Dr. Bhawana Tyagi

About

Dr. Bhawana Tyagi is an Assistant Professor in the School of Computer Science and Engineering at the Vellore Institute of Technology, with over 12 years of teaching and research experience. She holds a Ph.D. in Computer Science and Engineering, with her research focusing on computational approaches for crowd behavior analysis in real-world scenarios.

Her research interests span artificial intelligence, deep learning, computer vision, and cloud computing. She has published several high-impact research papers in reputed SCI/SCIE journals, including Scientific Reports, Neural Computing and Applications, and Journal of Network and Systems Management. Her recent work explores applications of vision transformers, CNN-based models, and AI-driven systems in domains such as healthcare and surveillance.

Dr. Tyagi has actively contributed to academic and professional communities through conference publications, organizing committees, and review activities. She has also taught a wide range of core computer science subjects and mentored undergraduate and postgraduate students in research and projects.

She is UGC-NET qualified and has also cleared GATE with a high percentile, reflecting her strong academic foundation and commitment to excellence in teaching and research.

Employment

• VIT Assistant Professor Senior Grade
  2024 - Present
• Banasthali University Assistant Professor
  2019 - 2024

Education

• Banasthali University PhD
  2019 - 2023

Projects & Funding

Projects & funding information is unavailable.

Publications (16)

• Class-attention pooling and token sparsity based vision transformers for chest X-ray interpretation
  Scientific Reports 2026 DOI: 10.1038/s41598-026-37109-6
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• A lightweight convolutional neural network architecture for violence detection in video sequences
  Scientific Reports 2026 DOI: 10.1038/s41598-026-37743-0
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• An attention based optimized network for the classification of skin lesions
  Scientific Reports 2026 DOI: 10.1038/s41598-025-31220-w
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• Enhanced Face Emotion Recognition Using CNN and YOLOv8 for Real-Time Applications
  Lecture Notes in Networks and Systems 2026 DOI: 10.1007/978-981-95-0684-2_27
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• Hybrid Synthetic Minority Over-sampling Technique (HSMOTE) and Ensemble Deep Dynamic Classifier Model (EDDCM) for big data analytics
  Scientific Reports 2025 DOI: 10.1038/s41598-025-23062-3
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• A model for SLA aware admission control and QoS aware task scheduling in cloud environment
  Peer-to-Peer Networking and Applications 2025 DOI: 10.1007/s12083-025-01988-9
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• RLSK_US: An Improved Dynamic Virtual Machine Consolidation Model to Optimize Energy and SLA Violations in Cloud Datacenter
  Journal of Network and Systems Management 2025 DOI: 10.1007/s10922-025-09936-x
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• Analysis of YOLO Models for Person Detection with Hazardous Objects
  Lecture Notes in Networks and Systems 2025 DOI: 10.1007/978-981-96-2179-8_10
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• Blockchain-Based Electronic Health Record System
  IETE Journal of Research 2025 DOI: 10.1080/03772063.2025.2451060
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• SA-DCPNet: Scale-aware deep convolutional pyramid network for crowd counting
  Neural Computing and Applications 2024 DOI: 10.1007/s00521-024-09572-7
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