Assistant Professor, Department of Mechatronics Engineering, University of Engineering & Technology Peshawar, Pakistan

• Ph.D, Mechanical Engineering (Manufacturing and Mechatronics), The University of British Columbia, Canada
• M.A.Sc., Mechatronics Engineering, Asian Institute of Technology, Thailand
• B.Sc., Computer Systems Engineering, UET, Peshawar

Phone (Office): +92-9217070 Email: tufail@uetpeshawar.edu.pk

RESEARCH INTERESTS

• Robotics: dynamics and control with application in precision agriculture and robotic tele-rehabilitation
• Artificial intelligence and machine learning
• Computer vision
• Haptics
• Embedded systems

RESEARCH GRANTS

EDITORIAL

• Reviewer – MDPI Agriculture
• Reviewer – Journal of Sensors, Hindawi
• Reviewer – Journal of Intelligent & Robotic Systems
• Reviewer – Computers and Electronics in Agriculture

SELECTED PUBLICATIONS

1. M. Tufail, J. Iqbal, M. I. Tiwana, M. S. Alam, Z. A. Khan, and M. T. Khan, “Identification of Tobacco Crop Based on Machine Learning for a Precision Agricultural Sprayer,” IEEE Access, vol. 9, pp. 23814–23825, 2021.
2. S. Khan, M. Tufail, M. T. Khan, Z. A. Khan, J. Iqbal, and M. Alam, “A novel semi-supervised framework for UAV based crop/weed classification,” PLoS One, vol. 16, no. 5, p. e0251008, 2021.
3. S. Khan, M. Tufail, M. T. Khan, Z. A. Khan, and S. Anwar, “Deep learning-based identification system of weeds and crops in strawberry and pea fields for a precision agriculture sprayer,” Precision Agriculture, pp. 1–17, 2021.
4. S. Khan , M. Tufail, M. T. Khan, Z. A. Khan, J. Iqbal, and A. Wasim, “Real-time recognition of spraying area for UAV sprayers using a deep learning approach,” PLoS One, vol. 16, no. 4, p. e0249436, 2021.
5. S. Khan, M. Tufail, M. T. Khan, Z. A. Khan, J. Iqbal, and A. Wasim, “A Novel Framework for Multiple Ground Target Detection, Recognition and Inspection in Precision Agriculture Applications Using a UAV,” Unmanned Systems, pp. 1–12, 2021.
6. S. Khan, M. Tufail, M. T. Khan, Z. A. Khan, and S. Anwar, “Deep learning-based spraying area recognition system for Unmanned Aerial Vehicle based sprayers,” Turkish J. Electr. Eng. Comput. Sci., vol. 29, no. 2021, pp. 241–256, 2021, doi: 10.3906/elk-2004-4.
7. M. Alam, M. Aaqib, M. S. Alam, M. Tufail, and S. Anwar, “A Novel Machine Learning Technique for Classification of COVID-19 and Pneumonia,” Pakistan J. Eng. Technol., vol. 4, no. 01, pp. 90–96, 2021.
8. M. Alam, M. S. Alam, M. Roman, M. Tufail, M. U. Khan, and M. T. Khan, “Real-Time MachineLearning Based Crop/Weed Detection and Classification for Variable-Rate Spraying in Precision Agriculture,” 2020 7th Int. Conf. Electr. Electron. Eng. ICEEE 2020, no. April, pp. 273– 280, 2020, doi: 10.1109/ICEEE49618.2020.9102505.
9. H. U. Rehman, S. Anwar, and M. Tufail, “Machine Vision Based Plant Disease Classification Through Leaf Imagining,” Ing´enierie des Syst`emes d’Information, vol. 25, no. 4, pp. 437–444, 2020.
10. M. Tufail, S. Anwar, Z. A. Khan, and M. T. Khan, “Real-Time Impedance Control Based on Learned Inverse Dynamics,” Arab. J. Sci. Eng., pp. 1–13, 2020.
11. Y. Abd Djawad, H. Rehman, O. Jumadi, M. Tufail, S. Anwar, and N. Bourgougnon, “Discrimination of Nitrogen Concentration of Fertilized Corn with Extracted Algae and Polymer Based on Its Leaf Color Images,” Ing´enierie des Syst`emes d’Information, vol. 25, no. 3, pp. 303–309, 2020.
12. H. Zafar, Z. H. Abbas, G. Abbas, F. Muhammad, M. Tufail, and S. Kim, “An Effective Fairness Scheme for Named Data Networking,” Electronics, vol. 9, no. 5, p. 749, 2020.
13. S. N. K. Marwat, M. Shuaib, S. Ahmed, A. Hafeez, and M. Tufail, “Medium Access-Based Scheduling Scheme for Cyber Physical Systems in 5G Networks,” Electronics, vol. 9, no. 4, p. 639, 2020.
14. M. Fayyaz, M. Tufail, S. Anwar, Z. Ahmad, and S. Khan, “Optimization of Rao Blackwellized Particle Filter SLAM using Firefly algorithm,” Pakistan J. Eng. Technol., vol. 3, no. 03, pp. 46– 50, 2020.
15. S. G. Khan, M. Tufail, S. H. Shah, and I. Ullah, “Reinforcement learning based compliance control of a robotic walk assist device,” Advanced Robotics, vol. 33, no. 24, pp. 1281–1292, 2019, doi: 10.1080/01691864.2019.1690574.
16. S. H. Shah, M. Arsalan, S. G. Khan, M. Tufail, and M. S. Alam, “Design and Compliance Control of a Robotic Gripper for Orange Harvesting,” in 2019 22nd International Multitopic Conference (INMIC), 2019, pp. 1–5.
17. Z. A. Khan, M. T. Khan, I. ul Haq, J. Iqbal, and M. Tufail, “Human immune system inspired framework for disruption handling in manufacturing Process,” Int. J. Comput. Integr. Manuf., vol. 32, no. 11, pp. 1081–1097, 2019.
18. M. Tufail and C. W. de Silva, “Impedance control schemes for bilateral teleoperation,” in 2014 9th International Conference on Computer Science Education, 2014, pp. 44–49.
19. M. Tufail and C. W. de Silva, “Haptic Teleoperation using Impedance Control with Application in Homecare Robotics,” Control and Intelligent Systems, vol. 41, no. 3, 2013.