Mohammad Shafiul Alam

Ahsanullah University of Science and Technology

Papers

Total Citations

H-Index

About

Mohammad Shafiul Alam is a robotics researcher specializing in autonomous navigation, simultaneous localization and mapping (SLAM), and computer vision, with a particular focus on enabling mobile robots to operate reliably under challenging environmental conditions. His most cited work, "Convolutional Auto-Encoder and Independent Component Analysis Based Automatic Place Recognition for Moving Robot in Invariant Season Condition" (2022, 17 citations), addresses a critical bottleneck in SLAM: maintaining map consistency when weather or seasonal changes degrade sensor data. By integrating convolutional auto-encoders with independent component analysis, Alam developed a robust place recognition system that allows robots to recognize previously mapped locations even under invariant season conditions—a key step toward truly all-weather autonomous navigation. This contribution is especially valuable for field robotics applications in agriculture, search-and-rescue, and environmental monitoring. While still early in his career, Alam’s work demonstrates a strong commitment to solving real-world perception challenges, and his citation record reflects growing interest from the SLAM and mobile robotics communities. His research promises to make autonomous systems more resilient in unstructured, outdoor environments.