Dr. Zarko is a Professor at the Maritime Faculty, University of Dubrovnik, CROATIA. Dr. Zarko spent several years as a field engineer and Marine engineer. He is Establishing a cruise management company from the beginning til full certification (Document of Compliance, ISO 9001, establishing technical dep; purchasing dep; HR dep). Managed planned maintenance system of the ships, implemented planned maintenance system -AMOS, organized shore support, purchased certifications from flag state and classification society. Planning and supervising dry docking. Managing vendors and services. Planning, organizing, and supervising refit and rebuilding of ship interiors, new cabins, restaurants, and other public spaces on the cruise ships. Chief Engineer of Cruise Ships. Dr. Zarko has authored over 50 journal articles and conference papers in high-quality engineering and scientific journals such as the NAŠE MORE, Promet-Traffic & Transportation, and Transactions on Maritime Science. Dr. Zarko is a member and a certified engineer of the Croatian Chamber of Engineers of Transport and Transportation Technology - a professional class of marine engineers and traffic engineers on inland waterways, a Junior Editor of the international scientific journal for the sea and seafaring Naše more; and of the Journal of Environmental Science and Engineering Technology. A member of the examination committee at the Ministry of Maritime Affairs of Transport and Infrastructure - Harbour Master's Office in Dubrovnik for taking state professional examinations of a ship's engineer, Chief engineer, and ship's electro-technical officer, He is also actively involved in the international exchange of teaching staff of the Erasmus+ program.

 

Speech title "Model of Risk Assessment Using Multiplicative Matrices"

Abstract-Risk matrices recommended by International Maritime Organization (IMO) and International Standards Organization (ISO) are not suitable for the risk assessment of the pollution of the coastal sea by sewage waters from various vessels. An original model has been set for risk assessment by means of multiplicative matrices at three levels. Very complex assessments with a more input factors unlike the classic risk matrix that has two input factors. The proposed model of risk assessment uses matrices which first determine the vessel risk index taking into consideration the factor of device for the processing of faecal waters and the factor of regulations that are applied to the respective vessels. Later, the location sensitivity index is determined, which takes into consideration the sensitivity factor of the location and the factor of impact on the location. Finally, at the third level the assessed risk of sea pollution by sewage waters is determined according to the type of vessel at precisely defined maritime zone locations. The offered model of risk assessment using multiplicative matrices has practical application and can be used also for many other risk assessments that take into consideration many input factors that affect the risk.

Dr. Jun-Ho Huh Since April 2025, he has been a Full Professor (Tenured) with the Department of Data Informatics/Data Science, National Korea Maritime and Ocean University, Republic of Korea. Also, since September 2020, he has been an Center Chair (Director) of Big Data Center for Total Lifecycle of Shipbuilding and Shipping at National Korea Maritime and Ocean University. Also, since April 2025, he has been Join a Full Professor (Tenured) (Sep. 2022~Mar. 2025: Associate Professor) of Global R&E Program for Interdisciplinary Technologies of Ocean Renewable Energy (BK 21 Four Research Group) of Interdisciplinary Major of Ocean Renewable Energy Engineering, National Korea Maritime and Ocean University, Republic of Korea. Also, since April 2025, he has been a Full Professor (Tenured) (Mar. 2024~Mar. 2025: Associate Professor) of Research Group of Marine Safety and Disasters, Dept. of Convergence Paper on the Ocean Science and Technology, Ocean Science and Technology School (OST School: KMOU & KIOST: Korea Institute of Ocean Science and Technology). He was a Research Professor at Dankook University at Jukjeon, Yongin, Republic of Korea, from July 2016 to September 2016. Also, he was an Assistant Professor with the Department of Software, Catholic University of Pusan, Republic of Korea, from December 2016 to August 2019. Also, he was an Assistant Professor with the Department of Data Informatics, National Korea Maritime and Ocean University, Republic of Korea, from Sep., 2019 to Sep., 2021. Also, he was an Associate Professor (Tenured) with the Department of Data Informatics, National Korea Maritime and Ocean University from Oct., 2021 to Mar., 2024. He received B.S. in Science Degree from Department of Major of Applied Marine Sciences, And, B.E. in Engineering Degree (Double Major) from Department of Computer Engineering from Jeju National University, Republic of Korea in Aug. 2007. And he received M.A. degree in education from Department of Computer Science Education, Pukyoug National University in Aug. 2012. Also, he received the Ph.D. in Engineering Degree from Department of Computer Engineering, Pukyoug National University, Republic of Korea in Feb. 2016. He received Best Paper Minister Award (Ministry of Trade, Industry and Energy, Korean Government) the 16th International Conference on Control, Automation and Systems (Oct. 2016), ICROS with IEEE Xplore. Also, he received Springer Nature Most Cited Paper Award, Human-centric Computing and Information Sciences most cited paper award 2019 (Research published in the journal between 2016-2018; SCIE). Also, he was awarded the Commendation for Meritorious Service in the Promotion of Busan's Data Industry in December 2023. (Commendation by the Mayor of Busan, Republic of Korea Government). He was General/Head Professor of Catholic University of Pusan on International Game Exhibition G-Star 2017 (G-Star 2017). Also, he was the Organizing Chair of 15th International Conference on Multimedia Information Technology and Applications (MITA 2019: University of Economics and Law (UEL), Vietnam National University Ho Chi Minh City, Vietnam). Also, he was the Organizing Chair of 17th International Conference on Multimedia Information Technology and Applications (MITA 2021). He was Editors (ME/AE) at Journal of Information Processing Systems (JIPS), Korea Information Processing Society (SCOPUS/ESCI indexed) from Managing Editor (ME) Jan. 2020 to Dec. 2021/from Associate Editor (AE) Apr. 2016 to Dec. 2023. Also, he was Managing Editor (ME) at Journal of Multimedia Information System (JMIS), Korea Multimedia Society (EI/KCI indexed) from Jan. 2017 to Dec. 2022. He is the Book Author of “Smart Grid Test Bed Using OPNET and Power Line Communication” pp.1-425, IGI Global, USA, 2017. Also, He is the Book Author of “Principles, Policies, and Applications of Kotlin Programming” pp.1-457, IGI Global, USA, 2023. And, he has authored/edited 10 books and edited 10 special issues in reputed Clarivate Analytics Index journals. Since Mar. 2025, he has been an Managing Editor (ME) of JICCE (SCOPUS/KCI) (Korea Institute of Information and Communication Engineering/former Korean Institute of Maritime Information & Communication Sciences). Also, he has published more than 117 articles in Clarivate Analytics Index (SCI/SCIE/SSCI indexed) with over 4500 citations and has an h-index of 34. He has given three invited talks Chi Minh University of Banking (HUB) (Oct. 2023), Vietnam National University HCM, University of Economics and Law (Aug. 2023, May 2025) and two keynote speeches (The 41st Conference of The Malacological Society of Korea: June 2025, Soonchunhyang University) (17th ICFICE 2025: July 2025, Guam USA) at conferences. He is Stanford/Elsevier/SCOPUS World Top 2% Scientist (2023, 2024). https://scholar.google.com/citations?user=cr5wjNYAAAAJ&hl=en

 

Speech title "Intelligent Aquaculture: AI Trends Driving the Future of Marine Food Production"

In this Invited Talk, Prof. Jun-Ho Huh will begin with a concise survey of the evolution of Artificial Intelligence (AI) and Big Data. Prof. Jun-Ho Huh will highlight pivotal breakthroughs from the Google DeepMind team that were featured on the Cover Paper of Nature, including AlphaGo, AlphaGo Zero, Ithaca, and AlphaFold, and will discuss how these achievements have shaped current AI trends.
Prof. Jun-Ho Huh will then explore influential AI applications in aquaculture, including the well-recognized article from third cover story in IEEE Spectrum (May 2025) titled “This Alphabet Spin-off Brings ‘Fishal Recognition’ to Aquaculture: Tidal’s AI and Robots Make Salmon Farming More Sustainable.” Key academic publication venues will also be introduced, such as the prestigious Proceedings of the IEEE with over 110 years of history, as well as IEEE Transactions on Big Data, IEEE Transactions on AgriFood Electronics, and IEEE Transactions on Artificial Intelligence.
Prof. Jun-Ho Huh will present his major research contributions from 2017 to 2025 in the fields of Artificial Intelligence applied to Smart Marine Science and Smart Aquaculture, including SCI-indexed publications, recently submitted manuscripts, and ongoing research projects. Effective academic publishing strategies will also be discussed. In addition, Prof. Jun-Ho Huh will showcase the achievements of national research projects he has led, such as the 2024 award-winning project selected as the top achievement by public vote in the Republic of Korea titled “Image Data Training and Comparative Analysis Using a Dataset for Single Oyster Fatness Characterization” and its extension in 2025, “Development of Single Oyster Sorting and Management Factors Using AI.”
Finally, Prof. Jun-Ho Huh will briefly introduce recent Keynote Speeches presented at The 41st Conference of The Malacological Society of Korea of Korea in June 2025 (Trends in AI and the Future of AI-Based Single Oyster Identification Methods) and at the 17th ICFICE July, 2025 in Guam, USA (Trends in Artificial Intelligence and Artificial Intelligence Driven Methods for Single Oyster Identification: Opportunities, Challenges, and Future Directions) The talk will conclude with perspectives on future directions for marine technology innovation.

Dr. Gwanghyun Jo is an Associate Professor (Tenure Track) with the Department of Mathematical Data Science, Hanyang University ERICA, Republic of Korea. He received the B.S. (Feb. 2011), M.S. (Feb. 2013), and Ph.D (Feb. 2018). degrees in Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea. From 2018 to 2019, he was a Postdoctoral Researcher at Department of Mathematical Sciences in KAIST. He was an Assistant Professor (Tenure Track Sep. 2019~Sep. 2022) and Associate Professor (Tenure Track Oct. 2022~Aug. 2023) in the Department of Mathematics, Kunsan National University, Republic of Korea. Since Mar. 2025, he has been an Editor-in-Chief of JICCE (SCOPUS/KCI) (Korea Institute of Information and Communication Engineering/former Korean Institute of Maritime Information & Communication Sciences since 2003~2011). Also, he has served as a Vice President of Korea Institute of Information and Communication Engineering since Mar. 2025.

Currently, he is a member of the editorial board of International Journal of Fuzzy Logic and Intelligent Systems, Journal of Korean Institute of Intelligent Systems, and Journal of Korea Institute of Information and Communication Engineering.

Recently, he has been selected for Mid-Career Researcher Program grant from the National Research Foundation of Korea (NRF) for the project “Development of a mixed virtual volume method for prediction of multiphase flows in poroelastic media” (2025.9~2028.8).

 

Speech title "Title: Axis-augmented physics-informed neural network for Poisson-Boltzmann equation"

Abstract-While physics-informed neural networks (PINNs) have been successfully applied to a wide range of PDEs, relatively few studies have addressed PDEs involving interfaces. In this presentation, we introduce an axis-augmented PINN that tackles elliptic interface problems with discontinuous solutions. We start by reformulating the problems into continuous problems in a higher-dimensional space via Sobolev extension. Then we define the physics-informed neural network with augmented variables which retains universal approximation property. In practice the additional axis is used to label the location of subdomains. The loss function is judiciously defined to include the strong form of governing equations in augmented variables. We apply the axis-augmented PINN for the Poisson–Boltzmann equation where we observe robust numerical results with respect to the locations of singular charges. Finally, we discuss a convergence analysis of the axis-augmented PINN applied to the Poisson–Boltzmann equation. We show that the errors between exact and reconstructed solutions by PINN is bounded by the loss functional, which can be made small by increasing the number of parameters such as number of nodes and training points. The proposed methods can be extended to various PDEs having discontinuous solutions.