Earned a Gold Medal for academic excellence while obtaining my MCA degree from MDS University, Ajmer, Rajasthan, India. Currently, I am employed Technical trainer at the esteemed Department of Computer Science & Engineering, located at Chandigarh University, Mohali, Punjab, India. I am a dedicated and experienced professional trainer, specializing in Research and Development. I am a dedicated researcher with extensive experience in Machine Learning, Deep Learning, and utilizing data science to drive transformative advancements. Additionally, I have been engaged in research on AI-based remote sensing for the past year. With a passion for education and a commitment to promoting innovation. As a core and founding member of various research actively participated in shaping the research culture within the departments. I have a total Academic teaching experience of more than 10 years. I have numerous publications in reputed, SCI, Scopus, Springer Journals & Conferences, peer-reviewed Nation
EDUCATION
MCA (Gold Medalist) | SMIEEE
RESEARCH, TEACHING, or OTHER INTERESTS
Artificial Intelligence, Computers in Earth Sciences, Computer Science Applications, General Environmental Science
62
Scopus Publications
1659
Scholar Citations
25
Scholar h-index
35
Scholar i10-index
Scopus Publications
Data Preparation, Collecting, Cleaning, and Managing Datasets in Generative AI Vishal Dutt, Sartajvir Singh, Ganesh Kumar Sethi Generative AI for Remote Sensing of the Environment Algorithms and Applications, 2026 The importance of high-quality, diverse, and well-structured data undergirds model performance, fairness, and reliability by detailing collection, cleaning, and management practices. Different sources of data, including public sets, proprietary records, web scraping, and crowdsourcing, are reviewed alongside ethics such as consent, privacy, and mitigating bias. The chapter elaborates on cleaning methods such as normalization, outlier discarding, and modality-specific preprocessing for text, images, and audio with recourse to popular tools such as Pandas, OpenCV, NLTK, and Librosa. Recommendations for dataset structuring, versioning, scalability, security, and automation of the workflow are surveyed to ensure sustainable management. Typical pitfalls, such as bias, scalability, scarcity in narrow fields, and quality degradation during training, are complemented by pragmatic solutions. Practical case studies highlight the preparation of Wikipedia text for language generators, curated face datasets for GANs, and multimodal datasets for creative tools. The chapter concludes with future directions, including the incorporation of automation through AutoML, synthetic data integration, federated learning, and adherence to fast-evolving regulations. Overall, the emphasis is on the importance of disciplined, repeated preparation of data, which is as essential as the architecture of the model for tapping the full potential of generative AI. It encourages practitioners to insist on quality and governance from the beginning.
Development of Snow Cover Product from Scatterometer Using Google Earth Engine Vishal Dutt, Sartajvir Singh, Ganesh Kumar Sethi International Geoscience and Remote Sensing Symposium IGARSS, 2025 The Western Himalayas are an important source of fresh water that impact agriculture, hydroelectricity production, and natural disaster management and the variability of snow over Himalayas may affect these domains. Most the traditional approaches to remote sensing can't work properly either because of persistent cloud cover or give poor performance while examining changing snow-cover areas. Hence, this study has attempted the development of SCATSAT-1 scatterometer data integration with the Google Earth Engine and neural network for the binary classification of the snow/non-snow zones. The proposed approach achieved 97% of accuracy, validated through highly correlated MODIS datasets. Thus, the proposed approach provides an efficient framework for the highly accurate mapping of snow cover areas that may facilitate better resource management and disaster mitigation strategies in high-altitude, snow-fed regions.
Detection of Snow/Ice over Western Himalayas Using Scatterometer with Google Earth Engine Reet Kamal Tiwari, Vishakha Sood, Sartajvir Singh, Vishal Dutt International Geoscience and Remote Sensing Symposium IGARSS, 2025 A scatterometer is one of the active microwave sensors utilised in a variety of applications over land and nonland such as sea-ice and oceanography. Since the first launch of the scatterometer in 1976, a variety of scatterometers were launched by the different space agencies especially to observe the wind direction and wind speed. But with the advancement in technical specifications and algorithms various applications were also explored over the land surface such as in agriculture, water hydrology, snow-ice and snow water equivalent due to its nature of the sensitivity towards the water contents within the land in the form of snow or soil. In this article, the scatterometer data has been processed using Google Earth Engine (GEE) over western Himalayas. The SCATSAT-1 data has been utilized to detect the snow/ice. Two classifiers i.e., random forest (RF) and support vector machine (SVM) have been tested for SCATSAT-1 dataset. The experiment results confirm the effectiveness of each classifier in the detection of snow/ice cover maps over western Himalayas. This study is beneficial for the accurate estimation of snow/ice at a larger scale along with decadal record of the scatterometer dataset.
Preface Multimodal Data Fusion for Bioinformatics Artificial Intelligence, 2025
Multimodal Data Fusion for Bioinformatics Artificial Intelligence Multimodal Data Fusion for Bioinformatics Artificial Intelligence, 2025 Multimodal Data Fusion for Bioinformatics Artificial Intelligence is a must-have for anyone interested in the intersection of AI and bioinformatics, as it delves into innovative data fusion methods and their applications in ‘omics’ research while addressing the ethical implications and future developments shaping the field today. Multimodal Data Fusion for Bioinformatics Artificial Intelligence is an indispensable resource for those exploring how cutting-edge data fusion methods interact with the rapidly developing field of bioinformatics. Beginning with the basics of integrating different data types, this book delves into the use of AI for processing and understanding complex “omics” data, ranging from genomics to metabolomics. The revolutionary potential of AI techniques in bioinformatics is thoroughly explored, including the use of neural networks, graph-based algorithms, single-cell RNA sequencing, and other cutting-edge topics. The second half of the book focuses on the ethical and practical implications of using AI in bioinformatics. The tangible benefits of these technologies in healthcare and research are highlighted in chapters devoted to precision medicine, drug development, and biomedical literature. The book addresses a wide range of ethical concerns, from data privacy to model interpretability, providing readers with a well-rounded education on the subject. Finally, the book explores forward-looking developments such as quantum computing and augmented reality in bioinformatics AI. This comprehensive resource offers a bird’s-eye view of the intersection of AI, data fusion, and bioinformatics, catering to readers of all experience levels.
Preface Secure Energy Optimization Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency, 2025
Secure Energy Optimization: Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency Secure Energy Optimization Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency, 2025 Secure Energy Optimization: Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency is essential for anyone looking to navigate the transformative landscape of energy management, as it expertly combines the principles of IoT and AI with real-world case studies to provide actionable insights for achieving sustainable and efficient energy optimization. Energy is rapidly changing, with an emphasis on sustainable and efficient energy use. In this context, the combination of Internet of Things (IoT) and Artificial Intelligence (AI) technologies has emerged as a potent technique for optimising energy use, improving efficiency, and enhancing overall energy security. Secure Energy Optimization: Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency provides a comprehensive review of how IoT and AI can be used to accomplish safe energy optimisation. Readers will gain an understanding of the underlying principles of IoT and AI, as well as their applications in energy efficiency and the problems and hazards related to their adoption. They will investigate the successful integration of IoT and AI technologies in energy management systems, smart grids, and renewable energy sources using real-world case studies and examples. By bringing together theoretical notions, cutting-edge research, and practical examples, this book bridges the gap between theory and implementation.
Preface Federated Learning and Privacy Preserving in Healthcare AI, 2024
Improved Healthcare System with Quantum Computing Sriramakrishnan Chandrasekaran, Rashmi Agrawal, Vishal Dutt, Narayan Vyas 2023 International Conference on Artificial Intelligence and Smart Communication Aisc 2023, 2023
Graph technology: a detailed study of trending techniques and technologies of graph analytics Demystifying Graph Data Science Graph Algorithms Analytics Methods Platforms Databases and Use Cases, 2022
Toward graph data science Demystifying Graph Data Science Graph Algorithms Analytics Methods Platforms Databases and Use Cases, 2022
Math Optimization for Artificial Intelligence: Heuristic and Metaheuristic Methods for Robotics and Machine Learning U Kumar Lilhore, V Dutt, TA Kumar, M Margala, K Raahemifar De Gruyter , 2025 2025 Citations: 6
Multimodal data fusion for bioinformatics artificial intelligence UK Lilhore, A Kumar, N Vyas, S Simaiya, V Dutt John Wiley & Sons , 2025 2025 Citations: 9
Quantum machine learning algorithms: A comprehensive review J Singh, A Chugh, SS Chauhan, AK Singh, UK Lilhore, S Dalal, V Dutt, ... Industrial Quantum Computing: Algorithms, Blockchains, Industry 4.0, 37-52 , 2025 2025 Citations: 1
Industrial Quantum Computing: Algorithms, Blockchains, Industry 4.0 UK Lilhore, S Dalal, V Dutt, M Radulescu Walter de Gruyter GmbH & Co KG , 2024 2024 Citations: 6
Advanced Real‐Time Simulation Framework for the Physical Interaction Dynamics of Production Lines Leveraging Digital Twin Paradigms N Bhati, N Vyas, V Dutt, R Duggar, A Pokhriyal Simulation Techniques of Digital Twin in Real‐Time Applications: Design … , 2024 2024 Citations: 2
Federated learning and privacy-preserving in healthcare AI UK Lilhore, S Simaiya, M Poongodi, V Dutt IGI Global , 2024 2024 Citations: 11
Evaluation of the catalytic and antioxidant activity of in situ green synthesized graphene-gold nanocomposite S Akhil, PJ Kumar, VSS Mosali, VGV Dutt, S Kasturi, B Mullamuri, ... Carbon Letters 34 (4), 1207-1218 , 2024 2024 Citations: 12
Applying Machine Learning Techniques to Bioinformatics: Few-Shot and Zero-Shot Methods: Few-Shot and Zero-Shot Methods UK Lilhore, A Kumar, S Simaiya, N Vyas, V Dutt IGI Global , 2024 2024 Citations: 5
Contribution of E‐waste management in green computing S Sharma, V Dutt Sustainable management of electronic waste, 397-412 , 2024 2024 Citations: 4
Sustainable management of electronic waste A Kumar, PS Rathore, AK Dubey, AL Srivastav, V Dutt, TA Kumar John Wiley & Sons , 2024 2024 Citations: 21
An Approach for the Implementation of Multilevel Technique of Ga for Cardiac Disease Detection N Bhargava, R Bhargava, K Chauhan, PS Rathore, V Dutt Handbook of Research on Artificial Intelligence and Soft Computing … , 2024 2024
Quantum Innovations at the Nexus of Biomedical Intelligence V Dutt, A Kumar, S Ahuja, A Baliyan, N Vyas IGI Global , 2023 2023 Citations: 3
Innovations in machine learning and iot for water management A Kumar, AL Srivastav, AK Dubey, V Dutt, N Vyas IGI Global , 2023 2023 Citations: 9
E-commerce: the enhancement with the integration of AR and VR R Singh, P Sharma, V Dutt 2023 International Conference on Advances in Computation, Communication and … , 2023 2023 Citations: 8
Advancing precision agriculture: Leveraging YOLOv8 for robust deep learning enabled crop diseases detection N Vyas, V Dutt 2023 International Conference on Integration of Computational Intelligent … , 2023 2023 Citations: 7
AI-driven drug discovery: unravelling the potential of generative adversarial networks (GANs) in pharmaceutical research SR Burri, MY Diallo, L Sharma, V Dutt 2023 3rd International Conference on Technological Advancements in … , 2023 2023 Citations: 7
The rise of virtual health assistants: Chatbot-based healthcare support and counseling using recurrent neural networks (RNNs) SR Burri, VV Ghorpade, V Dutt, K Lipi 2023 3rd International Conference on Technological Advancements in … , 2023 2023 Citations: 9
Real-time traffic analysis and driver safety enhancement via IoT and computer vision with high-resolution project lamps for intelligent road illumination H Dhiman, N Vyas, A Pagrotra, V Dutt 2023 1st International Conference on Circuits, Power and Intelligent Systems … , 2023 2023 Citations: 7
Efficient privacy preserving lightweight cryptography for multi-hop clustering in internet of vehicles network A Kumar, AK Dubey, S Ahuja, V Dutt 2023 Citations: 3
Enhancing Land-Based Robotics Through the Development of Remotely Operated Vehicles for Military, Rescue and Industrial Applications A Pagrotra, N Vyas, H Dhiman, V Dutt 2023 3rd Asian Conference on Innovation in Technology (ASIANCON), 1-6 , 2023 2023 Citations: 3
MOST CITED SCHOLAR PUBLICATIONS
Machine learning implementation on medical domain to identify disease insights using TMS SM Sasubilli, A Kumar, V Dutt 2020 International Conference on Advances in Computing and Communication … , 2020 2020 Citations: 144
Multi model implementation on general medicine prediction with quantum neural networks SA Kumar, A Kumar, V Dutt, R Agrawal 2021 Third International Conference on Intelligent Communication … , 2021 2021 Citations: 124
Improving health care by help of internet of things and bigdata analytics and cloud computing SM Sasubilli, A Kumar, V Dutt 2020 International Conference on Advances in Computing and Communication … , 2020 2020 Citations: 107
IoT-based ECG monitoring for arrhythmia classification using Coyote Grey Wolf optimization-based deep learning CNN classifier A Kumar, SA Kumar, V Dutt, AK Dubey, V García-Díaz Biomedical Signal Processing and Control 76, 103638 , 2022 2022 Citations: 69
IoT based arrhythmia classification using the enhanced hunt optimization‐based deep learning A Kumar, SA Kumar, V Dutt, S Shitharth, E Tripathi Expert Systems 40 (7), e13298 , 2023 2023 Citations: 63
Self-health analysis with two step histogram based procedure using machine learning SA Kumar, H Kumar, V Dutt, H Soni 2021 Third International Conference on Intelligent Communication … , 2021 2021 Citations: 61
Exploring the impact of edge intelligence and IoT on healthcare: a comprehensive survey R Punugoti, V Dutt, A Anand, N Bhati 2023 International Conference on Sustainable Computing and Smart Systems … , 2023 2023 Citations: 59
A hybrid secure cloud platform maintenance based on improved attribute-based encryption strategies A Kumar, SA Kumar, V Dutt, AK Dubey, S Narang IJIMAI 8 (2), 150-157 , 2023 2023 Citations: 58
Big data approach for medical data classification: A review study S Boyapati, SR Swarna, V Dutt, N Vyas 2020 3rd international conference on intelligent sustainable systems (ICISS … , 2020 2020 Citations: 55
Dynamic information retrieval with chatbots: a review of artificial intelligence methodology V Dutt, SM Sasubilli, AE Yerrapati 2020 4th International Conference on Electronics, Communication and … , 2020 2020 Citations: 49
Student Sentiment Analysis Using Various Machine Learning Techniques S Chandrasekaran, V Dutt, N Vyas, R Kumar 2023 International Conference on Artificial Intelligence and Smart … , 2023 2023 Citations: 46
Retracted: Deep Learning in Dynamic Modeling of Medical Imaging: A Review Study SR Swarna, S Boyapati, V Dutt, K Bajaj 2020 3rd International Conference on Intelligent Sustainable Systems (ICISS … , 2020 2020 Citations: 46
A novel approach for anomaly detection in time-series data using generative adversarial networks R Raturi, A Kumar, N Vyas, V Dutt 2023 International Conference on Sustainable Computing and Smart Systems … , 2023 2023 Citations: 45
Improved healthcare system with quantum computing S Chandrasekaran, R Agrawal, V Dutt, N Vyas 2023 International Conference on Artificial Intelligence and Smart … , 2023 2023 Citations: 43
Multimodal Neuroimaging Data in Early Detection of Alzheimer's Disease: Exploring the Role of Ensemble Models and GAN Algorithm US Sekhar, N Vyas, V Dutt, A Kumar 2023 International Conference on Circuit Power and Computing Technologies … , 2023 2023 Citations: 39
Boosting the Accuracy of Cardiovascular Disease Prediction Through SMOTE R Punugoti, V Dutt, A Kumar, N Bhati 2023 International Conference on IoT, Communication and Automation … , 2023 2023 Citations: 38
Personalized cardiovascular disease risk prediction using random forest: an optimized approach VR Burugadda, V Dutt, N Vyas 2023 IEEE world conference on Applied Intelligence and Computing (AIC), 226-232 , 2023 2023 Citations: 34
Fuzzy KNN Implementation for Early Parkinson's Disease Prediction S Chandrasekaran, V Dutt, N Vyas, A Anand 2023 7th International Conference on Computing Methodologies and … , 2023 2023 Citations: 34
Drones in smart cities P Manju, D Pooja, V Dutt AI and IoT‐Based Intelligent Automation in Robotics, 205-228 , 2021 2021 Citations: 33
Covid-19 pandemic analysis using svm classifier: Machine learning in health domain SA Kumar, H Kumar, V Dutt, H Swarnkar Global Journal on Application of Data Science and Internet of Things 4 (1) , 2020 2020 Citations: 31
RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)
Conducted numerous research training workshops and seminars, focusing on advanced topics and techniques in the field of Computer Science and Engineering.
Developed and implemented training modules to enhance research skills and foster a culture of innovation among students and faculty members.
Mentored and guided students in their research projects, helping them explore new avenues and refine their methodologies.
Facilitated collaboration among research teams, fostering interdisciplinary research projects, and encouraging knowledge sharing.
Played a vital role in establishing research partnerships with industry and academia to enhance the research ecosystem at Chandigarh University.
Actively contributed to research publications, presenting papers at national and international conferences and journals.
Received the Outstanding Teaching Award for his contributions to the development and delivery of research-based contributions.
Conducted Seminars and workshops of GCP in various colleges and Universities.
Received consistently positive feedback from students in R & D training courses, with an average rating of 4.7 out of 5 for course content, delivery, and instructor expertise.
