Dr Mahdi Rezaei

Dr Mahdi Rezaei

Profile

Biography

I am an Assistant Professor in Computer Science and University Academic Fellow (UAF) at the Institute for Transport Studies. I have 15 years of experience in academia and industry and my primary area of expertise and research interests are Computer Vision, Machine Learning, and Deep Learning. My research mainly focuses on real-world applications in Autonomous Driving and Smart cars, Driver Behaviour Monitoring, Road/Traffic perception, Object Detection, Tracking, Human Factors, and Safety. I have contributed as PI and Co-I to multiple national and international research funding/projects as well as 55 publications including top-tier journal articles, conference papers (with 3 best paper awards), and a monograph book with Springer.

Education

PhD in Computer Science 2014, with the Best PhD Thesis Award, the University of Auckland, New Zealand (QS rank:50)

Employment History:

  • 2020 - Present, Assistant Professor (University Academic Fellow), Uni of Leeds, UK
  • 2017 - 2020, Senior Researcher, Auckland University of Technology, New Zealand
  • 2015 - 2020, Lecturer in the Department of Computer Engineering, Qazvin University, IR
  • 2010 - 2017, Honorary Academic Staff, University of Auckland, New Zealand
  • 2006 - 2010, Lecturer in the Department of Computer Engineering, Qazvin University, IR

Selected videos & research outputs:

3D Vehicle Detection / Pedestrian Detection, and Speed Estimation Using a Single Camera:

<iframe width="560" height="315" src="https://www.youtube.com/embed/FdiQ_EGbZe0" frameborder="-1" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

Traffic Monitoring including 3D Vehicles & Pedestrian Detection, Speed Detection & Tracking and activity heatmap generation.

Driver Behaviour Monitoring (Distraction, Drowsiness, Phoning / Texting, Yawning, Head Nodding,...)

<iframe width="560" height="315" src="https://www.youtube.com/embed/K_ZIhwqScpk" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

Driver Behaviour analysis using a single RGB camera

Stop/Go Decision Making at Roundabouts for Autonomous Vehicles

<iframe width="560" height="315" src="https://www.youtube.com/embed/FizrMquM0VU" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

The research aims for a timely, fast and safe merging manoeuvre by AVs at the roundabout where the human may act unsafely or with delays due to uncertainty, fatigue, or distraction. The solution can lead to reducing traffic jams behind roundabouts, saving times/lives, less fuel consumption, and less CO pollution!

Our contribution towards public health during the COVID-19 Pandemic:

<iframe width="560" height="315" src="https://www.youtube.com/embed/FwCP2ySDshE" frameborder="-1" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

Rezaei, M.; Azarmi, M. (2020). DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic. Applied Sciences. 2020, 10(21), 7514.

 

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 prospective PhD students, Postdocs & Researchers with relevant background are welcome to apply here and join our multideciplinary team at Institute for Transport Studies (ITS)*.

* Funded positions will be advertised publically. 

 

Honours, Awards, Grants:

  • EPSRC Impact Acceleration Account (IAA) fund 2022-2023 (PI, £287,295)
  • Hi-Drive – EU funded 2021-2025 (Co-Investigator, € 1,175,961.25) 
  • L3Pilot – EU Horizon 2020 Driving automation project 2017-2021 (Co-I, € 877,500)
  • Research England - World Class Laboratories Fund 2020-2021. (Co-I, £54,852)
  • Spark $100,000 Qualifiers Award, 2011. Also, the winner of the “Spark Ideas Challenge Award” for the project IntelliEye (one of the top 3 projects among all applications from all disciplines)
  • Marsden Grant, 2012. Faculty grant for going to the final round of Marsden competition- the most challenging research grant in New Zealand, by the Royal Society of New Zealand.
  • 3 x Best Paper Awards: ( IEEE Conference SensorCOMM (2007) | CVPR paper, University of Auckland (2014) | Computer Analysis of Images and Patterns (2019)
  • 2 x Akira Nakamura Awards and Grant: 2011 and 2014. provided by Akira Nakamura, professor emeritus of Hiroshima University. (PI, $60,000)
  • Best PhD Thesis Award, 2014. the University of Auckland
  • 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

My current Postdoc, PhD, and MSc Students:

 

Professional Engagements:

Editor and Organiser: 

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 monograph book published by Springer International Publishing:

Computer Vision for Driver Assistance 

<iframe width="560" height="315" src="https://www.youtube.com/embed/2H9JH9ZBQMI?autoplay=0" frameborder="1" allow="accelerometer; autoplay; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

Rezaei, M., Klette, R. (2017). Computer Vision for Driver Assistance: Simultaneous Traffic and Driver Monitoring. Springer. CIVI Book Series, pp. 1-224, Volume 45, 2017, ISBN : 978-3-319-50549-7

<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>

Professional memberships

  • IEEE
  • Computer Vision Foundation
  • CerV Research Group

Student education

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

Human Drive

Human Drive- Autonomous Vehicle

 

Driving Simulaor

Our Sophisticated Driving Simulator

 

University of Leeds

Modern Infrastructures

 

Academic & Social Profiles (click on icons below):

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Research groups and institutes

  • Human Factors and Safety

Current postgraduate researchers

<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>