Dr. Jamshed Iqbal

Dr Jamshed Iqbal

Senior Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • School of Computer Science

Qualifications

  • MSc (University of Engineering and Technology, Taxila)
  • MSc (Aalto University School of Science and Technology)
  • MSc (Lulea University of Technology)
  • PhD / DPhil (University of Genoa )

Summary

Dr. Iqbal is an academically sophisticated professional with pioneering career reflecting strong technical expertise flavored with intensive professional teaching and industrial research experience of over two decades. Currently, he is looking after BEng/MEng Robotics and AI programme.

His research interests include Robotics, Mechatronics and Control Systems. Summary of his profile is mentioned below:

Keynote Speeches: ISMSIT 2023, ICCEES 2021, ICoMST 2021, HORA 2019, WFAR 2016

Peer-reviewed Publications: 2 Books + 4 Book Chapters + 96 Journal + 47 Conference papers (mostly IEEE)

No. of Citations: ~4500 (Google Scholar)

H-Index: 41

Funded projects:

(1) “Unleashing the potential of Unmanned Aerial System (UAS) in oil and gas sector for infrastructure monitoring and fault analysis”, DSR grant, UJ, KSA (Co-PI, £17K, Project completed)

(2) “RoboPLEF ─ Robotics-inspired Practical LEarning Framework”, Ferens Education Trust (FET), UK (Role: PI, Amount: £5K, Status: Project completed)

(3) “Prospective opportunities and challenges of robotics in KSA – An investigational study to achieve strategic objectives of Vision 2030”, Deanship of Scientific Research (DSR) grant, University of Jeddah (UJ), KSA (PI, £2K, Project completed)

(4) “First Aid - Unmanned Aircraft System (FA-UAS)”, International Collaboration for Logistics Program, DSR grant, UJ, KSA (International Consultant, £18K, Project in progress)

Dr. Iqbal is a Senior Fellow of Advanced HE and a Senior member of IEEE. He is a Guest Editor of four Special issues in 'Electronics', 'Drones', 'Sensors' and 'Frontiers in Robotics and AI'. He is an Associate Editor or Academic Editor of 13 reputed journals. Moreover, he is a TPC member of various reputed international conferences.

MODULE LEADER:

- Mechatronic Systems (500680)

- Mechatronics Robotics Sensors and Simulation (500682)

- Stress Analysis and Dynamics of Mechanical Systems (500667)

- Robotics Systems and Simulation (551530)

- Embedded Systems Development (600085)

- Machine Vision and Sensor Fusion ( 601097)

CO-LECTURER:

- Robotics and Automation (601089)

- Autonomous Robots (701028)

- Honours Stage Project (600091)

Recent outputs

View more outputs

Journal Article

Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters

Saleem, O., Rasheed Ahmad, K., & Iqbal, J. (2024). Fuzzy-Augmented Model Reference Adaptive PID Control Law Design for Robust Voltage Regulation in DC–DC Buck Converters. Mathematics, 12(12), Article 1893. https://doi.org/10.3390/math12121893

Phase-Based Adaptive Fractional LQR for Inverted-Pendulum-Type Robots: Formulation and Verification

Saleem, O., & Iqbal, J. (in press). Phase-Based Adaptive Fractional LQR for Inverted-Pendulum-Type Robots: Formulation and Verification. IEEE Access, https://doi.org/10.1109/ACCESS.2024.3415494

Improving stability and adaptability of automotive electric steering systems based on a novel optimal integrated algorithm

Nguyen, T. A., & Iqbal, J. (2024). Improving stability and adaptability of automotive electric steering systems based on a novel optimal integrated algorithm. Engineering Computations, 41(4), 991-1034. https://doi.org/10.1108/EC-10-2023-0675

Fuzzy Fault-tolerant Controller With Guaranteed Performance for MIMO Systems Under Uncertain Initial State

Yin, C. W., Riaz, S., Uppal, A. A., & Iqbal, J. (2024). Fuzzy Fault-tolerant Controller With Guaranteed Performance for MIMO Systems Under Uncertain Initial State. International journal of control, automation and systems, 22(6), 2038-2054. https://doi.org/10.1007/s12555-023-0327-5

Minimum Distance and Minimum Time Optimal Path Planning With Bioinspired Machine Learning Algorithms for Faulty Unmanned Air Vehicles

Tutsoy, O., Asadi, D., Ahmadi, K., Nabavi-Chashmi, S. Y., & Iqbal, J. (2024). Minimum Distance and Minimum Time Optimal Path Planning With Bioinspired Machine Learning Algorithms for Faulty Unmanned Air Vehicles. IEEE Transactions on Intelligent Transportation Systems, https://doi.org/10.1109/TITS.2024.3367769

Research interests

Robotics, Mechatronics, Control Systems, Technology in Education, Learning and Teaching, Pedagogy

Lead investigator

Project

Funder

Grant

Started

Status

Project

Exploring the Best Practices in AI Education: Harnessing the Potential of Robotics via the CDIO Framework in Higher Education

Funder

British Council

Grant

£39,999.00

Started

1 April 2024

Status

Ongoing

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