Advances in Data Science and Artificial Intelligence

L. M. Patnaik earned his PhD in 1978 in Real-Time Systems and an earned D.Sc. in 1989 in Computer Systems and Architectures from the Indian Institute of Science, Bangalore. He was the Founding Vice Chancellor of the Defence Institute of Advanced Technology, Pune, from March 2008 to August 2011. With over forty years of experience, he has significantly contributed to computer science and engineering at IISc and is currently an INSA Honorary Scientist and Adjunct Professor at the National Institute of Advanced Studies, Bangalore, as well as the Pro Chancellor of GIET University, Gunupur, Odisha. Dr. Patnaik is a Life Fellow of the IEEE and a Fellow of several prestigious organizations, including the Indian National Science Academy and the Computer Society of India. His research interests include high-performance computing, soft computing, VLSI design, machine learning, and data analytics, with over 1,300 publications, including a widely cited paper in adaptive genetic algorithms. He has played a crucial role in the development of key organizations like CDAC and the National Brain Research Centre and initiated important conferences in the field. His contributions have earned him numerous awards, including the Dr. Vikram Sarabhai Research Award and the IEEE Computer Society Technical Achievement Award, highlighting his notable impact on Indian higher technical education. G.T. Raju is a distinguished academic and research professional in the field of Computer Science and Engineering, with over 32 years of experience in teaching and research. He currently serves as the Principal and Professor at SJC Institute of Technology in Chickballapur and is the Creator and Founder Director of BGS College of Engineering and Technology in Bengaluru. Dr. Raju has a wealth of experience in academia and industry, including 16 years dedicated to research. His contributions span several areas, including Knowledge Discovery in Databases, clustering techniques, web mining, artificial intelligence, machine learning, and next-generation agriculture and communication. He has guided 20 doctoral candidates and evaluated numerous Ph.D. theses.N. H. Prasad is currently a Professor and Head of the Master of Computer Applications Department at Nitte Meenakshi Institute of Technology (NMIT) in Bangalore. He received his Ph.D. from Jawaharlal Nehru University in New Delhi, India, and has over 18 years of experience in various roles within both public and private sector enterprises, including the Ministry of Human Resource Development, Government of India. He has been the Founder Vice-President of the International Federation of Engineering Education Societies (IFEES) in Washington, D.C., and served as Vice-Chancellor of Bangalore University for two terms. Additionally, he was the President of the Indian Society for Technical Education (ISTE) in New Delhi for three terms and a member of the Executive Committee of the All India Council for Technical Education (AICTE), where he chaired its South West Region Committee. Dr. Prasad has received prestigious recognitions, including the “Dr. Abdul Kalam Lifetime Achievement Award” and a “Young Faculty” award at the 2nd Academic Brilliance Awards.

• An Unique Comprehensive Analysis for Detecting Vitamin Deficiencies using Picture Analysis through Image Processing.- Predictive Traffic Management and Deep Learning Based Vehicular Congestion Mitigation.- Comprehensive analysis of Smart Greenhouse Monitoring System.- Cybersecurity Threat Detection of Anomaly based DDoS Attack using Machine Learning.- Deep Learning-Based Biometric Verification in a Secure Cloud Environment.- MOBILE APPLICATION TO DETECT SUGARCANE DAMAGED BILLETS.- Android Security: Genetic Algorithm-Based Malware Detection System.- Fire Detection Using Transformer Based Model.- NFT MARKETPLACE FOR EXCHANGE OF DIGITAL ARTIFACTS USING SMART CONTRACT.- Multi-Facial Recognition using Multitask Cascaded Convolutional Neural Networks.- CROP-CONNECT : Empowering Farmers through Digital Community.- A Novel System for Authentication of Identity Cards using YOLO v5 & YOLO v8.- Tailored Garment Recommendations Using Computer Vision and Machine Learning.- Brain Diseases Prediction using ML.- ASSISTING VISUALLY CHALLENGED INDIVIDUALS TO DISTINGUISH AUTHENTIC CURRENCY FROM COUNTERFEIT.- Zenify.me - Your AI companion for a happier, healthier you.- IoT-Powered Hydroponics System: A Real-Time  Monitoring and Control System.- Robust Human Target Detection And Acquisition.- Software Effort Estimation using AIML and a User-interface: A Comprehensive Literature Review.- A semi-supervised Centroid based Object Tracking in Video surveillance Using Deep Detector and Salience Estimation.- Recognizing personality traits from handwriting with machine learning technique.- Exploring the causes of Maternal mortality in Karnataka and Crafting Strategies for Prevention.- Utilizing Deep Learning Features to Categorize White Blood Cells in Blood Smear Images.- ENHANCING DATA SECURITY AND CLOUD PERFORMANCE WITH CONFIDENTIALITY- BASED CLASSIFICATION-AS-A-SERVICE (C2AAS) FOR BIG DATA PROCESSING AND STORAGE.- SmokeEye: An AI-ML based Dehazing and Desmoking System.- HYBRID APPROACH USING DEEP NEURAL NETWORKS FOR LEAF DISEASE DETECTION AND DISEASE MANAGEMENT.- Hybrid Model of SRGAN CNN-LSTM for Classifying Dysgraphia in Primary school children using Handwritten Images.- Securing Evidence in Digital Forensics Using Blockchain.- A Tri-Model Ensemble Approach for Phishing URL Detection using Explainable AI and Hyperparameter Tuning Techniques.-Exploring Advanced Techniques in Evaluating Water Quality Safety: A Comparative Analysis of Machine Learning and XAI Approaches.- Enhancing Medical Imaging: A Holistic Exploration of Precise PCOD Segmentation and Classification using Ensemble Deep Learning Approaches.- Design and Implementation of AI Machine Vision Inspection System with Multi-Optical Images for OLED Film Manufacturing.- Novel Framework for Malicious URL Detector using Enhanced XGBoost.- HealthLink: A Healthcare System Leveraging IoT, Blockchain, and IPFS for Enhanced Data Security.- Brain Tumor Segmentation Using 3D Unet and 3D Autoencoder Contribution.- Exploring Synthetic Data Generation Methods: A Comprehensive Survey.- Safeguarding EVs: A Next-Generation BMS with Integrated Fire Protection.- A QoS Aware RA Algorithm for OFDM Network.- Advancing Video Surveillance Security: Real-Time Threat Detection  with Deep Learning.