Mr. Chandan Sheikder | Bio-Robotics | Best Researcher Award
Mr. Chandan Sheikder | Beijing Institute of Technology | China
Mr. Chandan Sheikder is an emerging researcher in the interdisciplinary domains of bio-robotics, animal navigation, medical robotics, and calcium imaging. His current research explores bio-inspired and neuromorphic frameworks for autonomous robot navigation in complex and GPS-denied environments, focusing on sensor fusion, swarm intelligence, and adaptive control algorithms. He integrates mechanical engineering principles with artificial intelligence and neuroscience-inspired mechanisms to develop robust robotic systems capable of navigating dynamic and uncertain conditions. His research extends to assistive and medical robotics, particularly in designing intelligent systems for human–robot interaction and healthcare applications. He has also contributed to aerospace technology research, applying soft computing and physiological sensing techniques to enhance cognitive workload assessment and performance reliability. Mr. Sheikder’s innovative work has resulted in several peer-reviewed publications in high-impact journals such as Nature Reviews Bioengineering, Sensors, and Trends in Biotechnology. His research outputs demonstrate a strong emphasis on hybrid intelligence, ethical AI, and cross-domain applications of robotics in space exploration and medical systems. He holds one pending Chinese patent on bio-inspired fusion navigation frameworks and has received notable academic awards, including the IEEE Best Paper Award. According to Google Scholar, he has 6 citations, an h-index of 1, and an i10-index of 0, reflecting his growing scholarly influence. His Scopus and Google Scholar profiles collectively highlight his promising research trajectory in advancing next-generation robotic autonomy and bio-inspired engineering systems.
Publication Profile
Scopus | ORCID | Google Scholar
Featured Publications
Sheikder, C., Zhang, W., Chen, X., Li, F., He, X., Zuo, Z., Tan, X., & Liu, Y. (2025). Bio-inspired navigation systems for robots. Nature Reviews Bioengineering, 1–2.
Sheikder, C., Zhang, W., Chen, X., Li, F., Zuo, Z., & Tan, X. (2025). Marine-inspired multimodal sensor fusion and neuromorphic processing for autonomous navigation in unstructured subaquatic environments. Sensors, 25(216627).
Sheikder, C., Zhang, W., Chen, X., Li, F., He, X., Zuo, Z., Tan, X., & Liu, Y. (2025). A novel adaptive framework interconnects four pillars for tethered robots: Integrating fuzzy logic, genetic algorithms, and neural networks for robust dynamic environment navigation. Robotics and Autonomous Systems.
Sheikder, C., Haque, M. M. (2025). Towards the wearable cardiorespiratory sensors for aerospace applications. Journal of Aviation/Aerospace Education & Research, 34(2), 1–15.
Haque, M. M., Sheikder, C., & Djembong, R. (2023). Retroactive about robotics application with artificial intelligence toward the global pandemic scenario. European Journal of Electrical Engineering and Computer Science, 7(2), 34–43.