(5)

(IF:1.077)

4. Rakhshanda Imtiaz, Tariq M. Khan, Syed Saud Naqvi, Muhammad Arsalan, Syed Junaid Nawaz, Screening of Glaucoma disease from retinal vessel images using semantic segmentation, Computers & Electrical Engineering, Volume 91, 2021, 107036, ISSN 0045-7906 (IF:2.663) 5. F. Abdullah et al., "A Review on Glaucoma Disease Detection Using Computerized Techniques," in IEEE Access, vol. 9, pp. 373**-*****, 2021, doi: 10.1109/ACCESS.2021.3061451. (IF:3.745) 6. Naveed, K.; Abdullah, F.; Madni, H.A.; Khan, M.A.U.; Khan, T.M.; Naqvi, S.S. Towards Automated Eye Diagnosis: An Improved Retinal Vessel Segmentation Framework Using Ensemble Block Matching 3D Filter. Diagnostics 2021, 11, 114. https://doi.org/10.3390/diagnostics11010114 (IF:3.110) 7. M. Aslam, T. M. Khan, S. S. Naqvi, G. Holmes and R. Na a, "Ensemble Convolutional Neural Networks With Knowledge Transfer for Leather Defect Classi cation in Industrial Settings," in IEEE Access, vol. 8, pp. 198***-******, 2020, doi: 10.1109/ACCESS.2020.3034731. (IF:3.745) 8. K. Minhas et al., "Accurate Pixel-Wise Skin Segmentation Using Shallow Fully Convolutional Neural Network," in IEEE Access, vol. 8, pp. 156***-******, 2020, doi: 10.1109/ACCESS.2020.3019183.

(IF:3.745)

9. T. M. Khan, M. Alhussein, K. Aurangzeb, M. Arsalan, S. S. Naqvi and S. J. Nawaz, "Residual Connection-Based Encoder Decoder Network (RCED-Net) for Retinal Vessel Segmentation," in IEEE Access, vol. 8, pp. 131***-******, 2020, doi: 10.1109/ACCESS.2020.3008899. (IF:3.745) Dr. Syed Saud Naqvi 4

10. M. Tabassum et al., "CDED-Net: Joint Segmentation of Optic Disc and Optic Cup for Glaucoma Screening," in IEEE Access, vol. 8, pp. 102***-******, 2020, doi: 10.1109/ACCESS.2020.2998635.

(IF:3.745)

11. Khan TM, MehmoodM, Naqvi SS, Butt MFU (2020) A region growing and local adaptive thresholding- based optic disc detection. PLoS ONE 15(1): e0227566. https://doi.org/10.1371/journal.pone.0227566

(IF:2.74)

12. Bashir, T., Usman, I., Albesher, A.A., Atawneh, S.H. and Naqvi, S.S., 2020. A DCT domain smart vicinity reliant fragile watermarking technique for DIBR 3D-TV. Automatika, 61(1), pp.58-65.

(IF:0.764)

13. M. Aslam, T. M. Khan, S. S. Naqvi, G. Holmes and R. Na a, "On the Application of Automated Machine Vision for Leather Defect Inspection and Grading: A Survey," in IEEE Access, vol. 7, pp. 176***-******, 2019, doi: 10.1109/ACCESS.2019.2957427. (IF:3.745) 14. A. Khawaja, T. M. Khan, K. Naveed, S. S. Naqvi, N. U. Rehman and S. Junaid Nawaz, "An Improved Retinal Vessel Segmentation Framework Using Frangi Filter Coupled With the Probabilis- tic Patch Based Denoiser," in IEEE Access, vol. 7, pp. 164***-******, 2019, doi: 10.1109/AC- CESS.2019.2953259. (IF:3.745)

15. Khan, M.A.U., Khan, T.M., Naqvi, S.S. et al. GGM classi er with multi-scale line detectors for retinal vessel segmentation. SIViP 13, 1667{1675 (2019). https://doi.org/10.1007/s11760-019-01515- 3. (IF:1.794)

16. Syed Rameez Naqvi, Anjum Zahid, Lina Sawalha, Syed Saud Naqvi, Tallha Akram, Sajjad Ali Haider, Kumar Yelamarthi, Maksim Jenihhin, An optimization framework for dynamic pipeline man- agement in computing systems, Computers & Electrical Engineering, Volume 78, 2019, Pages 242-258, ISSN 0045-7906, https://doi.org/10.1016/j.compeleceng.2019.07.013. (IF:2.663) 17. Naqvi, S.S., Fatima, N., Khan, T.M. et al. Automatic optic disk detection and segmentation by variational active contour estimation in retinal fundus images. SIViP (2019). (IF: 1.894) 18. Khan, M.A.U., Khan, T.M., Naqvi, S.S. et al. GGM classi er with multi-scale line detectors for retinal vessel segmentation. SIViP (2019). https://doi.org/10.1007/s11760-019-01515-3 (IF: 1.894) 19. Bashir, T., Usman, I., Albesher, A., Khalid A. A., Naqvi S. S.. GP based smart reversible water- marking of depth image based rendering for stereoscopic images. Multimed Tools Appl (2019) 78: 21943. https://doi.org/10.1007/s11042-019-7399-5 (IF: 2.101) 20. Saleem Saqib, Naqvi Syed Saud, Manzoor Tareq, Saeed Ahmed, ur Rehman Naveed, Mirza Jawad. A Strategy for Classi cation of \Vaginal vs. Cesarean Section" Delivery: Bivariate Empirical Mode Decomposition of Cardiotocographic Recordings. Frontiers in Physiology, 10, 2019, 246. (IF: 3.201) 21. Zaka Ur Rehman, Syed S. Naqvi, Tariq M. Khan, Muhammad Arsalan, Muhammad A. Khan, M.A. Khalil, Multi-parametric optic disc segmentation using superpixel based feature classi cation, Expert Systems with Applications, Volume 120, 2019, Pages 461-473. (IF:3.768) 22. Zaka Ur Rehman, Syed S. Naqvi, Tariq M. Khan, Muhammad A. Khan, Tariq Bashir, Fully au- tomated multi-parametric brain tumour segmentation using superpixel based classi cation, Expert Systems with Applications, Volume 118, 2019, Pages 598-613. (IF:3.768) 23. S. S. Naqvi, J. Mirza, Tariq Bashir, A uni ed framework for exploiting color coe cients for salient object detection, Neurocomputing, Volume 312, 2018, Pages 187-200. (IF:3.241) Dr. Syed Saud Naqvi 5

24. J. Mirza; B. Ali; S. S. Naqvi; S. Saleem, "Hybrid Precoding via Successive Re nement for Millimeter Wave MIMO Communication Systems," in IEEE Communications Letters, vol.PP, no.99, pp.1-1.

(IF:2.723)

25. Muhammad Iqbal, S. S. Naqvi, Will N. Browne, Christopher Hollitt, Mengjie Zhang, Learning feature fusion strategies for various image types to detect salient objects, Pattern Recognition, Volume 60, December 2016, Pages 106-120. (IF:4.582)

26. S. S. Naqvi, W. N. Browne and C. Hollitt, "Feature Quality-Based Dynamic Feature Selection for Improving Salient Object Detection," in IEEE Transactions on Image Processing, vol. 25, no. 9, pp. 4298-4313, Sept. 2016. (IF:5.072)

27. S. S. Naqvi, Will N. Browne, Christopher Hollitt, Salient object detection via spectral matting, Pattern Recognition, Volume 51, March 2016, Pages 209-224. (IF:4.582) 28. Naqvi, S. S., Naqvi, R., Riaz, R.A. and Siddiqui, F., 2011. Optimized RTL design and impiementa- tion of LZW algorithm for high bandwidth applications. Przeglad Elektrotechniczny, 87, pp.279-285.

(IF:0.244)

29. Siddiqui, M.F., Riaz, R.A. and Naqvi, S. S., 2012. Low power and area e cient DCT architecture for low bit rate communication. Przeglad Elektrotechniczny, 8, pp.216-219. (IF:0.244) 30. Naqvi, S. S., Naqvi, S.R., Khan, S.A. and Malik, S.A., 2008. Application speci c scalable architec- tures for advanced encryption standard (aes) algorithm. WSEAS Transactions on Electronics, 5(10), pp.427-436.

31. Naqvi, S.R., Naqvi S.S., Rehman, F., Naghman, F., Tariq, R. and Zainab, A., Scalable Architecture for Discrete Cosine Transform Computation Engine Based on Array Processors. International Journal of Engineering & Technology, IJET, 9(9).

International Refereed Conference Papers

1. Khan T.M., Robles-Kelly A., Naqvi S.S., T-Net: A Resource-Constrained Tiny Convolutional Neural Network for Medical Image Segmentation, to appear in WACV 2022 Waikoloa, Hawaii. 2. Aslam, M., Khan, T.M., Naqvi, S.S., Holmes, G., Putting Current State Object Detectors to the Test: Towards Industry Applicable Leather Surface Defect Detection, to appear in Digital Image Computing: Techniques and Applications (DICTA) 2021 Goald Coast Australia. 3. Khan T.M., Robles-Kelly A., Naqvi S.S., RE-Net: A Convolutional Neural Network for Retinal Vessel Segmentation, to appear in Digital Image Computing: Techniques and Applications (DICTA) 2021 Goald Coast Australia.

4. Khan T.M., Robles-Kelly A., Naqvi S.S., Arsalan M. (2021) Residual Multiscale Full Convolutional Network (RM-FCN) for High Resolution Semantic Segmentation of Retinal Vasculature. Structural, Syntactic, and Statistical Pattern Recognition. S+SSPR 2021. Lecture Notes in Computer Science, vol 12644. Springer, Cham.

5. Khan T.M., Robles-Kelly A., Naqvi S.S. (2020) A Semantically Flexible Feature Fusion Network for Retinal Vessel Segmentation. In: Neural Information Processing. ICONIP 2020. Communications in Computer and Information Science, vol 1332. Springer, Cham. https://doi.org/10.1007/978-3-030- 63820-7 18.

6. T. M. Khan, S. S. Naqvi, M. Arsalan, M. A. Khan, H. A. Khan and A. Haider, "Exploiting Residual Edge Information in Deep Fully Convolutional Neural Networks For Retinal Vessel Segmentation," 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1-8, doi: 10.1109/IJCNN48605.2020.9207411.

Dr. Syed Saud Naqvi 6

7. T. M. Khan, F. Abdullah, S. S. Naqvi, M. Arsalan and M. A. Khan, "Shallow Vessel Segmentation Network for Automatic Retinal Vessel Segmentation," 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1-7, doi: 10.1109/IJCNN48605.2020.9207668. 8. S. S. Naqvi and W. N. Browne, "Adapting learning classi er systems to symbolic regression," 2016 IEEE Congress on Evolutionary Computation (CEC), Vancouver, BC, 2016, pp. 2209-2216. 9. H. Williams, S. S. Naqvi, W. N. Browne and C. Hollitt, "Introduction of a human based attention model for robotic navigation," 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ), Auckland, 2015, pp. 1-6.

10. Muhammad Iqbal, S. S. Naqvi, Will N. Browne, Christopher Hollitt, and Mengjie Zhang, \Salient object detection using learning classi er systems that compute action mappings" In Proceedings of the conference on Genetic and evolutionary computation (GECCO ’14). ACM, New York, NY, USA, 525-532. (Best Paper Award: EML track)

11. S. S. Naqvi, Will N. Browne, Christopher Hollitt, \Genetic algorithms based feature combination for salient object detection, for autonomously identi ed image domain types. IEEE Congress on Evolutionary Computation" 2014: 109-116.

12. S. S. Naqvi, Will N. Browne, Christopher Hollitt, \Evolutionary Feature Combination Based Seed Learning for Di usion-Based Saliency" SEAL 2014: 822-834. 13. Naqvi, S. S., Will N. Browne, and Christopher Hollitt. "Optimizing visual attention models for predicting human xations using Genetic Algorithms." In 2013 IEEE Congress on Evolutionary Com- putation, pp. 1302- 1309. IEEE, 2013.

14. S. S. Naqvi, Will N. Browne, Christopher Hollitt, \Combining object-based local and global feature statistics for salient object search". IVCNZ 2013: 394-399. 15. Naqvi, S. S., Will Browne and Christopher Hollitt, Optimizing Bio-Inspired Visual Attention Model Using Genetic Algorithm For Predicting Human Fixations, NZCSRSC 2013 Hamilton New Zealand

(Best paper Award; prize money 1500 NZD).

Supervision Experience

In Progress

PhD Thesis (Masood Aslam, Fall 2019, CUI; LASRA Funded) Leather defect classi cation for quality grading using deep learning

PhD Thesis (Shahwaze, Fall 2019, CUI)

Retinal image analysis for medical diagnosis using machine vision

PhD Thesis (Asim Nazir, Fall 2019, CUI; HEC funded) Activity recognition in real-world crowd scenes using deep learning

PhD Thesis (Afshan Shah, Spring 2019, CUI)

Deep learning based leukaemia diagnosis in microscopy images Completed

MS Thesis (Rakhshanda Imtiaz, Spring 2019, CUI)

Glucoma detection and diagnosis using fully convolutional neural networks Dr. Syed Saud Naqvi 7

MS Thesis (Mannan, Spring 2019, CUI)

Retinopathy leakage detection, segmetation and classi cation using deep neural networks

MS Thesis (Zaka ur Rehman, Spring 2018, CUI)

Automated early detection and diagnosis for brain tumor detection in FLAIR MRI using machine learning techniques

MS Thesis (Nayab Fatima, Fall 2017, CIIT)

Salient feature extraction and aggregation using machine learning for early detection and diagnosis of diabetic retinopathy

Undergraduate Final Year Project (Raza Mehmood, Asma Mir) Fall 2018, CUI) Multi-layer authentication based automated attendance system

Undergraduate Final Year Project (Sumair, Hamza and Hassan, Fall 2017, CIIT) An automated attendance system was developed using Implementation of a face based attendance system using raspberry pi

Undergraduate Final Year Project (Wajih, Shahwaze, Fall 2017, CIIT) Implementation of heart rate detection system using video processing - Won 1 st

position out in com-

puter engineering stream in CPCE 2018.

Summer Research Project (Peter Clarke, Summer 2015, VUW) Research on the adaptive selection of saliency features for real-time salient object detection on Pioneer P3-DX

Teaching Experience

Assistant Professor: CUI

(March 2016 { Continuing)

Developed course outlines/contents, delivered lectures, designed and evaluated course assignments and examination papers for the following courses:

1. ECI671 Arti cial Intelligence

2. ECI748 Machine Learning

3. ECI674 Pattern Recognition

Supervised and/or evaluated undergraduate development projects and postgraduate research projects.

Trained/guided postgraduate students to publish the conducted research work.

Mentored undergraduate students to guide in any course related and general institute level concern.

Successfully sought accreditation under Washington Accord on the OBE system for the Bachelor of Science in Computer Engineering program at ECE department, enabling students for job search visa in partnering countires.

Lecturer Information Technology: WelTec Institute of Technology New Zealand

(August 2015 { February 2016)

Taught the course IT6268 IT Project Management and conducted the associated lab.

Designed and evaluated online and home assessments and examination papers. Dr. Syed Saud Naqvi 8

Tutor: VUW New Zealand

(July 2014 { October 2015)

Conducted labs for the course of NWEN242 Computer Organization.

Conducted labs for the course of ENGR101 Engineering Fundamentals.

Contributed to development of marking scheme and marked labs and assignments. Lecturer: CIIT Islamabad

(September 2007 { August 2012)

Courses taught:

{ CSC103 Programming Fundamentals

{ CSC112 Algorithms and Data Structures

{ EEE343 Computer Organization

{ EEE445 Advance Computer Architecture

Designed and evaluated assessments and examination papers. Administrative Experience

I have more than 5 years of administrative experience in various roles and positions at COMSATS Uni- versity Islamabad. I am currently working as Incharge Computer Engineering for the last two years and am responsible for program accreditation under the Washington Accord, outcome based education (OBE) standard. I am also involved in various administrative committees at the departmental level including:

Member, Departmental Academic Review Committee

Member, Undergraduate Committee

Head, Program Academic Review Committee

Member, Graduate Advisory Committee

Member, Course Review Committee

Employment History

Managing Director: Visual Computing Technologies Islamabad

(October 2017{to-date)

Assistant Professor: COMSATS University Islamabad

(March 2016{to-date).

Research Assistant: Victoria University of Wellington New Zealand

(September 2015{February 2016).

Lecturer-Information Technology: WelTec Institute of Technology New Zealand

(August 2015{Feb 2016).

Lecturer: CIIT Islamabad

(September 2007{July 2012).

Design Engineer: RIMS Islamabad

(August 2005{July 2006)

Dr. Syed Saud Naqvi 9

Skills

Leading/supervising research based projects

Research and development for real-time solutions

Object detection and recognition

Machine vision systems for medical image diagnosis

Machine vision systems for industrial visual inspection

Programming in Python (scikit-learn, numpy, scipy), C/C++, MATLAB and Java

GPU (CUDA C, MATLAB PCT, Keras with Tensor ow)

Software engineering and databases

Education

PhD Computer Systems Engineering: Victoria University of Wellington New Zealand August 2012{September 2015.

MSc Electrical Engineering: University of She eld United Kingdom September 2006{September 2007.

BSc Computer Engineering: COMSATS Institute of Information Technology (CIIT) Islamabad August 2001{August 2005.

References

A/Prof. Will Browne adovo4@r.postjobfree.com

School of Engineering and Computer Science,

Victoria University of Wellington New Zealand

Senior Lecturer Christopher Hollitt adovo4@r.postjobfree.com School of Engineering and Computer Science,

Victoria University of Wellington New Zealand

Last updated: October 1, 2021

Contact this candidate