Subramaniyaswamy

About

Subramaniyaswamy Vairavasundaram received the Ph.D. degree from Anna University, in 2013, and continued the extension work with the Department of Science and Technology Support, as a Young Scientist award holder. He is currently a Professor with the School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India. With the experience of more than 18 years, as an Academician and a Researcher, he has contributed more than 200 articles and chapters for many high-quality technology journals and books that are being edited by internationally acclaimed professors and professionals. He is a Research Supervisor and successfully guided seven research scholars, and he is also a Visiting Expert to various universities in India and Abroad. His technical competencies lie in recommender systems, computer vision, artificial intelligence, machine learning, and big data analytics. He has received government funded and consultancy projects from DST-SERB, DST-CSRI, ICSSR–IMPRESS, MHRD(MoE), TVS MOTORS, MHI, and SERB–MATRICS. He is on the reviewer board of several international journals and has been a program committee member for several international/national conferences and workshops.

Employment

• Vellore Institute of Technology University Professor
  2024 - Present
• SASTRA University Professor
  2021 - 2024
• SASTRA Deemed University Associate Professor
  2018 - 2021

Education

• Anna University, Chennai Ph.D.
  2009 - 2013
• Sathyabama University M.Tech.
  2006 - 2008
• Bharathidasan University B.E.
  1999 - 2003

Projects & Funding

Projects & funding information is unavailable.

Publications (198)

• Parameter-efficient fine-tuning of Llama models for crisis-tweet categorization: A Pareto-informed trade-off analysis
  Results in Engineering 2026 DOI: 10.1016/j.rineng.2026.110247
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• SignCraft: Transformative Learning-Based Sign Gesture Generation for Consumer Electronics
  IEEE Transactions on Consumer Electronics 2026 DOI: 10.1109/TCE.2026.3658738
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• Corrections to “An Improved Boykov’s Graph Cut-Based Segmentation Technique for the Efficient Detection of Cervical Cancer”
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3723044
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• Sensitivity-Guided Mixed-Precision Quantization-Aware Training for Large Language Models
  IEEE Access 2026 DOI: 10.1109/ACCESS.2026.3698449
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• An IoT based remote medical diagnosis system using one time pad cipher over MQTT protocol
  Scientific Reports 2025 DOI: 10.1038/s41598-025-26208-5
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• An Exploration of Generative AI Frameworks and Tools for Generation of Multi-Perspective Contents
  2025 DOI: 10.1201/9781003533009-12
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• Comparative Analysis of Transformer Models for Stack Overflow Question Quality Classification
  2025 DOI: 10.1201/9781003533009-21
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• Human-AI Collaboration with Decision Control and Adaptive Trust for Enhancing User Perceptions
  2025 DOI: 10.1201/9781003533009-6
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• Image-Based Analysis of Parkinson's Disease Using Generative Artificial Intelligence Algorithms
  2025 DOI: 10.1201/9781003533009-10
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• Impact of Commercial Applications on GenAI with Its Evolving Landscape
  2025 DOI: 10.1201/9781003533009-16
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