College of Electrical & Mechanical Engineering
Researches Industrial AI and IoT (IAI) Research Group

Industrial AI and IoT (IAI) Research Group

Our research group is dedicated to tackling real-world industrial challenges through the application of state-of-the-art AI solutions. Our mission is to equip our members with cutting-edge expertise in AI and Internet-of-Things (IoT), complemented by hands-on training, to empower them in delivering robust solutions tailored to industrial needs.

With a keen focus on emerging trends in agentic AI, generative AI, deep learning, reinforcement learning, IoT and human-machine interaction, we strive to produce impactful research outcomes with tangible benefits for the local industry in Pakistan.

Join us as we pave the way for innovation, driving transformative advancements at the intersection of industry and artificial intelligence.

Members:

Name Designation Specialization Contact
Dr Ayesha Zeb Assistant Professor Artificial Intelligence, Machine learning, IoT [email protected]
Dr Zohaib Riaz Associate Professor of Practice Distributed systems, machine learning, Information privacy [email protected]
Dr Umar Shahbaz Khan Professor IoT, embedded systems [email protected]
AP Kanwal Naveed Assistant Professor Artificial Intelligence, Reinforcement learning [email protected]
Mr. Usman Asad Senior lecturer Robotics, Digital twins [email protected]

Journal Papers:

  1. Mahboob, Z., Khan, M. A., Lodhi, E., Nawaz, T., & Khan, U. S. (2024). Using segFormer for effective semantic cell segmentation for fault detection in photovoltaic arrays. IEEE Journal of Photovoltaics.
  2. Ramsha Shahid, Waqar S. Qureshi, Umar S. Khan, Arslan Munir, Ayesha Zeb, Syed Imran Moazzam, “Aerial imagery-based tobacco plant counting framework for efficient crop emergence estimation”, Computers and Electronics in Agriculture, Volume 217, 4th Jan 2024,108557, ISSN 0168-1699, https://doi.org/10.1016/j.compag.2023.108557. (IF 8.3)
  3. Muhammad Umair, Nasir Rashid, Umar Shahbaz Khan, Amir Hamza, Javaid Iqbal, “Emotion Fusion-Sense (Emo Fu-Sense) – A novel multimodal emotion classification technique”, Elsevier, Biomedical Signal Processing and Control, Vol 94,2024,106224, 28th Mar 2024, ISSN 1746-8094, https://doi.org/10.1016/j.bspc.2024.106224. (IF: 5.1)
  4. Wahab, Umar S. Khan, T. Nawaz, H. Akbar, S. T. H. Shah, A. Khalid, Ali. R. Ansari, R, Nawaz., “Improved Accuracy for Subject-Dependent and Subject-Independent Deep Learning-Based SSVEP BCI Classification: A User-Friendly Approach,” in IEEE Access, vol. 12, pp. 115935-115950, 12th Aug 2024, doi: 10.1109/ACCESS.2024.3442235. (IF: 3.4)
  5. Shabbir Minhas, H. Nazeer, N. Naseer, Umar S. Khan, A. R. Ansari and R. Nawaz, “Enhancing Classification Accuracy of fNIRS-BCI for Gait Rehabilitation,” in IEEE Access, vol. 12, pp. 117944-117954, 13th Aug 2024, doi: 10.1109/ACCESS.2024.3443066. (IF: 3.4)
  6. Haroon, H. Jabbar, U. Shahbaz Khan, T. Ted. Jeong and N. Naseer, “Mental Fatigue Classification Aided by Machine Learning-Driven Model Under the Influence of Foot and Auditory Binaural Beats Brain Massages via fNIRS,” in IEEE Access, vol. 12, pp. 187160-187191, 29th Nov 2024, doi: 10.1109/ACCESS.2024.350887. (IF 3.4)
  7. Amjad, N. Asif, H. Elahi, U. Shahbaz Khan, H Akbar, A. R. Ansari, R. Nawaz, “Precision Segmentation and Binary Masking of Skin Lesions in Automated Dermatological Diagnostics Using Detectron2,” in IEEE Access, vol. 12, pp. 187696-187708, 11th Dec 2024, doi: 10.1109/ACCESS.2024.3514865 (IF 3.4)
  8. Wahab, A., Khan, U. S., Nawaz, T., Shah, S. T. H., Izhar, U., & Zeb, A. (2025). An optimized Impulse Factor-based VMD-EMD approach to improve SSVEP accuracy for BCI Systems. Results in Engineering, 25, 104203.

Conference Papers:

  1. Mahboob, Z., Zeb, A., & Khan, U. S. (2023, October). YOLO v5, v7 and v8: A Performance Comparison for Tobacco Detection in Field. In 2023 3rd International Conference on Digital Futures and Transformative Technologies (ICoDT2) (pp. 1-6). IEEE.
  2. Mahboob, S. Sadiq, U. S. Khan, A. Zeb and M. I. Tiwana, “MASA: Multi Agent Situational Awareness for Visually Impaired,” 2024 21st International Bhurban Conference on Applied Sciences and Technology (IBCAST), Murree, Pakistan, 2024, pp. 349-354, doi: 10.1109/IBCAST61650.2024.10877205.
  3. Ahmad, S., Imran, S. B., Asad, U., & Zeb, A. (February, 2025). In 2025 11th International Conference on Mechatronics and Robotics Engineering (ICMRE) (pp. 1 -6).
  4. A. Khan, U. Farooq, A. Zeb, I. Awais, M. Q. Tariq and M. Tiwana, “A Soft Robotics Approach to Prosthetic Hands: Integrating 3D Printing Techniques and Embedded Vision,” 2024 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan, 2024, pp. 1-7, doi: 10.1109/ICRAI62391.2024.10894254.
  5. Farooq, W. A. Khan, A. Zeb, I. Awais, M. Tiwana and M. Q. Tariq, “A Lightweight CNN for RGB-D Grasp Classification in Computer Vision-Based Prosthetic Hands,” 2024 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan, 2024, pp. 1-6, doi: 10.1109/ICRAI62391.2024.10894378.
  6. Shabbir, N., Ahmed, R., Raza, M. W., Zeb, A., Elahi, H., & Waheed, H. (2025, April). Comparative Performance and Resource Utilization Analysis of OCR Models for Number Plate Recognition on Raspberry Pi 4. In 2025 5th International Conference on Communication Technologies (ComTech)(pp. 1–6). IEEE.
  7. Naveed, M. L. Anjum, W. Hussain and D. Lee, “Deeper Introspective SLAM: How to Avoid Tracking Failures Over Longer Routes?,” 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, United Arab Emirates, 2024, pp. 635-641, doi: 10.1109/IROS58592.2024.10801911.
  8. Ahmed, N. Shabbir, M. W. Raza, A. Zeb and H. Elahi, “Evaluation of Model Degradation in PaddleOCR, UltOCR, and TrOCR Across Baseline and TensorFlow Lite Environments,” 2024 International Conference on Robotics and Automation in Industry (ICRAI), Rawalpindi, Pakistan, 2024, pp. 1-5, doi: 10.1109/ICRAI62391.2024.10894257.

Patents:

  1. Utility Patent: “An Adaptive AI enabled System for Navigation of Visually Impaired Persons”, Patent Application No. 418/2024, 13 June 2024 – Filed

Funding:

  1. “SceneScribe – AI Enabled Intelligent Glasses for Assistance of Visually Impaired” – 1 Million PKR
  2. “Virtual Telepresence Robot” – 1 Million PKR
  3. “Humanoid Assistive Robotic Platform (HARP)” – 1 Million PKR

Featured projects:

  1. SceneScribe – AI Enabled Intelligent Glasses for Assistance of Visually Impaired
  2. Intelligent Prosthetic Hand: A 3D Printed Solution Combining Soft Robotics, Sensor Fusion, and Computer Vision
  3. CleanBot: Autonomous Indoor Cleaning Robot
  4. Smart fruit harvesting robot based on UR5 manipulator
  5. Humanoid Assistive Robotic Platform (HARP)
  6. Autovendi: Autonomous food delivery robot
  7. Electrospin: A Sustainable Smart Transport Solution

Contact Person:

Dr Ayesha Zeb

Head IAI research group

Email: [email protected]

Contact: +92-51-5444-4446

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