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Dr. Krishnan Batri

Dr. Krishnan Batri

Associate Dean & Professor , Computer Science & Engineering (CSE)

batri.k@sharda.ac.in

About

Dr. Krishnan Batri is a Professor, Associate Dean  in the School of Computer Science and Engineering at Sharda University, Greater Noida. He holds a Ph.D. in Computer Science and Engineering from the National Institute of Technology (NIT), Tiruchirappalli, and is an accomplished academician with extensive experience in teaching, research, curriculum development, and academic leadership.

His research interests include Information Retrieval, Artificial Intelligence, Genetic Algorithms, Data Fusion Techniques, Deep Learning, and Intelligent Information Systems. His work focuses on developing intelligent computational models that address real-world challenges across information retrieval, healthcare, and data-driven applications.

Dr. Batri has established a strong research profile through numerous publications in reputed national and international journals and conferences. He has successfully supervised 13 Ph.D. scholars, mentoring researchers in emerging areas of computer science and engineering. His commitment to high-quality research has contributed significantly to advancements in artificial intelligence and intelligent computing.

An advocate of outcome-based education and innovation in teaching, Dr. Batri actively contributes to curriculum design, academic planning, and the development of industry-oriented learning environments. He has played an important role in fostering academic collaborations, promoting interdisciplinary research, and encouraging innovation among faculty members and students at both national and international levels.

Dr. Batri is passionate about integrating research with education to create meaningful technological solutions for society. Through his leadership, mentorship, and scholarly contributions, he continues to inspire students and researchers to pursue excellence, innovation, and lifelong learning while contributing to the advancement of computer science and engineering.

Experience
  • 23 years
Qualification
  • Ph.D
  • M.E
Research

Research Papers:

  • “Thermodynamic Modeling of Hashtag Dynamics for Social Media Clustering: A Maxwell-Boltzmann Approach”, IEEE Access, August 2025.
  • “STIM: A Unified Spatially-Informed Model for Robust Hyperspectral Anomaly Detection”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, January 2026
  • “STIM-D: A 31× Faster Spatially-Informed Anomaly Detector with High-Confidence Saliency Preservation”, IEEE Geoscience and Remote Sensing Letters, May 2026.
  • “Decoding basal ganglia motor circuit dysfunction from handwriting: a physics-informed neural signal interpretation framework for Parkinsons disease screening”, Frontiers in Neuroinfomatics, June 2026
  • “Beyond Equal Weighting: Pareto-Optimal Descriptor Fusion for Hyperspectral Anomaly Detection via Multi-Objective Optimization”, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, June 2026

Certifications

  • Completed FDP on “ OBE and Accreditation” in NPTEL , Nov 2025
  • Completed FDP on” Introduction to Information Retrieval” in NPTEL, April 2026

Area of Interest

  • Information Retrieval,
  • Artificial Intelligence,
  • Genetic Algorithms,
  • Data Fusion Techniques