1) Ph.D. in Computer Science from  Department of Computer Science 

    University of Engineering and Technology (UET), Taxila 

    Dissertation Topic: "Computer Vision-Based Phenotyping Of Plant Disease Symptoms"

2) Master of Science in Information Technology (MSIT) from Department of Computing

    NUST School of Electrical Engineering and Technology (SEECS), Islamabad

    Dissertation Topic: "Collective Asynchronous Remote Invocation (CARI) Schedules A High-Level and Efficient Communication API for Irregular Applications"

3) Masters in Computer Science (MCS) from Department of Computer Science and IT

    University of Sargodha, Sargodha

    Dissertation Topic: "Offline Handwritten Signature Verification System Using Image Processing"

4) Bachelor in Computer Science (BCS) from Department of Computer Science

    University of Punjab, Lahore

    Dissertation Topic: "Mini-Compiler: Parser plus Syntactical Analyzer using C++"

Our research in computer vision includes applications in the areas such as 

I.F Journal Publications 

1. Rehman, Hafiz., Nida, N., Shah, S. A., Ahmad, Wakeel., Faizi, M. I., & Anwar, S. M. (2022). Automatic melanoma detection and segmentation in dermoscopy images using deep RetinaNet and conditional random fields. Multimedia Tools and Applications, 1-21.

2. Abbas, W., Adnan, S. M., Javid, M. A., Ahmad, Wakeel., & Ali, F. (2021). ANALYSIS OF TIBIA-FIBULA BONE FRACTURE USING DEEP LEARNING TECHNIQUE FROM X-RAY IMAGES. International Journal for Multiscale Computational Engineering, 19(1).

3. Ahmad, Wakeel, S. M. Shah, and Aun Irtaza. "Plants Disease Phenotyping using Quinary Patterns as Texture Descriptor." KSII Transactions on Internet and Information Systems (TIIS) 14.8 (2020): 3312-3327.

4. Ahmad, Wakeel., Carpenter, B., and Shafi, A., 2011. Collective Asynchronous Remote Invocation (CARI): A High-Level and Efficient Communication API for Irregular Applications. Procedia Computer Science, 4, pp.26-35.

HEC Recognised Journals

1. Rana, G. A., Adnan, S. M., Nida, N., Ahmad, Wakeel., & Bilal, F. (2022). Asphalt Pavement Potholes Localization and Segmentation using Deep RetinaNet and Conditional Random Fields. International Journal of Innovations in Science & Technology, 3, 126-139.

2. Shahbano; Shah, Syed Muhammad Adnan; Ahmad, Wakeel; Ilyas, Muhammad. (2020). CARRIED BAGGAGE DETECTION AND CLASSIFICATION USING MULTI-TREND BINARY CODE DESCRIPTOR AND SUPPORT VECTOR MACHINE. NED University Journal of Research, 17(4), 81-95.

3. Kanwal, M., ZESHAN, D. F., AMIN, D. R., ADNAN, D. S. M., & Ahmad, Wakeel. (2021). Artificial Intelligence Based Dynamic Wavelength Grouping for QoS in Optical Packet Switched Networks. University of Wah Journal of Science and Technology (UWJST), 5(1), 34-40.

4. Zeeshan, M., Adnan, S. M., Ahmad, Wakeel., & Khan, F. Z. (2021). Structural Crack Detection and Classification using Deep Convolutional Neural Network. Pakistan Journal of Engineering and Technology, 4(4), 50-56.

5. Ajmal, A., Ibrar, S., Ahmad, Wakeel., & Shah, S. M. A. (2021). Covid-19 Detection using Deep Convolutional Neural Networks from X-Ray Images. Pakistan Journal of Engineering and Technology, 4(2), 139-143

6. Ali, H., Adnan, S. M., Aziz, S., Ahmad, Wakeel., & Obaidullah, M. (2019). Sound classification of Parkinsonism for telediagnosis. Technical Journal, 24(01), 90-97.

7. Zafar, M. Z., Adnan, S. M., Ahmad, Wakeel., Rashid, J., & Ikram, J. (2019). Brain tumor detection and classification using geometrical shapes as texture descriptors. Technical Journal, University of Engineering and Technology (UET) Taxila, 24(1), 83-89.

8. Shah, S. A., Malik, A., Aziz, S., & Ahmad, Wakeel. (2018). Sound Recognition Aimed towards Hearing Impaired Individuals in Urban Environment using Ensemble Methods. Journal of Information Communication Technologies and Robotic Applications, 30-39.

9. ud Din, Z., Adnan, S. M., Ahmad, Wakeel., Aziz, S., Ismail, W., & Iqbal, J. (2018). Classification of Tomato Plants’ Leaf Diseases Using Image Segmentation and SVM. Technical Journal, 23(02), 81-88.

Open Positions

Ph.D. Positions: We have openings for Ph.D. positions. The potential research topics include (but are not limited to)  

1. Computer Vision, Machine Learning, Artificial Intelligence, Image Processing/Recognition
2. Pattern Matching and Recognition, Object Detection, 
3. Smart Farming, Offline Biometrics

For the open Ph.D. position, you can also choose your own research topic within our area of expertise. The research will be performed in the Computer Vision Research Group (CVRG) at the University of Engineering and Technology (UET) Taxila. The positions are available for Fall 2023 and will be filled as a suitable candidate is found.

Prospective Research Profile: A highly motivated candidate, who is eager to get involved in cutting-edge, creative research. Must hold a degree of Master of Science in Computer Science/Computer-Engineering/Information-Technology/Software-Engineering with a solid background in machine learning and computer vision. Must have excellent skills in applied mathematics, and a programming language (e.g., Python, MATLAB, C/C++). Background in Deep Learning will be an added advantage. Candidates with previous related published works will be preferred.

Masters's thesis Positions:  We have one slot for a master's thesis available for the Smart-Farming project. This project is about precision farming through unmanned-Ariel vehicles (UAVs) to increase crop production in Pakistan boost the national economy, and crop revenue, and ensure nutritional security. In order to achieve these objectives, the project will result in a form of multiple products for crop scouting, crop-disease detection, individual plant/fruit monitoring, individual plant/fruit requirement identification, pesticide suggestions, pesticide localization, environmental behaviors identification, and agri-directions.

How to Contact

Potential candidates may contact me at the email address ([email protected]), by sending a research proposal along with 2 page brief CV.

1) Reviewer: IEEE Symposium on Business, Engineering, and Industrial Applications

2) Reviewer: Transactions on Internet and Information Systems published by KSII and supported by KETI.

3) Reviewer: Multimedia Tools and Applications published by Springer

1): Member of the International Association of Engineers (IAENG), Member Number: 133952

2: Member of the International Association of Computer Science and Information Technology (IACSIT), Member Number 80347307

Postgraduate 

1. Advance Operating Systems 
2. Advance Theory of Computation 

Under Graduate

1. Theory of Automata and Formal Language
2. Compiler Construction
3. Operating System Concepts 

1) Lecturer in Computer Science at Department of Computer Science, University of Engineering and Technology (UET) Taxila - Pakistan

2) Lecturer in Software Engineering at Department of Software Engineering, Foundation University Rawalpindi Campus (FURC) - Pakistan

3) Research Scientist at Parallel Emergent and Distributed Architecture (PEDAL) Lab, School of Systems Engineering, University of Reading – United Kingdom (UK)


 

Ph.D. Students

1. Waqar Ismail                          2019
2. Muhammad Huzaifa               2019

Graduate Students

1. Nayyera Baidar Raja              2016
2. Muhammad Assam                2017
3. Shahbano                              2019
4. Madiha Ashfaq                       2019
5. Tasswar Abbas                       2021
6. Rabail Fatima                         2021
7. Abdullah Ajmal                       2022
8. Irshad Ali                                2022
9. Ammad Noor                          2023
10. Hassan Butt                           2023
11. Munzza Bibi                           2023
12. Usman Islam                          2023 

The C-VIP Research Group directed by Dr. S. M. Adnan Shah, and Dr. Rao Wakeel Ahmad is actively pursuing research in core computer vision technologies and their real-world application to improve human lives. Computer Vision is about interpreting images, therefore we are interested in all aspects of image understanding and machine-learning approaches. The group has been successfully exploring and implementing state-of-the-art computer vision (machine/deep learning) algorithms. 

Members

1). Dr. Syed M. Adnan Shah from Department of Computer Science UET Taxila

2). Dr. Rao Wakeel Ahmad from Department of Computer Science UET Taxila

Collaborators 

1). Dr. Syed M. Bilal Rizvi from Department of Computing, NUST School of Electrical Engineering and Computer Science.

2). Dr. Muhammad Ilyas from Department of Computer Science and IT, University of Sargodha 

Research Students

1). Muhammad Huzaifa (Ph.D. Student) 

2). Waqar Ismail  (Ph. D. Student) 

3). Abdullah Ajmal (Master's Student) working on Biomedical Images

4). Muhammad Hassan Butt (Master's Student) working on Biomedical Images

5). Ammad Noor (Master's Student) working on Facial Images.

6). Irshad Ali (Master's Student) working on Seismic Impedance Inversion optimization

7). Munzza Bibi  (Master's Student) is working on Automated Kinship Identification using Facial Images 

8). Usman Islam (Master's Student) is working on Leaf Image-Based Wheat Fungi Disease Identification and Classification using Deep Learning

We are hiring! We are looking for highly qualified and motivated candidates for Internships, Master's studentships, and Ph.D. research positions working in computer vision, machine learning, and related areas. See the Projects tab for our open positions.