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 Ph.D. 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 Ph.D. 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 Ph.D. ordinances for starting research work in Rajasthan Technical University (RTU) Kota and other affiliated Engg. colleges as the 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 Ph.D. 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 health care, 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.

• Design and Evaluation of a Real-Time Web Application for Air Quality Monitoring: Toward User-Centered Environmental Information Systems in Indonesia.- Detection of DDoS Attacks in SDN using Feature Optimization and FNet-Based Transformer Models.- Deep Learning-Based Gujarati Image Caption Generator using ResNet18 and GRU.- Evaluating Vision Transformer Variants and Hybrid Quantum-Classical Models for Face Forgery Detection.- The Impact of Large Language Models in Healthcare: A Systematic Review of AI Applications.- Wearable Textile Antennas on Jeans Substrate for Biomedical Applications.- Optimising Baseline Random Forest model with Hybrid EDBO and MadDE: A Hybrid Approach for Early Cardiovascular Disease Detection.- Multi-Label Object Detection using Multi-model‬ ‭ R-CNN.- Lightweight EmergencyNet for Aerial Scene Classification.- Advances in Feature Selection for Visual Art Style and Artist Identification.