Signal Processing, Telecommunication & Embedded Systems: AI and ML Applications

Vikrant Bhateja is Associate Professor in Department of Electronics Engineering, Faculty of Engineering and Technology (UNSIET), Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India. He is also serving as Head: Computer Sc. Engg. & Information Technology in the same university. He holds a doctorate in ECE (bio-medical imaging) with a total academic teaching experience of 21 years with around 190 publications in reputed international conferences, journals, and online book chapter contributions, out of which 40 papers are published in SCIE indexed high impact factored journals. He has been instrumental in chairing/co-chairing around 30 international conferences in India and abroad as Publication/TPC Chair and edited 55 book volumes from Springer-Nature as Corresponding/Co-Editor/Author on date. He has delivered nearly 25 keynotes, invited talks in international conferences, ATAL, TEQIP, and other AICTE sponsored FDPs and STTPs. Xin-She Yang is Reader in modeling and simulation as well as optimization at Middlesex University London, with more than 25 years’ experience in teaching and research. He got his D.Phil. in applied mathematics from Mathematical Institute, University of Oxford, in 1998. He then worked at Cambridge University Engineering Department and later as Senior Research Scientist at Mathematics and Scientific Computing Division of UK’s National Physical Laboratory. He is also Elected Fellow of the Institute of Mathematics and its Applications (2021), Fellow of Asian Computational Intelligence Society (2023), and Fellow of Soft Computing Research Society (2025). He is Co-Editor for Springer’s book series: Springer Tracts in Nature-Inspired Computing and has been on editorial boards of multiple international journals, such as Engineering Applications of Artificial Intelligence (Elsevier) and Journal of Computational Science (Elsevier). He is also Member of the UKRI Talent Peer Review College. Hai Van Pham received the doctor of engineering (Ph.D.) degree from Ritsumeikan University, Japan. He is currently Associate Professor with the School of Information and Communication Technology, Hanoi University of Science and Technology. He has published over 150 research papers in international journals and conference proceedings in ISI/ Scopus index. He is Senior Expert and conducted research projects inapplied AI and industry 4.0. His current research interests include artificial intelligence, fuzzy logics, fuzzy graph, fuzzy knowledge graph, rule-based systems and fuzzy systems, soft computing, machine learning and big data analysis in the trends of digital transformation, and industry 4.0. He served as Member of program, Associate Editor, technical committees for international conferences, and Reviewer for international conferences and journals: IEEE TRANSACTION, IEEE ACCESS, Soft Computing, Engineering applications of Artificial Intelligence and Neural Computing and Applications. Zaid Omar (Senior Member, IEEE) received the master’s degree in data communications from the University of Sheffield and the Ph.D. degree in electrical engineering from the Imperial College London, in 2012. He is currently Associate Professor with Universiti Teknologi Malaysia. His research interests include computer vision, medical imaging, and image fusion. Dr. Omar was crowned the best science communicator for FameLab Malaysia 2017—one of the biggest science communication competitions in the world organized by British Council.

• Advanced Feature Selection Techniques using PCA-RFECV for Accurate Data Driven Prostate Cancer Diagnosis.- Beyond the Mirror: Rethinking Explainabilityas Cognitive Dialogue in AI Systems.- Data Cleaning Strategies Proteomics Datasets:Challenges and Computational Solutions.- Comparison of Deep Learning Architectures for Automated Breast Ultrasound Report Generation.- Association of   Placental dysfunction   during   pregnancy with developing    Retinopathy of prematurity of the newborn.- Comprehensive Study of Existing Prediction Models for Depression in Women.- Literature Review of Sentiment Analysis on Film Criticism.- Quantum Machine Learning Analysis forElectricity Consumption.- Demographic and Personality-Based Drug Abuse Prediction using Machine Learning Models.- Comprehensive Survey of Fundus Image Analysis for Early Detection of Diabetic Retinopathy Using Deep Learning.- Automobile Vehicle Insurance Claims Fraud Detection using Machine Learning.- The Intelligent Personal Learning Assistant: A Smarter Approach to University Learning.- Artificial Intelligence and Blockchain in Court System.- Analyzing Predictive Algorithms for Demand Forecasting in Industrial Supply System.- AI-Driven Adaptive Services: Enhancing User Experience through Intelligent and User-Centric Network Design.