Dr. Soumi Dutta is Associate Professor at Sister Nivedita University (SNU) at New Town, Kolkata, India. She has completed her Ph.D. (CST), IIEST, Shibpur. She received her B.Tech. (IT) and M.Tech. (CSE) securing 1st position (Gold Medalist), from MAKAUT. She is certified as Publons Academy Peer Reviewer, 2020, and Certified Microsoft Innovative Educator, 2020. Her research interests are data mining, information retrieval, online social media analysis, and image processing. She has published more than 40 conference and journal papers in Springer, IEEE, IGI Global, Taylor & Francis, etc. She is Peer Reviewer and TPC Member in different international journals. She is Active Member of several technical functional bodies such as ACM, IEEE, IFERP, MACUL, SDIWC, Internet Society, ICSES, ASR, AIDASCO, USERN, IRAN, and IAENG. She has published 8 patents and 1 copyright. Dr. Soumi Dutta has delivered 37 Keynote talks in different international conferences. Dr. Abhishek Bhattacharya is Associate Professor at Sister Nivedita University, India. He has completed his Ph.D. (CSE), BIT, Mesra. He is certified as Publons Academy Peer Reviewer, 2020. His research interests are data mining, cyber security, and mobile computing. He has published 55 conference and journal papers in Springer, IEEE, IGI Global, Taylor & Francis, etc. He has 3 book chapters in Taylor & Francis Group EAI. He is Peer Reviewer and TPC Member in different international journals. He was Editor in IEMIS 2020, IEMIS 2018, IEMIS 2022, ICIDA 2022, ICIDA 2023, CIIR 2023 and special issues in IJWLTT. He is Member of several technical functional bodies such as IEEE, IFERP, MACUL, SDIWC, Internet Society, ICSES, ASR, AIDASCO, USERN, IRAN, and IAENG. He has published 3 patents and 15 books.Dr. Pham is currently Assistant Professor in the Department of Computer Science, Sam Houston State University. His areas of expertise centered around data analytics, data visualizations, machine learning, and deep learning. He received his bachelor's from President University and master's from Politecnico di Milano, both with full scholarships. He then became Lecturer at FPT University for eight years before joining the Department of Computer Science from Texas Tech University under the President's strategic growth initiative in data science (3-year fellowship) for his Ph.D. As Research Assistant, he published one patent, various peer-reviewed journals, and conference papers. Dr. Pham also wrote an NSF I-Corps proposal and executed it as Entrepreneur Lead. As part of his research development, he won one best paper award, an award in VAST 2018 Mini-Challenge 2, honorable prizes in KDD 2020 Cup and BigData 2020 Cup challenges and achieved Spirits of NSF I-Corps award.Dr. Zdzislaw Polkowski is Professor of UJW at Faculty of Technical Sciences and Rector’s Representative for International Cooperation and Erasmus+ Program at the Jan Wyzykowski University Polkowice. Since 2019 he is also Adjunct Professor in Department of Business Intelligence in Management, Wroclaw University of Economics and Business, Poland. Since 2021 Zdzislaw Polkowski collaborates with the Karkonosze State University of Applied Sciences in Jelenia Góra, Poland. Moreover, he is Visiting Professor in Univeristy of Pitesti, Romania, WSG University Bydgoszcz, Poland, and Adjunct Professor in Marwadi University, India. He is Former Dean of the Technical Sciences Faculty during the period 2009-2012 at UZZM in Lubin.   He has published more than 120 papers in journals, 25 conference proceedings, including more than 50 papers in journals indexed in the Web of Science, Scopus, IEEE.Dr. Polkowski is Co-Editor of  five books which have been published in Springer and CRC Press Taylor & Francis.

• Forecasting Future Stock Market Values Using Long-Term Memory Models and Sentiment Analysis.- Early Detection and Classification of Blight Diseases in Tomato and Potato Leaf Using Deep Convolution Neural Networks.- A Smartphone based Robust Model for Intelligent Prediction of Thyroid disease.- Analysis of leveraging machine learning and data analytics to predict Cardiac Disease.- Comparative Analysis of Machine Learning Algorithms for Early Sepsis Detection.