Machine Intelligence Techniques for Data Analysis and Signal Processing

On Diverse and Serendipitous item Recommendation: A Reinforced Similarity and Multi-Objective Optimization based Composite Recommendation Framework.- Comparative Analysis of Node Dependent and Node Independent Graph Matrices for Brain Connectivity.- Facial Expression Recognition from low resolution facial segments using Pre-trained networks.- Design and Analysis of Quad Element UWB MIMO Antenna with Mutual Coupling Reduction Techniques.- Enhancing Agriculture Outcome with Multiple Crop Recommendations Using Sequential Forword Feature Selection.- Kernel Level Pruning for CNN.

Dilip Singh Sisodia is an Associate Professor and Head at the Department of Computer Science Engineering of National Institute of Technology Raipur. Dr. Sisodia contributed over 100 high-impact articles in reputed journals, conference proceedings, and edited volumes. He also edited Scopus indexed research book volumes published by Springer Nature and IGI Global. Dr. Sisodia was included in the World Ranking of Top 2% Scientists/researchers in 2022 by a study of Scientists from Stanford University USA and Published by Elsevier B.V. So far he has supervised four Ph.D. thesis, eight M.Tech. dissertations and more than 50 B.Tech. projects. He is a Senior Member of IEEE and ACM. He received a Ph.D. degree in computer science and engineering from the National Institute of Technology Raipur, India. He earned his M.Tech. and B.E. degrees, respectively, in information technology (with specialization in artificial intelligence) and computer science and engineering from the Rajiv Gandhi Technological University, Bhopal, India. His research interests include the applications of machine learning/soft computing techniques, artificial intelligence, biomedical signal, and image processing.

Lalit Garg is a Senior Lecturer in the Department of Computer Information Systems at the University of Malta, Malta, and an Honorary Lecturer at the University of Liverpool, UK. He has been a Researcher at the Nanyang Technological University, Singapore, and Ulster University, UK, has supervised 200+ Master's dissertations, two DBA, and two Ph.D. theses, and published 120+ high-impact publications in refereed journals/conferences/books, five edited books, and 20 patents. His research interests are business intelligence, machine learning, data science, deep learning, cloud computing, mobile computing, the Internet of Things (IoT), information systems, management science, and their applications mainly in healthcare and medical domains.


Ram Bilas Pachori received a B.E. degree