Dr. Vaibhav C. Gandhi

About

Vaibhav C. Gandhi is an accomplished academician and researcher, currently serving as an Assistant Professor at MBIT, CVM University, and pursuing postdoctoral research at KLUST University, Malaysia. He holds a Ph.D. from Gujarat Technological University and brings over a decade of combined academic and industry experience, including professional experience as a Software Developer. His areas of expertise include Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, and Data Mining, with a strong research focus on applying advanced AI, ML, and DL methodologies to early disease detection and healthcare applications. A prolific researcher, he has contributed more than 25 research papers, patents, and book chapters to reputed journals, conferences, and edited volumes, including publications indexed in Web of Science and published by internationally recognized publishers such as Springer, Wiley-Scrivener, and Taylor & Francis. He is also actively involved in the global academic and research community and is affiliated with professional organizations including ISTE, IAENG, and SDIWC.

Employment

• MBIT-Madhuben & Bhanubhai Patel Institute of Technology, CVM University Assistant Professor
  2024 - Present
• Devang Patel Institute of Advance Technology & Research (DEPSTAR), Charotar University of Science & Technology (CHARUSAT) ASSISTANT PROFESSOR
  2023 - 2024

Education

• Parul University ME
  2011 - 2013
• LDRP Institute of Technology and Research BE
  2007 - 2011

Projects & Funding

Projects & funding information is unavailable.

Publications (61)

• PhantomWall: A Transformer-Autoencoder Ensemble Approach for Adaptive Zero-Day Web Application Firewall Defense
  2026 DOI: 10.1109/WcCST67302.2026.11496204
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• Advancing glaucoma diagnosis: Multi-modal deep learning with vision transformer architectures
  Intelligence-Based Medicine 2026 DOI: 10.1016/j.ibmed.2026.100355
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• EfficientNetB7 & Bi-LSTM for Deepfake Detection
  2026 DOI: 10.1109/CCIC68129.2026.11486188
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• PrunedLoRa: Robust Gradient-Based Structured Pruning for Efficient Fine-Tuning of Large Language Models
  2026 DOI: 10.1109/CCIC68129.2026.11486129
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• Generative Adversarial Networks for Early Autism Detection: A Novel Approach Using ML
  2026 DOI: 10.1007/978-3-032-10047-4_15
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• Optimizing birth weight prediction using hybrid convolutional and long short-term memory networks
  AIP Conference Proceedings 2026 DOI: 10.1063/5.0327175
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• Synergizing CNN and LSTM in a Hybrid Framework for Precise Early Detection of Pediatric Heart Disease
  2026 DOI: 10.1007/978-981-96-9196-8_32
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• The Impact of Deep Learning on Image Recognition and Classification: Techniques, Applications, and Future Directions
  2026 DOI: 10.1007/978-981-96-8563-9_24
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• Optimizing Fuzzy Decision Systems with the Jaya Algorithm for Enhanced Data Transfer in Multi-Hop CRNs
  Franklin Open 2026 DOI: 10.1016/j.fraope.2026.100722
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• Wireless Sensor Network-Driven Human Intrusion Detection Using RT-DETR for Real-Time Perimeter Protection
  2025 International Conference on Networks and Cryptology (NETCRYPT) 2025 DOI: 10.1109/netcrypt65877.2025.11102501
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