Journals

• [9] Shiv Nath Chaudhri. “Recursive Shrinking Towards Effective Cluster Isolation for Robust Electronic Noses”. In: IEEE Access (2025).
• [8] Shiv Nath Chaudhri and Swalpa Kumar Roy. “A Discriminatory Groups-Based Supervised Band Selection Technique for Hyperspectral Image Classification”. In: Remote Sensing Letters 15.2 (2024), pp. 111–120.
• [7] Shiv Nath Chaudhri. “ASASA: Automatic Selection and Adaption in Sensor Array for Intelligent Artificial Olfaction Systems”. In: IEEE Sensors Letters 7.9 (2023), pp. 1–4.
• [6] Kanak Kumar et al. “An IoT-Enabled E-Nose for Remote Detection and Monitoring of Airborne Pollution Hazards Using LoRa Network Protocol”. In: Sensors 23.10 (2023), p. 4885.
• [5] Sumit Srivastava et al. “A Novel Data-Driven Technique to Produce Multi-Sensor Virtual Responses for Gas Sensor Array-Based Electronic Noses”. In: Journal of Electrical Engineering 74.2 (2023), pp. 102–108.
• [4] Sumit Srivastava et al. “Spatial Upscaling-Based Algorithm for Detection and Estimation of Hazardous Gases”. In: IEEE Access 11 (2023), pp. 17731–17738.
• [3] Shiv Nath Chaudhri and Navin Singh Rajput. “Multidimensional Multiconvolution-Based Feature Extraction Approach for Drift Tolerant Robust Classifier for Gases/Odors”. In: IEEE Sensors Letters 6.4 (2022), pp. 1–4.
• [2] Shiv Nath Chaudhri, Navin Singh Rajput, and Ashutosh Mishra. “A Novel Principal Component-Based Virtual Sensor Approach for Efficient Classification of Gases/Odors”. In: Journal of Electrical Engineering 73.2 (2022), pp. 108–115.
• [1] Shiv Nath Chaudhri et al. “Zero-Padding and Spatial Augmentation-Based Gas Sensor Node Optimization Approach in Resource-Constrained 6G-IoT Paradigm”. In: Sensors 22.8 (2022), p. 3039.

Conferences:

• [25] Arya Awachat, Ananya Dube, and Shivnath Chaudhri. “ML for Sustainable Solutions: Applications in Renewable Energy Optimization and Climate Change Prediction”. In: 2025 4th International Conference on Sentiment Analysis and Deep Learning (ICSADL). IEEE. 2025, pp. 1689–1694.
• [24] Yash S Pachghare et al. “Analysing Indoor Gas Concentration Using Machine Learning Models”. In: 2025 3rd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIHEI). IEEE. 2025, pp. 1–5.
• [23] Chinmay Pawar et al. “Deep Learning-Based Multi-Class Classification of Cough Sounds for Respiratory Disease Detection and Real-Time Screening”. In: 2025 3rd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIHEI). IEEE. 2025, pp. 1–6.
• [22] Tejas Pisal et al. “AI-Driven Transcription and Analysis for Medical Conversations”. In: 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE. 2025, pp. 1228–1234.
• [21] Komal Pokale and Shiv Nath Chaudhri. “Transfer Learning and Domain Adaptation in Hyperspectral Image Processing: An Overview”. In: 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE. 2025, pp. 1208–1213.
• [20] Rahul Raushan et al. “Advancing Healthcare Through Internet of Things: A Comprehensive Review of Smart Healthcare Systems and Their Applications”. In: 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE. 2025, pp. 1946–1951.
• [19] Yashasvi Raut and Shiv Nath Chaudhri. “Deep Learning Utility for Gas/Odor Sensor Signature Analysis”. In: 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE. 2025, pp. 515–519.
• [18] David Raymond, Shivnath Chaudhri, and Kahkasha Shaikh. “Data Processing and Pattern Recognition for Electronic Nose”. In: 2025 International Conference on Electronics and Renewable Systems (ICEARS). IEEE. 2025, pp. 463–468.
• [17] Mohan K Warbhe, Joy Jordan Bore, and Shiv Nath Chaudari. “A deep learning-based system to predict the plant disease using streamlit”. In: 2025 4th international conference on sentiment analysis and deep learning (ICSADL). IEEE. 2025, pp. 1744–1751.
• [16] Prajyot R Yesankar, Shiv Nath Chaudhri, and Pradnyawant Gote. “Impact of Artificial Intelligence on Healthcare: Opportunities and Challenges”. In: 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI). IEEE. 2025, pp. 1478–1483.2
• [15] Shiv Nath Chaudhri. “Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical Engineering”. In: 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI). IEEE. 2024, pp. 1–6.
• [14] Shiv Nath Chaudhri. “Recent gas/odor sensor array signal processing trend for model nose: A mini review”. In: 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC). IEEE. 2024, pp. 35–41.
• [13] Dharmendra Kumar et al. “Enhancing Security with Microwave and LiDAR Sensor Integration”. In: 2024 International Conference on Emerging Systems and Intelligent Computing (ESIC). IEEE. 2024, pp. 130–135.
• [12] Yashasvi Raut and Shiv Nath Chaudhri. “Comprehensive Overview of Gas and Bio-Sensors Enabling Artificial Intelligence in Healthcare”. In: 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI). IEEE. 2024, pp. 1–6.
• [11] Hrutik Singewar, Shiv Nath Chaudhri, and Subodhkumar Daronde. “Reducing False Alarm Situation in LPG Leak Detection Using Arduino-Based Multi-Sensor (MQ-2, MQ-5, and MQ-6 Gas Sensor) Module”. In: 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI). IEEE. 2024, pp. 1–5.
• [10] Radha Wasudeo Wande, Shiv Nath Chaudhari, and Rutuja Nitin Lanjewar. “Interdisciplinary Research Scope for Electronic Nose”. In: 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI). IEEE. 2024, pp. 1–5.
• [9] SN Chaudhri et al. “Synergetic effect of complementary nature of hyperspectral and lidar data for high performance lulc classification”. In: 2023 3rd International Conference on Intelligent Technologies (CONIT). IEEE. 2023, pp. 1–6.
• [8] SN Chaudhri et al. “Vision Transformer-Based LULC Classification Using Remotely Sensed Hyperspectral Image”. In: International Conference on Advances in Signal Processing and Communication Engineering. Springer. 2023, pp. 127–136.
• [7] Dharmendra Kumar, Shiv Nath Chaudhri, and Navin Singh Rajput. “A machine learning-based disinfectant type, concentration, and usage monitoring system for real-world scenarios”. In: 2023 International Conference on IoT, Communication and Automation Technology (ICICAT). IEEE. 2023, pp. 1–6.
• [6] Dharmendra Kumar, Shiv Nath Chaudhri, and Navin Singh Rajput. “Air quality prediction and monitoring using machine learning-based forecasting approach”. In: 2023 International Conference on IoT, Communication and Automation Technology (ICICAT). IEEE. 2023, pp. 1–6.
• [5] Shiv Nath Chaudhri and NS Rajput. “Mirror Mosaicking: A Novel Approach to Achieve High-performance Classification of Gases Leveraging Convolutional Neural Network.” In: SENSORNETS. 2021, pp. 86–91.
• [4] Shiv Nath Chaudhri et al. “Mirror mosaicking based reduced complexity approach for the classification of hyperspectral images”. In: 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. IEEE. 2021, pp. 3657–3660.
• [3] SN Chaudhri, NS Rajput, and KP Singh. “The novel camouflaged false color composites for the vegetation verified by novel sample level mirror mosaicking based convolutional neural network”. In: 2020 IEEE India Geoscience and Remote Sensing Symposium (InGARSS). IEEE. 2020, pp. 237–240.
• [2] Shiv Nath Chaudhri et al. “Different modality based remote sensing data fusion approach for efficient classification of agriculture and urban subclasses”. In: IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE. 2019, pp. 5710–5713.
• [1] Shiv Nath Chaudhri et al. “Maximum membership fraction based pure pixel assessment approach for hyperspectral data analysis using deep learning”. In: IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium. IEEE. 2019, pp. 5820–5823.

Book Chapters:

• [2] Shiv Nath Chaudhri, Ashutosh Mishra, and Navin Singh Rajput. “Advanced data-driven approaches for intelligent olfaction”. In: Advanced Interdisciplinary Applications of Machine Learning Python Libraries for Data Science. IGI global, 2023, pp. 124–154.
• [1] Dharmendra Kumar et al. “Intelligent monitoring of disinfectants”. In: IoT, Big Data and AI for Improving Quality of Everyday Life: Present and Future Challenges: IOT, Data Science and Artificial Intelligence Technologies. Springer, 2023, pp. 379–391.