Dr Mahdi Rezaei

Profile

I am a full-time University Academic Fellow (UAF) and Assistant Professor at the University of Leeds, Institute for Transport Studies.

Having more than 14 years of research and lecturing experience in the field of Computer Vision, Autonomous Vehicles and Self-driving Cars, I received my PhD degree in Computer Science in 2014 from the University of Auckland (QS world rank: 50), New Zealand, with the Best PhD Thesis Award.

Since 2006, I have participated in various academic roles and industrial activities such as acting as Head of Department in Computer Science, R&D Manager, Lecturer, Supervisor of PhD and MSc students, Honorary Academic Staff, and Senior Researcher at the University of Auckland, CeRV Research Centre, Qazvin University, Auckland University of Technology, and currently at the University of Leeds, UK.

My primary area of expertise and research interests are in Computer Vision and Artificial Intelligence, and in particular, I am interested in applied Machine Learning in the interdisciplinary field of Autonomous Vehicles (Self-driving cars), Driver Behaviour Monitoring, Pedestrian Detection and Tracking, Human Factors, and Traffic Scene Analysis. 

“ Talented and motivated prospective PhD candidates, Postdocs, and Researchers are welcome to apply and join our dynamic multidisciplinary team at the Institute for Transport Studies (ITS). ” 

Recently graduated / current PhD and MSc Students:

• Sabeeha Mehtab – 2019
• Navid Raeesi – 2019
• Mohsen Azarmi – 2019
• Mahsa Shahidi – 2018 
• Dr Noor Saleem – 2019

Employment History:

• University Academic Fellow (Assistant Professor in US discipline), University of Leeds, 2020-Present
• Research Fellow and Honorary Academic, Auckland University of Technology, New Zealand, 2017-2020
• TA, Researcher, and Honorary Academic Staf, University of Auckland, New Zealand, 2010-2017
• Lecturer in Department of Computer Engineering, QIAU, Iran, 2006-2010

Honours, Award, Grants:

• Best Paper Award, 2019. NH Saleem, HJ Chien, M Rezaei, R Klette. “Improved Stixel Estimation Based on Transitivity Analysis in Disparity Space”, Intl. Conference on Computer Analysis of Images and Patterns (CAIP).
• Honorary Academic, 2017-2020. Dept. of Computer Science, Auckland University of Technology. 
• Honorary Academic, 2014-2016. Dept. of Computer Science, the University of Auckland, Researcher at ‘.enpeda..’ research group.
• Best PhD Thesis Award, 2014. the University of Auckland
• Akira Nakamura Award and Grant, 2011 and 2014. provided by Akira Nakamura, professor emeritus of Hiroshima University
• Best Paper Award and Certificate of Achievement, 2014. M Rezaei, R Klette, “Look at the Driver, Look at the Road: No Distraction! No Accident!”, IEEE Conference on Computer Vision and Pattern Recognition (CVPR). CVPR holds the world Rank #1 conference in the field of computer vision. CVPR is also among the top 10 venues in the world from all fields and disciplines.
• Marsden Grant, 2012. Faculty grant for going to the final round of Marsden competition- the most challenging research grant in New Zealand, by Royal Society of New Zealand.
• Spark $100,000 Qualifiers Award, 2011. Also, the winner of “Spark Ideas Challenge Award” for the project IntelliEye as one of the top 3 top research ideas among all applications received from all disciplines, students and staff.

Other Professional Engagements:

Reviewer: 

• IEEE Transactions on Intelligent Transportation Systems
• IEEE Transactions on Vehicular Technologies
• International Journal of Applied Science
• International Journal of Computer and Robotics
• International Journal of Sensors
• International Conference on Pattern Recognition
• Asian Conference on Pattern Recognition
• International Conference of Computer Analysis of Images and Patterns
• Pacific-Rim Symposium on Image and Video Technology 

Panel Member / Technical Program Committee (TPC): 

• International Conference of Computer Analysis of Images and Patterns
• Pacific-Rim Symposium on Image and Video Technology
• RoboCup Asia-Pacific Symposium
• IEEE

Latest Publications:

https://scholar.google.co.uk/citations?user=9Z7J8ecAAAAJ&hl=en

Responsibilities

• Research, lecturing, and supervsion of postdocs, PhDs, and postgrad students

Research interests

• Computer Vision
• Artificial Intelligence
• Machine Learning
• Autonomous Vehicles | Driver Behaviour Monitoring | Pedestrian Detection and Tracking
• Traffic Science Segmentation and Understanding
• Human Factors

A short video spotlight on my book published by Springer International Publishing:

Computer Vision for Driver Assistance 

<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://environment.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>

Qualifications

• PhD in Computer Science - Computer Vision
• MSc in Computer Engineering - Artificial Intelligence & Robotics
• BSc in Computer Engineering- Computer Hardware

Professional memberships

• IEEE
• Computer Vision Foundation
• CerV Research Group

Student education

Supervision of PhD and PGR students

My current students (local and external):

• Sabeeha Mehtab
• Navid Raeesi
• Mohsen Azarmi
• Mahsa Shahidi

Join our team at the Institute for Transport Studies, Ranked 12th in the world, as one of the most advanced research centres in the interdisciplinary field of Autonomous Vehicles, Self-driving Cars, Driver Behaviour Monitoring, and Human factors.

 Talented and motivated prospective PhD candidates, Postdocs, and Researchers are welcome to apply and join our multideciplinary team at the Institute for Transport Studies (ITS). 

For your questions and any further information feel free to email me via m.rezaei@leeds.ac.uk 

 

 

 

Academic & Social Profiles (click on icons below):

   

 

Research groups and institutes

• Human Factors and Safety

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>