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Dr. Vivek Mehta

Dr. Vivek Mehta
Assistant Professor
Qualification
Ph.D.

 

 

 

Dr. Vivek Mehta completed his PhD from Thapar University, Patiala in 2021. He is working as Assistant professor in Netaji Subhas university of Technology, Delhi. Earlier, he was associated with Bennett University of the Times Group, Greater Noida from Aug 2021 to June 2025. He is a NVIDIA DLI ambassador for the workshop Building LLM applications with Prompt Engineering which focuses on programmatically interacting with Large Language Models using Langchain Framework and Prompt Engineering Techniques. His research area lies mainly at the intersection of Natural Language processing and Machine Learning. He has published research papers in reputed SCI/SCIE journals such as Expert Systems with applications, Artificial Intelligence reviews, Complex and Intelligent Systems in the application areas like sentiment analysis, dialogue summarization, detecting AI written text, and plant disease detection etc. He has delivered expert lectures in reputed institutes such as NIT Kurukshetra,  IIIT Nagpur, S R University Warangal etc. in the field of AI/ML. He is also passionate about fostering positive mental health specifically among the youth, and has conducted seminars on topics such as Positive Programming of Mind and Enhancing concentration with Meditation.

 

Areas of Interest

  • Machine learning
  • Deep Learning
  • Natural language processing
  • Large Language Models
  • Computer Vision

 

Publications in International Journal

  1. V Mehta, S Bawa, J Singh, Analytical review of clustering techniques and proximity measures, Artificial Intelligence Review 53, 5995–6023 (2020). https://doi.org/10.1007/s10462-020-09840-7 (SCI/SCIE).
  2. V Mehta, S Bawa, J Singh, WEClustering: word embeddings based text clustering technique for large datasets, Complex & Intelligent Systems 7, 3211–3224 (2021). https://doi.org/10.1007/s40747-021-00512-9 (SCI/SCIE).
  3. V Mehta, S Bawa, J Singh, Stamantic Clustering: Combining Statistical and Semantic Features for Clustering of Large Text Datasets, Expert Systems with Applications, 174, 2021, 114710, https://doi.org/10.1016/j.eswa.2021.114710 (SCI/SCIE).
  4. V Mehta, M Agarwal, RK Kaliyar, A comprehensive and analytical review of text clustering techniques, International Journal of Data Science and Analytics, 18, 239–258 (2024). https://doi.org/10.1007/s41060-024-00540-x (ESCI).
  5. L. Mohanty, A Kumar, V Mehta, M Agarwal, JS Suri, Pruning techniques for artificial intelligence networks: a deeper look at their engineering design and bias: the first review of its kind, Multimedia Tools and Applications 84, 9591–9665 (2025). https://doi.org/10.1007/s11042-024-19192-x (Scopus).
  6. L. Mohanty, M Agarwal , V Mehta, FCDC: Firefly optimization algorithm based compression of deep CNN model with explainability, Cluster Computing, Accepted (2025) (SCI)

 

Publications in National conferences

  1. V. Mehta, M. Agarwal, S. Yadav and J. Sahni, "Efficiently Fine-Tuned Flan T5 LLM for Happiness Oriented Dialogue Summarization," 2025 International Conference on Innovation in Computing and Engineering (ICE), Greater Noida, India, 2025, pp. 1-6, doi: 10.1109/ICE63309.2025.10984314.
  2. M. Agarwal, R. K. Kaliyar and V. Mehta, "Skin Disease Classification with Help of Artificial Intelligence Techniques," 2024 IEEE 16th International Conference on Computational Intelligence and Communication Networks (CICN), Indore, India, 2024, pp. 1169-1174, doi: 10.1109/CICN63059.2024.10847516.
  3. R. Harsh, R. Patodiya, R. Agarwal and V. Mehta, "Analysing Emotional Drivers and Behavioural Patterns of Twitter Overuse in India During the COVID-19 Lockdown using ML and BERT," 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT), Kamand, India, 2024, pp. 1-6, doi: 10.1109/ICCCNT61001.2024.10725268.
  4. M. Agarwal, R. K. Kaliyar and V. Mehta, "Fake News Detection Using Multi Modal Deep Neural Network," 2024 5th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), Bangkok, Thailand, 2024, pp. 1-5, doi: 10.1109/TIMES-iCON61890.2024.10630743.
  5. Sharma, Abhinav and Tomar, Sakshi and Pal, Yogesh and Mehta, Vivek, Optimizing Churn Prediction in the Telecom Industry: Leveraging Support Vector Classifier for Enhanced Accuracy (May 12, 2024). Proceedings of the International Conference on Innovative Computing & Communication (ICICC 2024), Available at SSRN: https://ssrn.com/abstract=4825674 or http://dx.doi.org/10.2139/ssrn.4825674
  6. Bisht, D., Kumari, S., Kanupriya, Pal, Y., Mehta, V. (2024). Lip Movement Detection—A Survey of State-of-the-Art Approaches. In: Hassanien, A.E., Anand, S., Jaiswal, A., Kumar, P. (eds) Innovative Computing and Communications. ICICC 2024. Lecture Notes in Networks and Systems, vol 1038. Springer, Singapore. https://doi.org/10.1007/978-981-97-4149-6_7
  7. Mehta, V., Chana, I. (2017). Urban Traffic State Estimation Techniques Using Probe Vehicles: A Review. In: Vishwakarma, H., Akashe, S. (eds) Computing and Network Sustainability. Lecture Notes in Networks and Systems, vol 12. Springer, Singapore. https://doi.org/10.1007/978-981-10-3935-5_28

 

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