College of Electrical & Mechanical Engineering
Researches Vision and Machine Learning (VML) Research Group

Vision and Machine Learning (VML) Research Group

Introduction

The Vision and Machine Learning (VML) Group is dedicated to conducting highly impactful research on the cutting edge of computer vision, machine learning, their application areas as well as real-time software and hardware implementations. Both fundamental and applied research is carried out. The group consists of experts in object tracking, detection, recognition and segmentation, scene understanding (recognition, layout estimation), stereo and multi-view vision, structure from motion, shape from texture, unsupervised and supervised learning methods, and augmented reality.

Team

Name Role Research Area Email
Dr Ahmad Rauf Subhani Head Computer Vision, Signal Processing​ [email protected]​
Dr. Qasim Umar Khan Associate Head Machine Learning, Artificial neural network, Digital Signal Processing [email protected]
Dr Usman Ali Member Embedded Systems, Adaptive filtering, Machine learning [email protected]
Ms. Sobia Hayee Member Control Systems, Image Processing [email protected]

Publications (Journals)

  1. Muhammad Najam Dar, Muhammad Usman Akram, Ahmad Rauf Subhani, Sajid Gul Khawaja, Constantino Carlos Reyes-Aldasoro, and Sarah Gul. “Insights from EEG analysis of evoked memory recalls using deep learning for emotion charting.” Scientific Reports 14 (1), p 17080, 2024. (IF: 4.6)
  2. Syeda Noor-Ul-Huda Safder, Muhammad Usman Akram, Muhammad Najam Dar, Aliya Ashraf Khan, Sajid Gul Khawaja, Ahmad Rauf Subhani, Imran Khan Niazi, and Sarah Gul. “Analysis of EEG signals using deep learning to highlight effects of vibration-based therapy on brain.” Biomedical Signal Processing and Control 83, p 104605, 2023. (IF: 5.1)
  3. Wajid Mumtaz, Hafeez Ullah Amin, Abdul Qayyum, and Ahmad Rauf Subhani. “EEG-based assistive robotics for rehabilitation.” Frontiers in Neurorobotics 16, p 952495, 2022. (IF: 2.6)
  4. F. Naqvi, S. S. A. Ali, N. Yahya, M. A. Yasin, Y. Hafeez, A. R. Subhani, S. H. Adil, U. M. Al Saggaf, and M. Moinuddin, “Real-Time Stress Assessment Using Sliding Window Based Convolutional Neural Network”, MDPI Sensors, 20 (16), p 1-17, 2020. (IF: 3.30)
  5. Xia, A. S. Malik, and A. R. Subhani, “A physiological signal-based method for early mental-stress detection”, Biomedical Signal Processing and Control, 46, p 18-32, 2018. (IF: 2.78)
  6. Ahmad Rauf Subhani, Nidal Kamel, Mohamad Naufal Mohamad Saad, Nanda Nandagopal, Kenneth Kang and Aamir Saeed Malik, “Mitigation of Stress: New Treatment Alternatives”, Cognitive Neurodynamics, 12(1), p 1-20, 2018. (IF: 1.828)
  7. Hafeez Ullah Ullah Amin, Aamir S Malik, Wajid Mumtaz and Ahmad R Subhani, “Classification of EEG signals based on pattern recognition approach”, Frontiers in Computational Neuroscience, 11, 103, 2017. (IF: 1.82)
  8. Ahmad Rauf Subhani, Wajid Mumtaz, Mohamad Naufal bin Mohamad Saad, Nidal Kamel and Aamir Saeed Malik, “Machine Learning Framework for the Detection of Mental Stress at Multiple Levels”, IEEE Access, 5, p 13545-13556, 2017. (IF: 3.24)
  9. Humaira Nisar, Aamir Saeed Malik, Rafi Ullah, Seong-O Shim, Abdullah Bawakid, Muhammad Burhan Khan, Ahmad Rauf Subhani, “Tracking of EEG activity using motion estimation to understand brain wiring”, Advances in Experimental Medicine and Biology, 823, p 159-174, 2015. (IF: 2.0)
  10. Ahmad Rauf Subhani, Likun Xia and Aamir Saeed Malik, “Association of EEG Scalp Potential with Autonomic Nervous System”, Advanced Science Letters, 19 (5), p 1340-1344, 2013. (IF: 1.25)
  11. Ahmad Rauf Subhani, Likun Xia and Aamir Saeed Malik, “Association of EEG scalp potentials with autonomic innervations of the heart”, EUROPEAN JOURNAL OF NEUROLOGY, 19. p 129, 2012. (IF: 3.76)
  12. Farkhanda Aziz, Azhar Ul-Haq, Shahzor Ahmad, Yousef Mahmoud, Marium Jalal and Usman Ali, “A Novel Convolutional Neural Network-Based Approach for Fault Classification in Photovoltaic Arrays”. IEEE Access, 2020.
  13. Mohammad Bilal Malik and Usman Ali, “Adaptive Thresholding using Particle Filter for Tracking Small and Low Contrast Objects”, IEEE 10th International Conference on Information Sciences, Signal Processing and their Applications, 2010.
  14. Usman Ali, Mohammad Bilal Malik and Khalid Munawar, “FPGA/Soft-Processor Based Real-Time Object Tracking System”, IEEE 5th Southern Programmable Logic Conference, pp. 33-37, 2009.

Publications (Conference)

  1. Ng Kah Kit, Hafeez Ullah Amin, and Ahmad Rauf Subhani. “Discrete Wavelet Transform based EEG Feature Extraction and Classification for Mental Stress using Machine Learning Classifiers.” In 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), pp. 1-5. IEEE, 2022.
  2. R. Subhani, W. Mumtaz, N. Kamil, N. M. Saad, N. Nandagopal, and A. S. Malik, “MRMR based feature selection for the classification of stress using EEG”, Eleventh International Conference on Sensing Technology (ICST), 2017, pp. 1-4.
  3. Ahmad Rauf Subhani, Aamir Saeed Malik, Nidal Kamil and Mohamad Naufal Mohamad Saad, “Difference in brain dynamics during arithmetic task performed in stress and control conditions”, IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES), Kuala Lumpur, Malaysia, Dec. 4–8, 2016.
  4. Ahmad Rauf Subhani, Aamir Saeed Malik, Nidal Kamel and Mohamad Naufal bin Mohamad Saad, “Using resting state coherence to distinguish between low and high stress groups”, 6th IEEE International Conference on Intelligent and Advanced Systems (ICIAS), Kuala Lumpur, Malaysia, Aug. 15–17 2016.
  5. Ahmad Rauf Subhani, Aamir Saeed Malik, Nidal Kamel, Naufal Saad and D Nandagopal, “Experimental evidence for the effects of the Demand-Control model on the cognitive arousal: An EEG based study”, 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Milan, Italy, Aug. 25-29 2015.
  6. Hafeez Ullah Amin, Aamir Saeed Malik, Ahmad Rauf Subhani, Nasreen Badruddin and Weng-Tink Chooi, “Dynamics of Scalp Potential and Autonomic Nerve Activity during Intelligence Test”, 20th International Conference on Neural Information Processing (ICONIP), Daegu, South Korea, Nov. 3-7, 2013.
  7. Ahmad Rauf Subhani, Likun Xia, Aamir Saeed Malik and Zahiruddin Othman, “Quantification of Physiological Disparities and Task Performance in Stress and Control Conditions”, 35th IEEE conference of Engineering in Medicine and Biology (EMBC), Osaka, Japan, Jul. 3-7, 2013.
  8. Ahmad Rauf Subhani, Likun Xia and Aamir Saeed Malik, “Association of Autonomic Nervous System and EEG Scalp Potential during Playing 2D Grand Turismo 5”, 34th IEEE conference of Engineering in Medicine and Biology (EMBC), San Diego, California, USA, Aug.28-Sep.01, 2012.
  9. Ahmad Rauf Subhani, Likun Xia, Aamir Saeed Malik, “Association of Mental Stress with Video Games”, 4th IEEE International Conference on Intelligent & Advanced Systems (ICIAS), Kuala Lumpur, Malaysia, Jun. 12-14, 2012.
  10. Ahmad Rauf Subhani, Likun Xia, Aamir Saeed Malik, “EEG Signals to Measure Mental Stress”, 2nd International Conference on Behavioral, Cognitive and Psychological Sciences (BCPS 2011), Maldives, Nov. 25-27, 2011
  11. R. Subhani, L. Xia, and A. S. Malik, “Evaluation of mental stress using physiological signals”, National Postgraduate Conference, Malaysia, Sept 19, 2011.
  12. Wajid Mumtaz and Ahmad Rauf Subhani, “Adaptive Noise Cancellation: A Comparison of Adaptive Filtering Algorithms Aiming Fetal ECG Extraction”, 2nd World Congress on Computer Science and Information Engineering (CSIE), Changchun, China, Jun. 17-19, 2011.
  13. Saad Azhar Ali, Farhan Aziz, Ahsan Yasin and Ahmad Rauf Subhani, “Automatic Vehicle Identifier”, 14th WSEAS International Conference on Systems, Corfu Island, Greece Jul. 23-25, 2010.

Book Chapters

Likun Xia and Ahmad Rauf Subhani, “EEG and QEEG in Psychiatry”, EEG/ERP Analysis: Methods and Applications, CRC Press, US, ISBN# 978-1-4822-2469-6, June 2014.

Contact Person

Dr Ahmed Rauf Subhani

Head VML Research Group

Email: [email protected]

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