Yang Chen | Machine Learning Award | Best Researcher Award

Dr. Yang Chen, Machine Learning Award, Best Researcher Award

PHD at Harbin Engineering University, China

Yang CHEN, Ph.D., is a dedicated researcher specializing in ship and marine structures design and manufacture. Currently pursuing a Ph.D. at Harbin Engineering University, his focus lies in predicting motion responses of marine engineering through deep learning and digital twin technologies. With a Master’s from the same institution and a Bachelor’s from Zhejiang Ocean University, Yang has garnered numerous accolades, including scholarships and awards for his academic excellence. His research contributions span predictive mooring tension models for semi-submersible platforms, showcasing his expertise in offshore intelligent operation and maintenance. Yang’s innovative work holds promise for enhancing safety and efficiency in maritime industries.

Professional Profiles:

Scopus profile

Orcid profile

Education:

Ph.D. Student College of Shipbuilding Engineering, Harbin Engineering University, Harbin, China 09/2021 – Present Major: Ship and Marine Structures Design and Manufacture Research Area: Motion response prediction of marine structures; Deep learning; Marine engineering digital twin; Offshore intelligent operation and maintenance Thesis Title: Research on the motion response and mooring tension prediction method for semi-submersible production platforms M.Sc. Harbin Engineering University, Harbin, China 09/2020 – 06/2021 B.S. Zhejiang Ocean University, Zhoushan, China 09/2016 – 06/2020

Honors and Awards:

The First Prize Scholarship for Harbin Engineering University [2023] The Three-good students for Harbin Engineering University [2023] The Second Prize Scholarship for Harbin Engineering University [2022] The Second Prize Scholarship for Harbin Engineering University [2021] Zhejiang Ocean University Youth May Fourth Medal [2020]

Research Area:

Motion response prediction of marine structures, Offshore intelligent operation and maintenance, Deep learning, Marine engineering digital twin.

Research Works:

Lihao Yuan, Yang Chen, Yingfei Zan, Shenghua Zhong, Meirong Jiang, Yaogang Sun. A novel hybrid approach to mooring tension prediction for semi-submersible offshore platforms. Ocean Engineering, 287, 115776, 2023. Lihao Yuan, Yang Chen, Zhi Li. Real-time prediction of mooring tension for semi-submersible platforms[J]. Applied Ocean Research, 2024, 146: 103967.

Research Focus:

Yang CHEN, Ph.D., specializes in predictive modeling and analysis within the realm of marine engineering. His research focus primarily lies in developing innovative methods for predicting mooring tension in semi-submersible offshore platforms. With a keen interest in utilizing hybrid approaches and real-time data processing, Yang aims to enhance the efficiency and safety of offshore operations. By integrating deep learning techniques and digital twin technologies, he seeks to provide accurate and timely predictions, crucial for optimizing the performance of marine structures. Yang’s contributions represent a significant advancement in the field, promising practical solutions for the challenges faced in offshore engineering and operation management.

Publications (TOP NOTES)

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Emel Koc | Machine Learning Award | Best Researcher Award

Dr. Emel Koc, Machine Learning Award, Best Researcher Award

PHD at Istanbul Okan University, Turkey

Emel Koç is a Computer Engineering Ph.D. candidate at Istanbul Okan University, specializing in image analysis with machine learning and deep learning approaches. With a background in Information Systems and Technologies from Bilkent University, Emel has held various leadership roles at Istanbul Okan University, focusing on sustainability, innovation, and learning application. She has contributed significantly to projects in clinical decision support systems and mobile game-based learning. Emel’s research, particularly in neuroimaging and biomedical image analysis, showcases her expertise in applying advanced computational techniques to solve real-world problems. Passionate about education, she also teaches courses in Artificial Intelligence and Management Information Systems.

Professional Profiles:

Orcid profile

Education:

Ph.D. Istanbul Okan University, Istanbul Institute of Science, Computer Engineering (2013 – 2024) Msc. Istanbul Okan University, Istanbul Institute of Science, Computer Engineering (2011 – 2013) B.S. Bilkent University, Ankara Faculty of Applied Sciences, Information Systems and Technologies (2006 – 2010)

Experience

Sustainability and Innovation Center Assistant Director, Istanbul Okan University, Istanbul (02.08.2023 – Present) Learning Application and Research Center Director, Istanbul Okan University, Istanbul (01.10.2012 – Present) IT Expert, Istanbul Okan University, Istanbul (25.10.2010 – 01.10.2012) Application Development Intern, Acıbadem Hospital, Istanbul (17.08.2009 – 17.02.2010)

Projects

INTOUCH-ICT Project: “ICT Professionals in Touch: New nonroutine skills via mobile game-based learning” (2013 – 2015) Master Thesis: Clinical decision support systems: Methods and applications (2012 – 2013) Multiplatform M-Learning System for More Qualified Courses in the ICT Era (2012)

Teaching

Instructor at Istanbul Okan University covering Artificial Intelligence, Neuroscience and Neuroimaging, and Management Information Systems

Honors & Awards

Received the Blackboard Catalyst Awards – Leading Change in 2021 for contributions to hybrid education transformation.

Research Focus:

Emel Koç’s research primarily focuses on the application of machine learning and data analysis techniques in healthcare and education domains. Her work spans diverse topics such as autism spectrum disorder detection using neural networks, comparative studies on feature selection methods for analyzing medical data, and the implementation of game-based education strategies. Additionally, Emel has contributed to research in clinical decision support systems and the evaluation of classification algorithms for medical diagnoses. Her interdisciplinary approach combines computer science and healthcare management, emphasizing innovation in leveraging technology to improve healthcare outcomes and educational practices.

Publications (TOP NOTES)

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