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Academic Experts
Santosh Kumar Ray

Biography

Mr. Santosh Kumar Ray received his B.Tech. degree in Information Technology from Uttar Pradesh Technical University, Lucknow, India, in 2008, and his M. Tech. degree in Computer Science and Engineering from Jamia Hamdard University, New Delhi, India, in 2016. He is a full-time Ph.D. Research Scholar in the Department of Information Technology at Delhi Technological University (DTU), India, and has submitted his doctoral thesis for evaluation. He has substantial academic experience and is presently working as an Assistant Professor in the Department of Computer Science and Engineering / Information Technology at Jaypee Institute of Information Technology, Noida. His research interests include Online Machine Learning, Streaming Data, Anomaly Detection, Data Mining, and Data Science.

Research Highlights

He is engaged in research exploring intelligent systems capable of adapting to evolving patterns in dynamic environments. The work emphasizes scalable methodologies for learning from continuous data and assessing performance in real-time contexts. Interests lie in the intersection of adaptability, automation, and data-driven decision-making. Several research outcomes have been published in reputed journals and international conferences related to this domain.

Areas of Interest
  • Online Machine Learning
  • Data Mining
  • Streaming Data
  • Anomaly Detection
  • Data Science
Publications
  • Ray, Santosh Kumar, and Seba Susan. "Real-time Air Pollution Monitoring in Delhi Using Online Anomaly Detection Algorithms for Streaming Data." National Academy Science Letters (2025): 1-3. (SCIE)
  • Ray, Santosh Kumar, and Seba Susan. "Performance evaluation using online machine learning packages for streaming data." In 2022 international conference on computer communication and informatics (ICCCI), pp. 1-6. IEEE, 2022.
  • Ray, Santosh Kumar, and Seba Susan. "Performance Analysis of Online Machine Learning 
    Frameworks for Anomaly Detection in IoT Data Streams." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), pp. 1-5. IEEE, 2024.
  • Ray, Santosh Kumar, and Seba Susan. "Error-weighted drift-adaptive ensemble framework for classification of streaming data." Evolving Systems 17, no. 2 (2026): 45.” (SCIE)