Data Science and Applications

Dr. Satyasai Jagannath Nanda is an associate professor in the Dept. of Electronics and Communication Engg., Malaviya National Institute of Technology Jaipur since Dec. 2023. He joined as an assistant professor at MNIT Jaipur in June 2013. He received the PhD degree from School of Electrical Sciences, IIT Bhubaneswar in 2013 and M. Tech. degree from Dept. of Electronics and Communication Engg., NIT Rourkela in 2009. He received the B.E. degree in Electronics and Telecommunication Engg. from Institute of Technical Education and Research (ITER), Bhubaneswar in the year 2006. He was the recipient of Canadian Research Fellowship- GSEP, from Dept. of Foreign Affairs and Intern. Trade (DFAIT), Govt. of Canada for the year 2009-10. He was awarded Best PhD thesis award at SocProS 2015 by IIT Roorkee.Prof. Rajendra Prasad Yadav is currently working as a Professor-HAG in the Department of Electronics and Communication Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, India. He has more than four decades of teaching and research experience. He was instrumental in starting new B.Tech, M.Tech courses and formulating PhD Ordinances for starting research work in Rajasthan Technical University (RTU) Kota and other affiliated Engg colleges as Vice Chancellor of the University. He has served as HOD of Electronics and Comm. Engg., President Sports and Library, Hostel warden, Dean Student Affairs at MNIT Jaipur. He was also the Chief Vigilance Officer of MNIT Jaipur. Prof. Yadav received the PhD degree from MREC Jaipur and M.Tech degree from IIT Delhi.Dr Mukesh Prasad is a Senior Lecturer at School of Computer Science in the Faculty of Engineering and IT at UTS who has made substantial contributions to the fields of machine learning, artificial intelligence and the internet of things. Mukesh’s research interests include also big data, computer vision, brain computer interface, and evolutionary computation. He is working also in the evolving and increasingly important field of image processing, data analytics and edge computing, which promise to pave the way for the evolution of new applications and services in healthcare, biomedical, agriculture, smart cities, education, marketing and finance. His research has appeared in numerous prestigious journals, including IEEE/ACM Transactions and conferences, he has written more than 100 research papers.Prof. Mukesh Saraswat is a Professor and Associate Dean (Innovation) at Jaypee Institute of Information Technology (JIIT), Noida, India. Prof. Saraswat obtained his Ph.D. in Computer Science & Engineering from ABV-IIITM Gwalior, India. He has more than 20 years of teaching and research experience. He has guided 04 Ph.D. students and presently guiding 04 Ph.D. students. He has published more than 80 journal and conference papers in image processing, pattern recognition, and soft computing. He was part of a successfully completed project funded by SERB, New Delhi on image analysis. He has been an active member of many organizing committees for various conferences and workshops. He is also a faculty in charge of Jaypee Youth Club at JIIT, Noida. He is also a guest editor of the Array, Journal of Swarm Intelligence, SN Computer Science, and Journal of Intelligent Engineering Informatics. He is one of the General Chairs of the International Conference on Data Science and Applications. He is also an Advisory Board Member of the Journal MethodsX. He is also a series editor of the SCRS Book Series on Computing and Intelligent Systems (CIS). He is an active member of ACM, CSI, and SCRS Professional Bodies.

• Machine Learning–Based Prediction of MRP Process Runtime and Memory Usage for Scalable Business Operations.- Crop Yield Prediction of Indian States based on Machine Learning and Feature Engineering.- Heart Disease Prediction using Machine Learning: A Comparative Approach on CHSLB and Cleveland Datasets with Advanced Modeling Techniques.- Extensive Analysis of Electric Vehicles: Battery Management Systems, Machine Learning Strategies to Prevent Thermal Runaway for Improved Safety and Performance.- Analysis of Security Vulnerabilities in OSS For Predicting Diabetes using OWASP ZAP.- A SEM–Neural Network Approach to Predict Customers Intention to Purchase Battery Electric Vehicles in the Bangalore.- Automating Court Judgement Prediction and Explanation for Indian Legal Cases.- Deep Learning-Driven Real Time Video Summarization with Temporal Modeling and Attention Mechanism.- Integrated Monitoring System for Railway Wagon Coal Load Tracking: Sensor-Based Detection and Real-Time Notification.- Emotion Recognition from ECG Signals using Deep Neural Networks.- Brain Tumor Survival Prediction using MRI Segmentation and Autoencoder Features.- Analysis of Conventional vs Machine Learning Models for Decision-Making in Logistics based on Uncertainty Quantification.