AI Below the Surface

Naveen P. completed his Ph.D. in the field of Image Processing from Kalasalingam Academy of Research and Education. He has more than 10 years of teaching experience. Prior to joining KPR Institute of Engineering and Technology, he was associated as NIRF Co-ordinator at Sri Eshwar College of Engineering and also served as Assistant Director - Accreditation and Ranking at Kalasalingam Academy of Research and Education. His research interests include Image Processing and Machine Learning. He received the best faculty award from Kalasalingam Academy of Research and Education in the year 2019. He has published dozen of papers in International Journals and several patents. He is presently an Associate Editor in the Journal of Intelligent and Fuzzy Systems and AD ALTA-Journal of Interdisciplinary Research. He currently serves as an Editorial Board member for the International Journal of Interactive Multimedia and Artificial Intelligence and the Journal of Current Science and Technology. Dr. Vinayakumar Ravi is an Assistant Research Professor at the Center for Artificial Intelligence, Prince Mohammad Bin Fahd University, Khobar, Saudi Arabia. Dr. Ravi has been a Postdoctoral Research Fellow developing and implementing novel computational and machine learning algorithms and applications for big data integration and data mining with Cincinnati Children's Hospital Medical Center, Cincinnati, USA. He received his Ph.D. in Computer Science from Amrita School of Engineering, Coimbatore, India. His current research interests include applications of data mining, Artificial Intelligence, machine learning and, deep learning for biomedical informatics, cyber security, image processing, and natural language processing. Dr. Ravi is editor of Efficient Data Handling for Massive Internet of Medical Things: Healthcare Data Analytics, Springer. Dr. Ravi is an editorial board member for Journal of the Institute of Electronics and Computer (JIEC), International Journal of Digital Crime and Forensics (IJDCF), and he has organized a shared task force on detecting malicious domain names (DMD 2018) as part of SSCC'18 and ICACCI'18. Ajay Arunachalam is part of the division of research and Data Science Unit at Cambridge University Press & Assessment, United Kingdom. His core interests include Opacity in AI Systems, Applied AI, Machine Learning, Deep Learning, Reinforcement Learning, Optimization, Big Data, Algorithmic trading, Natural Language Processing, and Computer Vision. His research envisions learning algorithms that can learn feature representations from both unlabelled and labelled data, be it guided with and/or without human interaction, and that are on different levels of abstractions in order to bridge the gap between low-level data and high-level abstract concepts. He led the team of data analysts, data engineers, ML engineers, and data scientists in the past. He was a post-doctoral researcher (Artificial Intelligence) at the Centre for Applied Autonomous Sensor Systems (AASS), School of Science and Technology, Örebro University, Örebro, Sweden, to which he contributes with research on Autonomous Precision Agriculture Robot. Prior to his present role, he was working as a Data Scientist at True Corporation Public Company Limited, a Communications Conglomerate, working with Petabytes of data, and building & deploying models in production. He received the Ph.D. degree in Computer Science and Information Systems (CSIS) from National Institute of Development Administration (NIDA), Thailand. He holds a master’s in computer science & engineering. from Anna University, Chennai, India, and a bachelor's in computer engineering from Savitribai Phule Pune University, Pune, India. His research interests include Distributed Systems, Wireless and Mobile Networking, Algorithmic Trading, Big Data, Applied Machine Learning/Deep Learning, Opacity in AI systems, Optimization, FOSS related to e-learning/m-learning/e-governance.

• 1. Introduction to AI and Underwater Exploration2. AI-Driven Underwater Vehicles and Drones3. Intelligent Marine Life Monitoring4. Object Recognition and Interaction in the Deep Sea5. Challenges and Ethical Considerations in Underwater AI6. Future Trends in AI and Underwater Technology7. Data Analytics for Underwater Environments8. AI-Assisted Oceanographic Research9. Autonomous Underwater Vehicles (AUVs) and Machine Learning10. Human-Machine Collaboration in Underwater Exploration11. AI Applications in Underwater Archaeology12. Societal Impact and Public Perception of AI in the Deep