Qualifications
- PhD / DPhil (Northumbria University)
- FHEA (University of Hull)
Summary
I am actively looking for potential PhD students, please get in touch m.khalid@hull.ac.uk
Muhammad Khalid is currently working as a Lecturer(Assistant Professor) in the school of computer science, University of Hull. Before this, he worked Post-Doctoral Research Fellow at the University of Lincoln, Lincoln. He was responsible for assuring robot autonomy toward safety aspects in the project called MeSAPro. In this project, he ensured robotic safety through human-robot interaction for the robots used in the strawberry collection. Khalid has completed his PhD from Northumbria University in 2020 on Autonomous parking in intelligent smart cities, where he was awarded a fully funded PhD studentship in 2017 under research development framework.
Journal Article
An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †
Arshad, M., Liu, |., Khalid, |. M., Liu, Y., Wang, P., & Arshad, M. (online). An Adaptive Flooding Detection Framework with Blockchain Mitigation for Satellite Communications †. International Journal of Satellite Communications and Networking, https://doi.org/10.1002/sat.1560
mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology
Niaz, F., Zhang, J., Khalid, M., Younas, M., & Niaz, A. (online). mmFruit: A Contactless and Non-Destructive Approach for Fine-Grained Fruit Moisture Sensing Using Millimeter-Wave Technology. IEEE Transactions on Mobile Computing (TMC), https://doi.org/10.1109/TMC.2024.3520914
mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor
Niaz, F., Zhang, J., Zheng, Y., Khalid, M., & Niaz, A. (online). mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor. ACM Transactions on Sensor Networks, https://doi.org/10.1145/3694970
Presentation / Conference Contribution
Research interests
Autonomous/Electric vehicles
Autonomous Parking in Future Smart Cities
Applied AI in Autonomy
IoT in Future Smart Cities
AI-based Decision Making in IoT devices
Autonomous Transportation for Emergency Medical Services
Machine Learning in Wireless Networks
Machine Learning in Digital Health
Wireless communication
Robotics
Postgraduate supervision
PhD Students:
1. Ahmeed Farhan, Tumor detection using deep learning.
2. Haylay Hatton, Efficient 3D printing processes.
3. Franky George, GANs using DRL for improved autonomous transportation.
4. Waqas Ahmad RL for emergency autonomous transportation system.
5. Muneeb Anjum, Long term robot autonomy in adverse conditions.
6. Yingxiu Chang, Drone Navigation in GPS denied areas.