Microwave Sensing, Signals and Systems
Department of Microelectronics

MSc M Hassan

PhD student
Microwave Sensing, Signals and Systems (MS3), Department of Microelectronics

Expertise: Machine Learning algorithms for radar object detection and tracking applications in advanced driver assistance systems.

Themes: Distributed sensor systems, Radar for Remote Sensing and Targets Characterization, Radar technology

Biography

Mujtaba received his bachelor’s degree in Electrical Engineering at National University of Science & Technology, Pakistan in 2016. Afterwards, he started his master’s degree in Communications Engineering at Technical University Munich, Germany. He completed his master thesis with NXP Semi-Conductors, Germany where he designed an optimized convolutional neural network for dense optical flow estimation. Afterwards, he joined NXP as a Systems & Application Engineer in 2019. During this period, he had investigated machine learning algorithms involved during different stages of ADAS as well as their requirements for implementation on hardware accelerators. Currently, he is focusing on neural networks together with their requirements relevant to radar perception in ADAS. In December 2021, he joined Microwave Sensing, Signals and Systems Group as an external PhD candidate

AI for SLAM & Tracking techniques in automotive radar

  1. Classification of Tracked Objects Using Multiple Frame Processing for Automotive Radar
    Hassan, Mujtaba; Fioranelli, Francesco; Yarovoy, Alexander; Chen, Lihui; Ravindran, Satish; Wu, Ryan;
    In 2024 21st European Radar Conference (EuRAD),
    pp. 35-38, 2024. DOI: 10.23919/EuRAD61604.2024.10734928

  2. Radar Multi Object Tracking using DNN Features
    Hassan, Mujtaba; Fioranelli, Francesco; Yarovoy, Alexander; Ravindran, Satish;
    In 2023 IEEE International Radar Conference (RADAR),
    pp. 1-6, 2023. DOI: 10.1109/RADAR54928.2023.10371032

BibTeX support

Last updated: 29 Oct 2024

Mujtaba Hassan