Mahdi Rezaei – Leading Researcher in Autonomous Vehicles

Assoc Prof Dr Mahdi Rezaei, a distinguished academic and researcher in the field of renewable energy, Academician/Research Scholar University of Leeds, United Kingdom. His academic journey has been marked by a profound dedication to Autonomous Vehicles into Social Media and Digital Marketing applications.

📚 Education:

He holds a PhD in Computer Science with a focus on AI and Computer Vision from The University of Auckland, New Zealand, where he conducted groundbreaking research on “Computer Vision for Road Safety.” His exceptional contributions earned him the prestigious Best PhD Thesis Award in 2014. Prior to his doctoral studies, he earned an MSc in Computer Science, specializing in Artificial Intelligence and Robotics, from Tehran Science & Technology University, Iran. The culmination of his master’s program was marked by the successful completion of a dissertation titled “Design and Implementation of a 3P Robot for the Automotive Industry,” for which he graduated with Distinction star.

🌐 Profile Links:

• Google Scholar
• Scopus
• ORCID
• LinkedIn
• ResearchGate

📚 Employment History : 

He has an extensive and diverse employment history in academia. Currently, he serves as a University Academic Fellow at the Institute for Transport Studies in Leeds, UK, a position he has held since 2020. Prior to this, he contributed his expertise as Honorary Academic Staff in the Department of Computer Science at Auckland University of Technology in New Zealand from 2017 to 2020. Earlier in his career, he held the role of Lecturer at Qazvin University in Iran, specifically in the Department of Computer Engineering, from 2014 to 2017.

🤝 Membership of Professional Bodies:

He actively engages in professional bodies, showcasing his commitment to advancing knowledge and contributing to the academic community. Currently, he holds the position of Executive Member for the United Kingdom Universities Transport Study Group (UTSG) since 2022. In Leeds, UK, he serves as a Member of the Advisory Group for the LIDA Development Programme and acts as the Research Group Leader for Visual Computing and Autonomous Vehicles (VCAV), both roles held from 2022 onwards. Additionally, he has been dedicated to editorial and review activities on an international scale, serving as an Expert Reviewer and Editor since 2014. His involvement in these roles reflects his dedication to the growth and development of his field.

🌐 Research and Mentoring :

In his role as a mentor and researcher, he has demonstrated a strong commitment to fostering academic growth and development. Currently, he is actively engaged in staff mentorship, overseeing the progress and research activities of various scholars. This includes a 3-year Post Doctoral Research Fellow, Dr Tranveer Hussain, from October 2022 to September 2025, a 1-year Post Doctoral Research Fellow, Vishnu Radhakrishnan, from January 2023 to January 2024, and a 7-month PhD Research Assistant, Mojtaba Lashgari, from June 2022 to January 2023, all based at ITS, Leeds. Furthermore, he serves as the Lead Supervisor for Mr Yiming Hou, in his 3rd year, and Mr Mohsen Azarmi, in his 1st year, both at ITS, Leeds, starting from 2020 and 2022, respectively. Additionally, he contributed as the 2nd Supervisor to the successful graduation of Dr Noor Saleem at Auckland University of Technology, New Zealand, from 2016 to 2020. His dedication to guiding and supervising researchers reflects his commitment to shaping the future of academia.

📖 Publications :

1. M. Bonyani et al. and M. Rezaei. “DIPNet: Driver Intention Prediction for a Safe Takeover Transition in Autonomous Vehicles”. In: IET Intelligent Transport Systems – final round of review (2023).
2. Khan Muhammad, Tanveer Hussain, and Mahdi Rezaei. “Vision-Based Semantic Segmentation in Scene Understanding for Autonomous Driving: Recent Achievements, Challenges, and Outlooks”. In: IEEE Transactions on Intelligent Transportation Systems (2022).
3. Yiming Hou, Mahdi Rezaei, and Richard Romano. “Multi-level and multi-modal feature
   fusion for accurate 3D object detection in Connected and Automated Vehicles”. In: arXiv
   preprint arXiv:2212.07560 (2022).
4. Amir Sharifi, Ahmadreza Zibaei, and Mahdi Rezaei. “A deep learning based hazardous
   materials (HAZMAT) sign detection robot with restricted computational resources”. In:
   Machine Learning with Applications 6 (2021).
5. Mahdi Rezaei, Mohsen Azarmi, and Farzam Mohammad Pour Mir. “Traffic-Net: 3D Traffic
   Monitoring Using a Single Camera”. In: arXiv preprint arXiv:2109.09165 (2021).
6. Fatemeh Serpush and Mahdi Rezaei. “Complex human action recognition using a hierarchical
   feature reduction and deep learning-based method”. In: SN Computer Science 2.2 (2021).
7. Mahdi Rezaei and Mahsa Shahidi. “Zero-shot learning and its applications from autonomous
   vehicles to COVID-19 diagnosis: A review”. In: Intelligence-based medicine 3 (2020).

📚BOOK & BOOK-CHAPTERS:

1.  Mahdi Rezaei and Reinhard Klette. “Book: Computer vision for driver assistance”. In: Springer
   International Publishing 45 (2017), pp. i–224. doi: 10.1007/978-3-319-50551-0.
2. Mahdi Rezaei and Reinhard Klette. “Chapter 1: Vision-Based Driver-Assistance Systems”. In:
   Springer (2017), pp. 1–18. doi: 10.1007/978-3-319-50551-0_1.
3. Mahdi Rezaei and Reinhard Klette. “Chapter 2: Driver-Environment Understanding”. In:
   Springer (2017), pp. 19–37. doi: 10.1007/978-3-319-50551-0_2.
4. Mahdi Rezaei and Reinhard Klette. “Chapter 3: Computer Vision Basics”. In: Springer (2017),
   pp. 37–49. doi: 10.1007/978-3-319-50551-0_3.
5. Mahdi Rezaei and Reinhard Klette. “Chapter 4: Object Detection, Classification, and Tracking”. In: Springer (2017), pp. 51–94. doi: 10.1007/978-3-319-50551-0_4.
6. Mahdi Rezaei and Reinhard Klette. “Chapter 5: Driver Drowsiness Detection”. In: Springer
   (2017), pp. 95–126. doi: 10.1007/978-3-319-50551-0_5.
7. Mahdi Rezaei and Reinhard Klette. “Chapter 6: Driver Inattention Detection”. In: Springer
   (2017), pp. 127–145. doi: 10.1007/978-3-319-50551-0_6.
8. Mahdi Rezaei and Reinhard Klette. “Chapter 7: Vehicle Detection and Distance Estimation”.
   In: Springer (2017), pp. 147–188. doi: 10.1007/978-3-319-50551-0_7.
9. Mahdi Rezaei and Reinhard Klette. “Chapter 8: Fuzzy Fusion for Collision Avoidance”. In:
   Springer (2017), pp. 189–205. doi: 10.1007/978-3-319-50551-0_8.
10. Mahdi Rezaei and Reza Sabzevari. “Multisensor data fusion strategies for advanced driver
    assistance systems”. In: Sensor and Data Fusion (2009), pp. 141–166. doi: 10.5772/6575.