PhD (CSE), Mtech (IT), Btech (IT), Diploma in Engineering (Medical Electronics), MA Education, PG Diploma in Cyber Laws, LLB (Hons.)
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Artificial Intelligence, Computer Science Applications, Information Systems
152
Scopus Publications
1613
Scholar Citations
23
Scholar h-index
66
Scholar i10-index
Scopus Publications
A hybrid bio-inspired model for predicting urban air pollution using deep learning Deevesh Chaudhary, Prashant Vats, Shailender Vats, Saneh Lata Yadav, Avani Sharma Scientific Reports, 2026 Accurate prediction of urban air quality is vital for protecting public health and the environment. The current challenges in air quality prediction models include noisy data, missing data, interactions of pollutants, temporal and spatial variations, external variables, lack of generalization, and real-time prediction. To overcome these challenges, a hybrid bio-inspired model for predicting urban air pollution using deep learning (AQP-SAPINN-HMRFO) is proposed. The input data is obtained from the Global Urban Air Quality Index dataset. The data is preprocessed with Implicit Bulk Surface Filtering (IBSF) to normalize the data and treat missing values to provide high-quality input data. The Quadratic-Phase Wave Packet Transform (QPWPT) is used to extract relevant features such as concentrations of pollutants, interactions between pollutants, and past concentrations of pollutants. Air quality forecasting is carried out by using a Self-Adaptive Physics-Informed Neural Network (SAPINN) that predicts concentrations of five major air pollutants like Particulate Matter $$\text {PM}_{2.5}$$, Carbon Monoxide (CO), Nitrogen Dioxide ($$\text {NO}_2$$), Ozone ($$\text {O}_3$$), and Sulfur Dioxide ($$\text {SO}_2$$), along with meteorological factors like temperature, wind speed, and humidity at various locations. The Hierarchical Manta Ray Foraging Optimization (HMRFO) technique is used to optimize the weight parameters of SAPINN to improve the accuracy of the model. The AQP-SAPINN-HMRFO model is a combination of SAPINN and HMRFO techniques. This model is capable of handling the interactions and gaps of the pollutants effectively. The proposed method is implemented in Python and the experiments demonstrate that AQP-SAPINN-HMRFO achieves 99% accuracy. This is a significant improvement over existing approaches and indicates its potential for real-time applications in urban air quality monitoring, environmental management, and strategic urban planning.
Bio-optimized complex valued spatiotemporal GNN for herbal species classification Prashant Vats, Shailender Vats, Avani Sharma, Saneh Lata Yadav, Deevesh Chaudhary Scientific Reports, 2026 Herbs have long been integral to various health and medicinal benefits. Identifying the correct herb species from thousands of diverse options is a laborious and time-consuming process. To address this issue, an automated computer vision system that reduces the traditional labor-intensive work of herbal species classification is needed. In this paper, we propose a novel method for automated herb classification via a complex-valued spatiotemporal graph convolutional neural network (AHC-CVSTGCN) with hierarchical manta ray foraging optimization. The objective of our research work is to develop a robust, effective, and optimized classification model driven by graph neural networks on a diverse array of morphological features of various herbal leaves. Input images are collected from FLAVIA and the medical leaf dataset. The images are first preprocessed utilizing Multiple Local Particle Filter (MLPF) to remove background noise and enhance quality, and then Revised Tunable Q-Factor Wavelet Transform (RQFWT) extracts relevant features such as shape, color, and texture. Finally, CVSTGCN classifies the images, with HMRFO optimization applied to further improve accuracy. Our proposed approach bridges the gaps in the classification of various herbal species, empowering medicine practitioners to make informed decisions. Experimental evaluation demonstrated that our approach significantly outperforms existing methods by achieving 99.40% high accuracy, 99.11% high precision, and 99.12% high recall. By contributing a reliable and effective solution for automated herbal species classification, this work presents a crucial paradigm shift for medicinal plant science and health care practitioners.
Artificial Intelligence-Enhanced Construction of Landslide-Resistant Support Infrastructure Using Heterogeneous Composite Nanomaterials: A Computational Algorithm Innovative Development International Journal of Intelligent Systems and Applications in Engineering, 2024
Internet of Things: A literature review Naved Alam, Prashant Vats, Neha Kashyap 2017 Recent Developments in Control Automation and Power Engineering Rdcape 2017, 2018
A literature review of Bee Colony optimization algorithms Rishabh Gulati, Prashant Vats Proceedings of the International Conference on Innovative Applications of Computational Intelligence on Power Energy and Controls with their Impact on Humanity Cipech 2014, 2014
A hybrid deep learning model with adaptive feature fusion for automated rice leaf disease detection and classification SK Upadhyay, R Prasad, Vikas, P Vats Scientific Reports , 2026 2026
A hybrid bio-inspired model for predicting urban air pollution using deep learning D Chaudhary, P Vats, S Vats, SL Yadav, A Sharma Scientific Reports , 2026 2026
Bio-optimized complex valued spatiotemporal GNN for herbal species classification P Vats, S Vats, A Sharma, SL Yadav, D Chaudhary Scientific Reports , 2026 2026
Early detection of mental health disorders using machine learning models: An analysis based on behavioral and voice data P Vats, TK Tak, K Upreti, S Mahajan, PR Kshirsagar, GM Upadhyay Computers and Electrical Engineering 132, 110996 , 2026 2026
Towards Smarter Diagnosis: A Survey of CNN-Based Hybrid Models in Breast Cancer A Agarwal, M Jangid, P Vats Information Systems for Intelligent Systems: Proceedings of ISBM 2025 … , 2026 2026 Citations: 1
Systems for detecting intruders in Internet of Things environments using the cloud: A survey A Kaur, RK Tyagi, S Sinha, P Vats Emerging Trends in Industrial Engineering and Management, 11-38 , 2026 2026
Deep Learning for Anomaly Detection in Satellite Imagery: Predicting Emerging Military Activities AK Saini, P Agarwal, Anu, GM Upadhyay, P Vats, A Kumar International Conference on Information and Communication Technology for … , 2025 2025
Accelerating Drug Repurposing with AI: A Case Study of Existing Drugs AK Saini, D Bandil, R Dave, K Dubey, P Vats 2025 2nd International Conference on Artificial Intelligence for Innovations … , 2025 2025
Augmented 3D ResUNETR: Combining residual learning and transformer encoding with multi-scale feature extraction for 3D medical image segmentation AK Jayswal, SP Singh, S Mishra, P Vats, K Kaur, AK Dubey Biomedical Signal Processing and Control 110, 108235 , 2025 2025 Citations: 4
Analysis as a Catalyst for Healthcare A Arora, N Tomer, V Soni, N Arora, AK Gupta, LM George, R Kaur, P Vats Smart Trends in Computing and Communications: Proceedings of SmartCom 2025 … , 2025 2025
Time Series Analysis for Stock Market Prediction: Techniques, Challenges R Kaur, N Arora, N Tomer, P Vats Smart Trends in Computing and Communications: Proceedings of SmartCom 2025 … , 2025 2025
Towards Smarter Diagnosis: A Survey of CNN-Based Hybrid Models in Breast Cancer Detection A Agarwal, M Jangid, P Vats World Conference on Information Systems for Business Management, 9-22 , 2025 2025
Enhancing key distribution via discrete mathematical structures in cryptosystems PVLR Govind Murari Upadhyay, Surabhi Shanker, Vinit Kumar, Vishal Journal of Discrete Mathematical Sciences and Cryptography 28 (6), 2515–2526 , 2025 2025
The Role of Digital Marketing Analytics in Enhancing Passive Income from E-Commerce Platforms A Arora, V Soni, M Sharma, P Kulhari, P Vats International conference on WorldS4, 1-11 , 2025 2025
Harnessing Predictive Analytics R Kaur, N Tomer, V Soni, P Vats ICT: Applications and Social Interfaces: Proceedings of ICTCS 2024, Volume 2 … , 2025 2025
Combinatorial algebra and cryptographic graph structures for cluster-based hybrid intrusion detection in IoT networks SKPV Ashok Kumar Saini, Manoj Wadhwa, Ranjeeta Kaur Popli, Madan Lal Saini Journal of Discrete Mathematical Sciences and Cryptography 25 (8), 3111–3120 , 2025 2025
A PKI-integrated cryptographic framework for deepfake detection via facial micro-expression analysis Journal of Discrete Mathematical Sciences and Cryptography 28 (8), 3101–3109 , 2025 2025
Secure key exchange and digital signatures via elliptic curves and discrete mathematical principles Journal of Discrete Mathematical Sciences and Cryptography 28 (8), 3081–3089 , 2025 2025
A private key cryptographic framework for preventing replay attacks and digital signature verification in securing blockchain networks SKGAKS Prashant Vats, Sandeep Kumar Budhani, Sandeep Kumar Budhani, Devesh ... Journal of Discrete Mathematical Sciences and Cryptography 28 (8), 3081–3089 , 2025 2025
Algebraic graph models for secure distributed networks and cryptographic systems PV Surbhi Sharma, Preeti Rathi, Ranjeeta Kaur Popli, Sushama Journal of Discrete Mathematical Sciences and Cryptography 28 (8), 3071–3080 , 2025 2025
MOST CITED SCHOLAR PUBLICATIONS
Experimental analysis of geopolymer concrete: a sustainable and economic concrete using the cost estimation model M Verma, K Upreti, P Vats, S Singh, P Singh, N Dev, D Kumar Mishra, ... Advances in materials science and engineering 2022 (1), 7488254 , 2022 2022 Citations: 97
Internet of Things: A literature review N Alam, P Vats, N Kashyap 2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE … , 2017 2017 Citations: 56
A comprehensive literature review of penetration testing & its applications P Vats, M Mandot, A Gosain 2020 8th International Conference on Reliability, Infocom Technologies and … , 2020 2020 Citations: 52
Analysis of current trends, advances and challenges of machine learning (Ml) and knowledge extraction: from Ml to explainable AI NP Krishnam, MS Ashraf, BR Rajagopal, P Vats, DSK Chakravarthy, ... Industry Qualifications The Institute of Administrative Management UK 58, 54-62 , 2022 2022 Citations: 50
An IoHT system utilizing smart contracts for machine learning-based authentication K Upreti, P Vats, G Borkhade, RD Raut, S Hundekari, J Parashar 2023 International Conference on Emerging Trends in Networks and Computer … , 2023 2023 Citations: 40
Deep learning and machine intelligence for operational management of strategic planning AK Sharma, P Singh, P Vats, D Jain Proceedings of Third International Conference on Computing, Communications … , 2022 2022 Citations: 38
A sustainable green approach to the virtualized environment in cloud computing A Gupta, P Singh, D Jain, AK Sharma, P Vats, VP Sharma Smart Trends in Computing and Communications: Proceedings of SmartCom 2022 … , 2022 2022 Citations: 31
A blockchain-based framework for IoT based secure identity management S Varshney, P Vats, S Choudhary, D Singh 2022 2nd international conference on innovative practices in technology and … , 2022 2022 Citations: 31
Robotics and automation in industry 4.0 J Pandey, S Das, P Vats The implications of cloud computing, IoT, and wearable robotics for smart … , 2024 2024 Citations: 30
Literature survey for IoT-based smart home automation: a comparative analysis R Kaur, P Vats, M Mandot, SS Biswas, R Garg 2021 9th International Conference on Reliability, Infocom Technologies and … , 2021 2021 Citations: 30
Towards intelligent governance: the role of AI in policymaking and decision support for E-governance A Arora, M Gupta, S Mehmi, T Khanna, G Chopra, R Kaur, P Vats World Conference on Information Systems for Business Management, 229-240 , 2023 2023 Citations: 29
Big data analytics in real time for enterprise applications to produce useful intelligence P Vats, SS Biswas Data wrangling: concepts, applications and tools, 187-211 , 2023 2023 Citations: 27
A comprehensive framework for the IoT-based smart home automation using Blynk F Doja, R Batra, S Tayal, P Vats, SS Biswas Information and Communication Technology for Competitive Strategies (ICTCS … , 2022 2022 Citations: 27
Cloud-based patient health information exchange system using blockchain technology P Singh, D Jain, AK Sharma, A Jain, P Vats Information and Communication Technology for Competitive Strategies (ICTCS … , 2022 2022 Citations: 26
A comprehensive analysis of mixed reality visual displays in context of its applicability in IoT S Kaushik, M Phogat, AK Sharma, N Kumar, P Vats, SS Biswas 2022 international mobile and embedded technology conference (MECON), 101-107 , 2022 2022 Citations: 26
The Block Chain Technology to Protect Data Access Using Intelligent Contracts Mechanism Security Framework for 5g Networks PR Kapula, JG Jeslin, G Hosamani, P Vats, CJ Shelke, SK Shukla 2022 2nd International Conference on Advance Computing and Innovative … , 2022 2022 Citations: 25
A comprehensive framework for IoT-based data protection in blockchain system D Jain, AK Sharma, P Singh, AK Pandey, P Vats Information and Communication Technology for Competitive Strategies (ICTCS … , 2022 2022 Citations: 25
A comprehensive study on social network analysis for digital platforms to examine and solve the behavioral patterns of everyday routines A Arora, M Chaudhary, R Kaur, R Batra, P Vats ICT Systems and Sustainability: Proceedings of ICT4SD 2022, 13-21 , 2022 2022 Citations: 24
A hybrid approach for retrieving geographic information in wireless environment using indexing technique P Vats, Z Aalam, S kaur, A kaur, N Gehlot ICT Analysis and Applications, 145-155 , 2022 2022 Citations: 24
Data-driven decision support systems in e-governance: leveraging ai for policymaking A Arora, P Vats, N Tomer, R Kaur, AK Saini, SS Shekhawat, M Roopak International Conference on Artificial Intelligence on Textile and Apparel … , 2023 2023 Citations: 23
