Sasanko Sekhar Gantayat

About

Dr. Sasanko Sekhar Gantayat is working as an Associate Professor in the School of Computer Science and AI at SR University, Warangal, Telangana, India. He graduated in Electronics & Communication Engineering from the Institute of Engineers (India), Kolkata, India. He secured a Master of Science in Mathematics from Utkal University, Bhubaneswar (Odisha), India. He has also completed PGDCSA from Berhampur University, Berhampur (Odisha), and M.Sc. in Computer Science from Annamalai University, Annamalai, Tamil Nadu. He has completed a Ph.D. in Computer Science from Berhampur University, Berhampur (Odisha), India. He has been in the teaching profession for more than 32 years. He has presented a number of papers in national and international journals and conferences. He is a member of international professional associations like IEEE, ACM, IRSS, CSI, IMS, IACSIT, ISTE, IAENG, IE(I), IMS, SSI, ISIAM, WSEAS, IAMT, AIRCC, IOSRD, IFERP and is a reviewer of various international journals and conferences. To his credit, he is an author of 3 books and two book chapters. His current research interests include Soft Computing Techniques, Machine Learning, Data Science, Rough Sets Theory and Knowledge Representation, List Theory, Fuzzy Systems, and Social Network Analysis.

Employment

• SR University Associate Professor
  2024 - Present
• K L University Associate Professor
  2023 - 2024
• Gandhi Institute for Technology Professor
  2022 - 2023
• GMR Institute of Technology Associate Professor
  2012 - 2022
• Gandhi Institute of Engineering and Technology Professor
  2004 - 2011
• Hi-Tech Institute of Information Technology Vice Principal
  2001 - 2004

Education

• Annamalai University M.Sc. (Computer Science)
  2003 - 2005
• Berhampur University Ph.D.
  2001 - 2008
• Berhampur University PGDCSA
  1990 - 1991
• Utkal University M.Sc.(Maths)
  1986 - 1988

Projects & Funding

Projects & funding information is unavailable.

Publications (33)

• An Explainable Hybrid Transformer-XGBoost Framework for Cyber Threat Detection
  Proceedings of 7th International Conference on Smart Systems and Inventive Technology Icssit 2026 2026 DOI: 10.1109/ICSSIT69151.2026.11656497
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• Comparative Analysis of XAI-Enabled ML and NLP Approaches for Intelligent Cyber Threat Detection and Response
  Lecture Notes in Networks and Systems 2026 DOI: 10.1007/978-3-032-18349-1_39
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• Enhancing Crisis Response and Misinformation Detection Using Large Language Models and Hybrid Approaches
  Lecture Notes in Networks and Systems 2026 DOI: 10.1007/978-981-95-5082-1_29
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• Glomorph-TransLight: An Interpretable Hybrid Framework for Glomeruli Segmentation and Classification in Renal Histopathology
  International Conference on Intelligent and Sustainable AI Systems Icosaas 2026 Conference Proceedings 2026 DOI: 10.1109/ICOSAAS68663.2026.11648488
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• Leveraging Social Networks for Cyber Threat Intelligence: Attack Trends, Cybersecurity Threat Detection Challenges, AI-Based Solutions, and Potential Opportunities in X
  AI Driven Threat Intelligence Frameworks Revolutionizing Enterprise Cybersecurity 2026 DOI: 10.2174/9798898813840126010008
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• Two-Layer Input Filtering Framework for Large Language Model Security
  2026 IEEE International Conference for Convergence in Computing Technology I3ctcon 2026 2026 DOI: 10.1109/I3CTCON68242.2026.11507202
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• XAI-HDRL: An Intelligent Framework for Cyber Threat Prediction and Automated Security Response
  Proceedings of 7th International Conference on Smart Systems and Inventive Technology Icssit 2026 2026 DOI: 10.1109/ICSSIT69151.2026.11656470
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• Intelligent 6G-Enabled Cloud-Edge Framework for Smart Agriculture: Leveraging Beamforming, Massive MIMO, and Digital Market Connectivity for Empowering Farmers
  SSRN Electronic Journal 2026 DOI: 10.2139/ssrn.6399198
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• Digital Market: AI-Powered Cloud Platforms for Transparent and Efficient Agricultural Markets
  Proceedings of International Conference on Sustainable Communication Networks and Application Icscn 2025 2025 DOI: 10.1109/ICSCN67106.2025.11308356
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• Influenza Diagnosis Deep Learning: Machine Learning Approach for Pharyngeal Image Infection
  Eai Endorsed Transactions on Pervasive Health and Technology 2024 DOI: 10.4108/eetpht.10.5613
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