VISHAL DUTT

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

Scopus Publications

Data Preparation, Collecting, Cleaning, and Managing Datasets in Generative AI
Vishal Dutt, Sartajvir Singh, and Ganesh Kumar Sethi
CRC Press



AI-Based framework for real-time snow-cover analysis over western himalayas using scatterometer dataset
Vishal Dutt, Ganesh Kumar Sethi, and Sartajvir Singh
Elsevier



Development of Snow Cover Product from Scatterometer Using Google Earth Engine
Vishal Dutt, Sartajvir Singh, and Ganesh Kumar Sethi
IEEE



Comparative analysis of C-Band and Ku-band-based scatterometers
Vishal Dutt, Ganesh Kumar Sethi, and Sartajvir Singh
Elsevier



Detection of Snow/Ice over Western Himalayas Using Scatterometer with Google Earth Engine
Reet Kamal Tiwari, Vishakha Sood, Sartajvir Singh, and Vishal Dutt
IEEE



Preface




Multimodal Data Fusion for Bioinformatics Artificial Intelligence
Wiley



Preface




Secure Energy Optimization: Leveraging Internet of Things and Artificial Intelligence for Enhanced Efficiency
Wiley



Preface




Federated learning and privacy-preserving in healthcare AI
IGI Global



Preface




Applying machine learning techniques to bioinformatics: Few-shot and zero-shot methods
IGI Global



Contribution of E-Waste Management in Green Computing
Shweta Sharma and Vishal Dutt
Wiley



AN APPROACH FOR THE IMPLEMENTATION OF MULTILEVEL TECHNIQUE OF GA FOR CARDIAC DISEASE DETECTION
Neeraj Bhargava, Ritu Bhargava, Kapil Chauhan, Pramod Singh Rathore, and Vishal Dutt
Apple Academic Press



Advanced Real-Time Simulation Framework for the Physical Interaction Dynamics of Production Lines Leveraging Digital Twin Paradigms
Neha Bhati, Narayan Vyas, Vishal Dutt, Ronak Duggar, and Aradhya Pokhriyal
Wiley



Preface




Sustainable Management of Electronic Waste
Wiley



Preface




Quantum innovations at the nexus of biomedical intelligence




Preface




Innovations in machine learning and IoT for water management
IGI Global



IoT based arrhythmia classification using the enhanced hunt optimization-based deep learning
Abhishek Kumar, Swarn Avinash Kumar, Vishal Dutt, S. Shitharth, and Esha Tripathi
Wiley



Advancing Precision Agriculture: Leveraging YOLOv8 for Robust Deep Learning Enabled Crop Diseases Detection
Narayan Vyas and Vishal Dutt
IEEE
Precision agriculture relies on the early detection and isolation of crop diseases, and this research details how the You Only Look Once, Version 8 (YOLOv8) algorithm was used for the PlantVillage dataset. This research looks at how Deep Learning (DL) and Computer Vision (CV) could streamline and improve the diagnostic process, a problem with conventional disease detection approaches. The YOLOv8 model is trained and evaluated using the PlantVillage dataset, which consists of high-resolution photos encompassing different classes of crops and diseases. It is found that YOLOv8 outperformed other popular Machine Learning (ML) models in identifying agricultural diseases with 95% accuracy, 90% precision, 95% recall, 92% F1 score, and 90% specificity. Parameter optimization, advanced network architectures, and integration of the Internet of Things (IoT) and drones for real-time disease monitoring are just some of the future research directions proposed in this study, along with discussions of the difficulties posed by data availability, computational complexity, and resource requirements. YOLOv8's successful application to the PlantVillage dataset demonstrates its potential to automate and improve crop disease diagnosis, leading to more effective and environmentally friendly farming methods.


Pre-Trained Deep Learning-Based Approaches for Eye Disease Detection
Pankaj Kumar, Sudhir Bhandari, and Vishal Dutt
IEEE
This study primarily examines how well four pretrained deep learning models perform in identifying eye disorders using four metrics we developed: recall, precision, accuracy, and F1 Score. With the help of universal custom layers, the models are adjusted, and the outcomes are examined. The study then suggests an ensemble method that uses majority voting to combine the probabilistic outputs of the top-performing models. The suggested methodology outperforms state-of-the-art algorithms in experiments using a publicly available dataset, with average values for Recall, Precision, Accuracy, and F1 Score of 81.25%, 83.68%, 95.17%, and 79.12%, respectively. The work shows how well-trained deep learning models can identify eye illnesses and have the potential to improve public health, especially in mass screening programs.

RECENT SCHOLAR PUBLICATIONS

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.