Biplab Sikdar

Papers

Total Citations

286

H-Index

About

Biplab Sikdar is a leading researcher at the intersection of artificial intelligence, cybersecurity, and intelligent infrastructure systems. His work focuses on making AI systems both trustworthy and explainable, a critical challenge as these technologies become increasingly embedded in high-stakes applications. His highly cited 2023 review, "A Review of Trustworthy and Explainable Artificial Intelligence (XAI)," has already garnered over 275 citations, establishing a foundational reference for researchers working to address bias, security vulnerabilities, and transparency in AI-driven systems. Beyond theoretical frameworks, Sikdar applies his expertise to practical engineering challenges. He has developed a computer vision and IoT-enabled robotic platform for automated crack detection in roads and bridges, addressing critical needs in structural health monitoring while reducing reliance on costly manual inspections. Looking toward the future of autonomous systems, he has also proposed privacy-preserving multi-factor authentication schemes for robotic delivery systems, tackling the security and privacy challenges of last-mile logistics. Sikdar's work demonstrates a rare ability to bridge high-level AI ethics with concrete, deployable solutions for infrastructure and automation, making him a significant voice in shaping responsible and practical AI applications.