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Sanjay Sahay

Associate Professor · BITS, Pilani, K K Birla Goa Campus

https://researchid.co/s_k_sahay
@bits-pilani.ac.in
95Scopus Publications
2391Google Scholar Citations
24Google Scholar h-index
47Google Scholar i10-index

Research Interests

Information Security, Applied Artificial Intelligence, Malware Analysis, Blockchain Technology, Applied Cryptography and Gravitational Waves

Biography

Dr. Sanjay K. Sahay is an Associate Professor in the Department of Computer Science and Information Systems, BITS, Pilani, K.K. Birla Goa Campus. He is also a Visiting Associate of IUCAA, Pune. He has extensive research interests in Information Security, Applied Artificial Intelligence, Malware Analysis, Blockchain Technology, Applied Cryptography and Gravitational Waves. He has over 75 academic international publications, and under his supervision, four students received PhD degrees. He successfully completed a sponsored project. He has been a general chair of the 8th International Conference on Secure Knowledge Management in the Artificial Intelligence Era and member of the technical program committees, advisors and session chairs for about 15 international conferences. He also serves as an editor of SKM-2019 proceedings and its special issue published in Communications in Computer and Information Science (Springer) and Information Systems Frontiers journal respectively. He also publ

Recent Scopus Publications

  1. NS-CBM: Neuro-symbolic concept bottleneck for interpretable melanoma diagnosis
    Pattern Recognition Letters, 2026
  2. An Investigation of Deep Learning Techniques for the Robust Detection of Melanoma Cancer
    Communications in Computer and Information Science, 2026
  3. Explainable Skin Cancer Detection via Hybrid CNN and Adaptive Post-hoc Explanations
    Communications in Computer and Information Science, 2026
  4. PSKA-UAV: A Pre-shared Key-Based Authentication Protocol for Secure and Efficient Communication Between UAV and GCS
    Communications in Computer and Information Science, 2026
  5. A Novel Method for the Detection of Gravitational Wave Signal of BBH and BNS Using Convolutional Neural Networks
    Communications in Computer and Information Science, 2026

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