Research Interests

Remote Sensing

GIS

Artificial Intelligence

Machine Learning

Deep Learning

Publications

1. N. Vyas, S. Singh, and G. K. Sethi, “An Efficient Posterior Probability-Based Image Fusion Change Detection Model for the Estimation of Seasonal Agricultural Changes Using Microwave and Optical Datasets,” Computers and Electronics in Agriculture, article 110683, Oct. 2025. doi: 10.1016/j.compag.2025.110683 (SCIE Q1, Impact Factor - 8.7).
2. G. Singh, N. Vyas, N. Dahiya, S. Singh, N. Bhati, V. Sood, and D. K. Gupta, “A novel pixel-based deep neural network in posterior probability space for the detection of agriculture changes using remote sensing data,” Remote Sensing Applications: Society and Environment, May 2025. doi: 10.1016/j.rsase.2025.101591 (ESCI Q2, Impact Factor - 4.5).
3. N. Vyas, S. Singh, and G. K. Sethi, “A novel image fusion-based post classification framework for agricultural variations detection using Sentinel-1 and Sentinel-2 data,” Earth Science Informatics, Dec. 2024. doi: 10.1007/s12145-024-01506-0 (SCIE Q2, Impact Factor - 3.0).
4. A. Kumar, P. Sharma, N. Vyas, A. Sharma, R. Maheshwari, and P. K. Dutta, “Land Use Land Cover Mapping Using Random Forest and Multispectral Satellite Imagery in Google Earth Engine,” in Proc. 2025 Third International Conference on Networks, Multimedia and Information Technology (NMITCON), IEEE, pp. 1–5, Aug. 1, 2025. doi: 10.1109/nmitcon65824.2025.11188013.
5. Garima and N. Vyas, “Fundamentals of Disaster Management Using Remote Sensing,” in Artificial Intelligence in Remote Sensing for Disaster Management, Wiley, ch. 3, pp. 35–57, Jun. 2025. doi: 10.1002/9781394287222.ch3.
6. Abhishek Kumar, S. Bhatia Khan, N. Vyas, V. Dutt, and S. Basheer, Eds., Secure Energy Optimization: Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency, Scrivener Publishing LLC (Wiley), Aug. 2025. doi: 10.1002/9781394271849.
7. A. Vinciarelli, S. Singh, N. Vyas, and M. A. S. Ali, Eds., RADAR: Remote Sensing Data Analysis with Artificial Intelligence, De Gruyter, Jul. 2025. doi: 10.1515/9783111572970.
8. N. Vyas, “Integrating Sentinel-1 satellite data with machine learning for land use classification,” in RADAR: Remote Sensing Data Analysis with Artificial Intelligence, De Gruyter, pp. 1–16, Jul. 2025. doi: 10.1515/9783111572970-001.
9. N. Bhati, N. Vyas, R. Yadav, R. Sharma, and K. Sundar, “Revolutionizing agricultural and environmental analytics with synthetic aperture radar (SAR): innovations, challenges, and future directions,” in RADAR: Remote Sensing Data Analysis with Artificial Intelligence, De Gruyter, pp. 229–244, Jul. 2025. doi: 10.1515/9783111572970-015.
10. K. Sundar, N. Vyas, and N. Bhati, “Real-Time Earthquake Monitoring with Remote Sensing and AI Technology,” in Artificial Intelligence in Remote Sensing for Disaster Management, Wiley, ch. 17, pp. 303–322, Jun. 2025. doi: 10.1002/9781394287222.ch17.
11. N. Vyas, K. Sundar, A. Sharma, and P. S. Adhikari, “Leveraging Sentinel-2 Multispectral Data and Machine Learning Algorithms for Land Use Land Cover Mapping in Semi-Arid Regions,” in Proc. InCACCT, IEEE, Gharuan, India, pp. 439–443, May 2025. doi: 10.1109/InCACCT65424.2025.11011472.
12. N. Vyas, A. Sharma, A. Nayyar, M. Shrivastava, and D. Gowda V, Eds., Proceedings of the International Conference on Advancements in Computing Technologies and Artificial Intelligence (COMPUTATIA 2025), Atlantis Press International BV, Apr. 2025. doi: 10.2991/978-94-6463-700-7.
13. N. Bhati and N. Vyas, “Advanced Architectures and Innovative Platforms for Federated Learning: A Comprehensive Exploration,” in Model Optimization Methods for Efficient and Edge AI, Wiley, ch. 8, pp. 145–155, Nov. 2024. doi: 10.1002/9781394219230.ch8.
14. Y. Mahajan, M. Sharma, A. Meça, N. Vyas and R. Sharma, “Mathematical Optimization for Enhanced AI-Enabled Geospatial Intelligence,” in Math Optimization for Artificial Intelligence, De Gruyter, pp. 239–260, Apr. 2025. doi: 10.1515/9783111436180-011.
15. N. Vyas, G. K. Sethi, and S. Singh, “Comparative Analysis of Different Classifiers on Fusion of Sentinel Datasets for Agriculture Land,” in Proc. ICTACS, IEEE, Nov. 2024. doi: 10.1109/ictacs62700.2024.10840995.
16. U. K. Lilhore, A. Kumar, N. Vyas, S. Simaiya, and V. Dutt, Eds., Multimodal Data Fusion for Bioinformatics Artificial Intelligence, Scrivener Publishing LLC (Wiley), Feb. 2025. doi: 10.1002/9781394269969.
17. A. Kumar, N. Vyas, P. S. Rathore, A. Anand, and P. Dixit, Eds., Internet of Medicine for Smart Healthcare, Scrivener Publishing LLC (Wiley), Dec. 2024. doi: 10.1002/9781394272266.
18. U. K. Lilhore, A. Kumar, S. P. Yadav, A. Anand, and N. Vyas, Eds., AI-Driven Alzheimer’s Disease Detection and Prediction, IGI Global, Aug. 2024. doi: 10.4018/979-8-3693-3605-2.
19. P. Raj, H. H. Song, D.-N. Le, and N. Vyas, Eds., Quantum Machine Learning: Quantum Algorithms and Neural Networks, De Gruyter, Jul. 2024. doi: 10.1515/9783111342276.
20. U. K. Lilhore, A. Kumar, S. Simaiya, N. Vyas, and V. Dutt, Eds., Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods, IGI Global, Apr. 2024. doi: 10.4018/979-8-3693-1822-5.
21. A. Kumar, A. L. Srivastav, A. K. Dubey, V. Dutt, and N. Vyas, Eds., Innovations in Machine Learning and IoT for Water Management, IGI Global, Nov. 2023. doi: 10.4018/979-8-3693-1194-3.
22. V. Dutt, A. Kumar, S. Ahuja, A. Baliyan, and N. Vyas, Eds., Quantum Innovations at the Nexus of Biomedical Intelligence, IGI Global, Dec. 2023. doi: 10.4018/979-8-3693-1479-1.
23. N. Bhati and N. Vyas, “Elevating IoT Sensor Data Management and Security Through Blockchain Solutions,” in IGI Global chapter listing, Mar. 2024. doi: https://www.igi-global.com/chapter/.../342145.
24. N. Bhati, N. Vyas, V. Dutt, R. Duggar, and A. Pokhriyal, “Advanced Real-Time Simulation Framework for the Physical Interaction Dynamics of Production Lines Leveraging Digital Twin Paradigms,” in Wiley, ch. 15, May 2024. doi: 10.1002/9781394257003.ch15.
25. N. Vyas and V. Dutt, “Advancing Precision Agriculture: Leveraging YOLOv8 for Robust Deep Learning Enabled Crop Diseases Detection,” in Proc. ICICIS, IEEE, Pune, India, pp. 1–6, Nov. 2023. doi: 10.1109/ICICIS56802.2023.10430280.
26. N. Vyas, V. C. Patil, V. Desai Jabbar and Anurag, “Genetic Algorithm-Driven Hyperparameter Optimization of Capsule Networks for Predictive Analysis of Genetic Mutations,” in Proc. ICIIP, IEEE, Solan, India, pp. 616–621, Nov. 2023. doi: 10.1109/ICIIP61524.2023.10537665.
27. N. Vyas, A. Gudur, A. I. Tamboli and Anurag, “Hybrid Convolutional-Recurrent Neural Network Architecture with Attention Mechanisms for Multi-modal Medical Image Segmentation,” in Proc. ICIIP, IEEE, Solan, India, pp. 622–627, Nov. 2023. doi: 10.1109/ICIIP61524.2023.10537765.
28. N. Vyas, N. N. Jadhav, V. V. Raje and C. Choudhary, “Distributed Deep Reinforcement Learning with Graph Neural Networks for Personalized Drug Interaction Analysis,” in Proc. ICIIP, IEEE, Solan, India, pp. 610–615, Nov. 2023. doi: 10.1109/ICIIP61524.2023.10537643.
29. C. Choudhary, N. Vyas and U. K. Lilhore, “An Optimized Sign Language Recognition using Convolutional Neural Networks (CNNs) and TensorFlow,” in Proc. ICTACS, IEEE, Tashkent, Uzbekistan, pp. 896–901, Nov. 2023. doi: 10.1109/ICTACS59847.2023.10390276.
30. Mamta, M. B. Mane, N. Vyas and A. Baliyan, “Detecting Seizures from EEG Data: The Potential of Deep Learning Techniques,” in Proc. ICTACS, IEEE, Tashkent, Uzbekistan, pp. 439–444, Nov. 2023. doi: 10.1109/ICTACS59847.2023.10390369.
31. C. Choudhary, N. Vyas and U. Kumar Lilhore, “Cloud Security: Challenges and Strategies for Ensuring Data Protection,” in Proc. ICTACS, IEEE, Tashkent, Uzbekistan, pp. 669–673, Nov. 2023. doi: 10.1109/ICTACS59847.2023.10390302.
32. N. Vyas, P. A. P., P. Das and Y. Mahajan, “The Impact of Air Pollution on Respiratory Health Results: An Analysis of Asthma and COPD in a Population Study,” in Proc. ICCCIS, IEEE, Greater Noida, India, pp. 141–146, Nov. 2023. doi: 10.1109/ICCCIS60361.2023.10425187.
33. Anurag, N. Vyas and U. Kumar Lilhore, “Transforming Work: The Impact of Artificial Intelligence (AI) On Modern Workplace,” in Proc. ICTACS, IEEE, Tashkent, Uzbekistan, pp. 602–607, Nov. 2023. doi: 10.1109/ICTACS59847.2023.10390258.
34. K. Bansal, S. Agarwal and N. Vyas, “Deepfake Detection Using CNN And DCGANS To Drop-Out Fake Multimedia Content: A Hybrid Approach,” in Proc. ICICAT, IEEE, Gorakhpur, India, pp. 1–6, Oct. 2023. doi: 10.1109/ICICAT57735.2023.10263628.
35. V. R. Burugadda, V. Dutt, Mamta and N. Vyas, “Personalized Cardiovascular Disease Risk Prediction using Random Forest: An Optimized Approach,” in Proc. AIC, IEEE, Sonbhadra, India, pp. 226–232, Oct. 2023. doi: 10.1109/AIC57670.2023.10263915.
36. H. Dhiman, N. Vyas, A. Pagrotra and V. Dutt, “Real-Time Traffic Analysis and Driver Safety Enhancement via IoT and Computer Vision with High-Resolution Project Lamps for Intelligent Road Illumination,” in Proc. CCPIS, IEEE, Bhubaneswar, India, pp. 01–06, Sep. 2023. doi: 10.1109/CCPIS59145.2023.10291872.
37. V. R. Burugadda, A. Guddur, N. Vyas, and A. Pokhriyal, “Design and Evaluation of a Nanotechnology-Based Drug Delivery System for Enhanced Efficacy and Safety in Cancer Treatment,” in Proc. ICAECC, IEEE, Sep. 7, 2023. doi: 10.1109/icaecc59324.2023.10560299.
38. H. Prasad, A. Singh, J. Thakur, C. Choudhary and N. Vyas, “Artificial Intelligence Based Fire and Smoke Detection and Security Control System,” in Proc. NMITCON, IEEE, Bengaluru, India, pp. 01–06, Sep. 2023. doi: 10.1109/NMITCON58196.2023.10276198.
39. B. Sharma and N. Vyas, “Healthcare in the Aftermath of COVID-19: Charting a Course for the Future,” in Proc. ICCPCT, IEEE, Kollam, India, pp. 1280–1285, Sep. 2023. doi: 10.1109/ICCPCT58313.2023.10244828.
40. Akanksha, K. Ranjan and N. Vyas, “Deep Learning-Based Automatic Face Expression Recognition Framework,” in Proc. ICCPCT, IEEE, Kollam, India, pp. 1291–1296, Sep. 2023. doi: 10.1109/ICCPCT58313.2023.10245885.
41. U. S. Sekhar, N. Vyas, V. Dutt and A. Kumar, “Multimodal Neuroimaging Data in Early Detection of Alzheimer’s Disease - Exploring the Role of Ensemble Models and GAN Algorithm,” in Proc. ICCPCT, IEEE, Kollam, India, pp. 1664–1669, Sep. 2023. doi: 10.1109/ICCPCT58313.2023.10245177.
42. V. R. Burugadda, V. C. Patil, N. Vyas and A. Pokhriyal, “Enhancing Breast Cancer Diagnosis: A Deep Belief Network Approach for Mammography Image Analysis,” in Proc. ICAICCIT, IEEE, Faridabad, India, pp. 46–51, Nov. 2023. doi: 10.1109/ICAICCIT60255.2023.10465784.
43. S. R. Burri, D. K. Agarwal, N. Vyas and R. Duggar, “A Machine Learning Framework for Accurate Prediction of Parkinson’s Disease from Speech Data,” in Proc. CISCT, IEEE, Dehradun, India, pp. 1–6, Sep. 2023. doi: 10.1109/CISCT57197.2023.10351422.
44. Anurag, N. Vyas, V. Sharma and D. Balla, “Chronic Kidney Disease Prediction Using Robust Approach in Machine Learning,” in Proc. CISCT, IEEE, Dehradun, India, pp. 1–5, Sep. 2023. doi: 10.1109/CISCT57197.2023.10351277.
45. V. R. Burugadda, N. Jadhav, N. Vyas and R. Duggar, “Exploring the Potential of Deep Reinforcement Learning for Autonomous Navigation in Complex Environments,” in Proc. ICCUBEA, IEEE, Pune, India, pp. 1–6, Aug. 2023. doi: 10.1109/ICCUBEA58933.2023.10392109.
46. V. R. Burugadda, N. Vyas and A. Pagrotra, “Enhancing Land-Based Robotics through the Development of Remotely Operated Vehicles for Military, Rescue and Industrial Applications,” in Proc. ASIANCON, IEEE, Ravet, India, pp. 1–6, Aug. 2023. doi: 10.1109/ASIANCON58793.2023.10270756.
47. S. R. Burri, D. K. Agarwal, N. Vyas and R. Duggar, “Optimizing Irrigation Efficiency with IoT and Machine Learning: A Transfer Learning Approach for Accurate Soil Moisture Prediction,” in Proc. WCONF, IEEE, Raipur, India, pp. 1–6, Jul. 2023. doi: 10.1109/WCONF58270.2023.10235220.
48. R. Punugoti, N. Vyas, A. T. Siddiqui and A. Basit, “The Convergence Of Cutting-Edge Technologies: Leveraging AI and Edge Computing to Transform the Internet of Medical Things (IoMT),” in Proc. ICESC, IEEE, Coimbatore, India, pp. 600–606, Jul. 2023. doi: 10.1109/ICESC57686.2023.10193047.
49. R. Raturi, A. Kumar, N. Vyas and V. Dutt, “A Novel Approach for Anomaly Detection in the Time-Series Data using Generative Adversarial Networks,” in Proc. ICSC... (ICSCSS), IEEE, Coimbatore, India, pp. 1352–1357, May 2023. doi: 10.1109/ICSCSS57650.2023.10169365.
50. S. Chandrasekaran, V. Dutt, N. Vyas and A. Anand, “Fuzzy KNN Implementation for Early Parkinson’s Disease Prediction,” in Proc. ICCMC, IEEE, Erode, India, pp. 896–901, Feb. 2023. doi: 10.1109/ICCMC56507.2023.10083522.
51. S. Chandrasekaran, R. Agrawal, V. Dutt, and N. Vyas, “Improved Healthcare System with Quantum Computing,” in Proc. AISC, IEEE, Jan. 27, 2023. doi: 10.1109/aisc56616.2023.10085380.
52. S. Chandrasekaran, V. Dutt, N. Vyas, and R. Kumar, “Student Sentiment Analysis Using Various Machine Learning Techniques,” in Proc. AISC, IEEE, Jan. 27, 2023. doi: 10.1109/aisc56616.2023.10085018.
53. H. Krishna and N. Vyas, “RFID Based Attendance Monitoring System Using ESP8266 Wi-Fi Module and IoT Enabled Mobile Application,” Neural Computing and Applications, vol. 34, no. 9, pp. 2907–2916, Sep. 2022. doi: 10.14704/nq.2022.20.9.NQ44681.
54. S. Boyapati, S. R. Swarna, V. Dutt, and N. Vyas, “Big Data Approach for Medical Data Classification: A Review Study,” in Proc. ICISS, IEEE, Dec. 3, 2020. doi: 10.1109/iciss49785.2020.9315870.

Conferences, Talks & Speaking Engagements

• Served as a Session Chair at the 7th IEEE International Conference on Emerging Smart Computing and Informatics (ESCI-2025), held from 5th to 7th March 2025 in Pune.
• Served as a Session Chair at the 1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries (ICAIIHI-2023).
• Conducted a two-day Faculty Development Program (FDP) on the Internet of Things at Chitkara University.