Goswami / Saha / Beed Data Management, Analytics and Innovation

Proceedings of ICDMAI 2025, Volume 1
Erscheinungsjahr 2025
ISBN: 978-981-966537-2
Verlag: Springer Singapore
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 420 Seiten

Reihe: Intelligent Technologies and Robotics

This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence, and data analytics, along with advances in network technologies. The book is a collection of peer-reviewed research papers presented at 9th International Conference on Data Management, Analytics and Innovation (ICDMAI 2025), held during 17–19 January 2025 at St. Xavier’s College (Autonomous), Kolkata, India. It addresses state-of-the-art topics and discusses challenges and solutions for future development. Gathering original, unpublished contributions by scientists from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry. The book is divided into three volumes.

Zielgruppe

Research

Autoren/Hrsg.

Goswami, Saptarsi

Saha, Sajal

Beed, Romit S

Basu, Kanadpriya

Inhaltsverzeichnis

Chapter 1: Clustering-based Multivariate Prediction Model for Infectious Disease Forecasting in India.- Chapter 2: HyGen – A Hybrid Automation Testing Approach for reducing hallucination in LLM based applications.- Chapter 3: Chaotic-Wasserstein GAN Based Adversarial Defense.- Chapter 4: Machine Learning Approach for Sound Vibration Prediction Using Sensor-Based Technologies.- Chapter 5: Offensive Text Detection: Exploring Traditional Classifiers, Ensemble Models, and Kolmogorov Arnold Networks in Code-Mixed Tamil-English Text.- Chapter 6: Towards Autonomous Deep Learning: Comparative Analysis of AI-Generated and AI-Evaluated Code Using LLMs for Computer Vision Tasks.- Chapter 7: An Empirical Evaluation for LLMs Performance on AI Question & Answer in Bengali.- Chapter 8: Wikipedia-Savvy-RAG: A Lightweight Retrieval-Augmented Generation System for STEM Question Answering.- Chapter 9: Genre Based Movie Recommendation System to Improve Efficiency using LSTM Method.- Chapter 10:Recommendation Framework for Generative AI-Assisted Software Development.-

Über Autor(innen)

Dr. Saptarsi Goswami has 22+ years of experience in industry and academics. He holds a B.E. in ECE from NIT Jaipur, a diploma in business finance from ICFAI, and an M.Tech and Ph.D. from the University of Calcutta. He worked for 10+ years in IT at Tata Infotech Ltd, PwC, and Cognizant Technology Solutions. Currently, he is an Assistant Professor & Head of Computer Science at Bangabasi Morning College (University of Calcutta). He was a Visiting Scientist at Iwate Prefectural University, Japan, and is a founding member of the Data Science Lab at the University of Calcutta, serving as a lead researcher and research supervisor. Dr. Goswami has an H-Index of 20 and 2,000+ citations on Google Scholar. He leads the ODSC and Azure Community in Kolkata, is an executive member of the Society for Data Science (S4DS), and has chaired multiple editions of ICDMAI. His Machine Learning lectures are featured in the National Digital Library of India (NDLi). He has contributed to state-level programs for the Government of West Bengal and authored “Deep Learning” and “AI for Everyone” (Pearson India).

Dr. Sajal Saha has 20+ years of academic experience and is Professor & Head of Computer Science and Engineering and Director of Product & Innovation at Adamas University. He earned his Ph.D. from NIT Durgapur in 2016, focusing on QoS and Mobility Management in WiMAX and Next-Gen Networks. He began his career at ISRO in 2004 as a Project Trainee in GIS and Remote Sensing. He holds certifications from IBM, AWS Academy, and Dale Carnegie and serves as a Mentor of Change for Atal Innovation Mission, Coordinator for IIRS ISRO Outreach Program, and research liaison with Emory University and the Asian Institute of Technology. Dr. Saha has led TEQIP, NBA, NAAC, and NIRF assessments and facilitated cloud computing curriculum and plagiarism detection tools. He is an active member of IEEE, ACM, and ISoC-Internet Society, contributing to global research and networking.

Prof. Kanadpriya Basu is Professor of the Practice in Data Science & Operations at the Marshall School of Business, University of Southern California (USC), and Co-Founder at ArrowsUp.. Previously, he was a Professor of the Practice at Thunderbird School of Global Management (ASU), specializing in Data Science & Leadership Development. He has led 4IR initiatives aimed at reaching 100 million learners and was Director of the Global Business Analytics Executive Program. With 20+ years in AI and data science, he has built high-performing teams at MFour Research, SnackNation, Covisus, and Medallia, contributing to cutting-edge AI innovations. He holds multiple patents and has published papers in geophysics and AI. Kanad has taught at Occidental College and the University of Texas. He holds a Ph.D. in Applied & Computational Mathematics and is an established thought leader in AI, frequently speaking at global conferences.

Dr. Romit S Beed is an Associate Professor and Head of the Postgraduate and Research Department of Computer Science with 20+ years of teaching experience. He is known for his innovative teaching methods and commitment to academic and student development. His expertise includes Multi-Objective Optimization, Computational Intelligence, DBMS, Software Engineering, and IoT. Actively engaged in research and consultancy, he contributes to mentorship, academic leadership, and co-curricular activities. His work fosters a culture of learning and innovation at St. Xavier’s College (Autonomous), Kolkata.