Md. Delowar Hossain
University of Toyama, University of Calgary, Hosei University, Kyung Hee University
Papers
11
Total Citations
150
H-Index
8
About
Md. Delowar Hossain is a leading researcher at the intersection of robotics, deep learning, and evolutionary optimization. His work focuses on enabling autonomous robot manipulation through advanced object recognition and grasping systems. Hossain pioneered the use of genetic algorithms and multiobjective evolutionary algorithms to automatically tune deep learning parameters, significantly improving robot performance in pick-and-place tasks. His highly cited 2017 paper on dynamic object manipulation using deep learning and user-friendly interfaces has garnered 33 citations, establishing foundational methods for human-robot collaboration. With over 150 total citations across his publications, Hossain has demonstrated remarkable versatility, extending his expertise to healthcare applications—his 2023 work on using machine learning to assess upper limb proprioceptive impairments after stroke (22 citations) shows the translational impact of his research. He has also contributed to real-time moving object detection for Industry 5.0 and intelligent wheelchair navigation using multi-sensor fusion. Hossain’s ability to bridge theoretical optimization with practical robotic systems makes his work essential reading for researchers in autonomous robotics and applied AI.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8
- 9Multiobjective evolution for deep learning and its robotic applications5 citations · 2017
- 10A Faster R-CNN Approach for Partially Occluded Robot Object Recognition3 citations · 2019