Amirul Islam

American International University-Bangladesh, Electrical and Electronic Engineering, Faculty Member

Kookmin University, Electronic Engineering, Graduate Student

University of Essex, School of Computer Science and Electronic Engineering, Graduate Student

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Amirul Islam currently serves as an Assistant Professor in the Department of Electrical and Electronic Engineering at the American International University – Bangladesh. Prior to this, he held the position of a Post-Doctoral Researcher at the Visual Artificial Intelligence Laboratory, Oxford Brookes University. Notably, he led the MAESTRO Jr. project during his tenure there. In 2022, Amirul Islam successfully obtained his PhD from the University of Essex, United Kingdom, specializing in Computing and Electronic Systems.
His academic journey also includes achieving a Master of Science degree from Kookmin University, South Korea in August 2017. During his time there, he was actively engaged as a graduate research student from September 2015 to August 2017. Amirul Islam’s contributions to the field are evident through his substantial presence, with more than 1100 citations on Google Scholar.
His research interests encompass a wide range of areas, including Machine Learning for Communication, Deep Reinforcement Learning, Ultra-Reliable and Low-Latency Communication (uRLLC), Optical Wireless Communications (OWC), Automotive Vehicular Communications, Medical Robotics, Optimization Strategies, and 5G Communication. Amirul Islam is actively seeking opportunities for collaboration within these research domains.

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Interference Mitigation Technique for Time-of-Flight (ToF) Camera

by Mohammad Arif Hossain and Amirul Islam

— Time-of-Flight (ToF) camera has become an attractive source of applications in location-based s... more — Time-of-Flight (ToF) camera has become an attractive source of applications in location-based services, autonomous navigation, object localization for robotic manipulation, ego-motion estimation, etc. Besides, these services demand centimeter level accuracy to provide the required services. Though ToF cameras can provide high accuracy in location-based services with high frame rates (approx. 30 fps), they are facing some problems like multipath interference (MPI), internal scattering, motion blur, etc. The interferences inherent to ToF camera can influence the measurements by several centimeters. In this paper, we formulate a model to mitigate MPI and light scattering problems through a combination of scale-invariant feature transform (SIFT) and iterative closest point (ICP). We use SIFT algorithm for image features extraction and ICP for error correction during estimation. Finally, we present simulation results to prove the scalability and flexibility of our proposed algorithm for both MPI and light scattering mitigation.

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