Prof. Wang Tianzhen | Fault Diagnosis Awards | Best Researcher Award

Prof. Wang Tianzhen, Shanghai maritime University, China

Dr. Tianzhen Wang is a prominent full professor at Shanghai Maritime University and a Research Affiliate and Doctoral Supervisor at the Institute de Recherche Dupuy de Lôme (IRDL) in France. Her research focuses on the control and fault diagnosis of marine energy generation systems, contributing significantly to advancements in this critical field. An IEEE Senior Member, she actively participates in several professional committees, including the IEEE Energy Storage Technology Committee and the National Ocean Energy Conversion Equipment Standardization Technical Committee. With over 100 published papers, 29 patents in China and the United States, six books, five national standards, and two IEC standards to her credit, Dr. Wang is a leading figure in her area of expertise, recognized with the prestigious IEC 1906 Award. She has served as a guest editor for several journals, including the Journal of Marine Science and Engineering and Energies, focusing on technologies related to marine energy. Her commitment to the field extends to organizing major conferences, such as the Marine Energy Summit in China and multiple sessions for the IECON series of international conferences. Additionally, she has played a key role in promoting women in engineering through workshops and conferences. Dr. Wang’s impressive career trajectory includes roles as a lecturer, post-doctoral researcher, and associate professor at Shanghai Maritime University, where she has been since 2006, culminating in her current position as a full professor since July 2016.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award: Dr. Tianzhen Wang

Dr. Tianzhen Wang is a highly qualified candidate for the Best Researcher Award due to her extensive contributions to the field of marine energy generation and control systems. As a full professor at Shanghai Maritime University and a research affiliate at the Institut de Recherche Dupuy de Lôme (IRDL) in France, she has demonstrated exceptional leadership and innovation in her research.

Education and Work Experience 🎓

2006-2007: Lecturer, Department of Electrical and Automation, Shanghai Maritime University
2007-2008: Post-Doctoral Researcher, Naval Academy Research Institute of France
2008-2009: Lecturer, Department of Electrical and Automation, Shanghai Maritime University
2009-2016: Associate Professor, Department of Electrical and Automation, Shanghai Maritime University
2016.6-Present: Research Affiliate and Doctoral Supervisor, Institut de Recherche Dupuy de Lôme (IRDL), France
2016.7-Present: Full Professor and Doctoral Supervisor, Department of Electrical and Automation, Shanghai Maritime University

Achievements 📜

Published 100+ research papers
Secured 29 patents in China and the United States
Authored 6 books
Developed 5 national standards and 2 IEC standards

Awards and Honors 🏆

IEC 1906 Award
IEEE Senior Member
Committee Member of the IEEE Energy Storage Technology Committee
Committee Member of the National Ocean Energy Conversion Equipment Standardization Technical Committee
Committee Member of the CAA Fault Diagnosis and Safety of Technical Process Specialized Committee
Convener of IEC/TC114 Advisory Group 2

Publication Top Notes

A confidence-guided DS fault diagnosis method for tidal stream turbines blade

Sparrow search algorithm-optimized variational mode decomposition-based multiscale convolutional network for cavitation diagnosis of hydro turbines

A radius and minimum velocity Jensen model for far wake distribution prediction of tidal stream turbine

LAW-IFF Net: A semantic segmentation method for recognition of marine current turbine blade attachments under blurry edges

A Federated Adversarial Fault Diagnosis Method Driven by Fault Information Discrepancy

Prof. Abdullah Alhamdan, King Saud University, Saudi Arabia

Abdullah Mohamed Alhamdan is a distinguished Professor of Food Process Engineering and the Director of the Dates Industry & Technology Chair (CDIT) at King Saud University, Riyadh, Saudi Arabia. With a B.Sc. in Agricultural Engineering from King Saud University and an M.Sc. and Ph.D. from The Ohio State University, his expertise spans food processing engineering, focusing on the design of production lines, food packaging, and postharvest chain management. He is renowned for his work in dates and by-products processing, including innovative applications in dates and dairy products. Alhamdan has served as a consultant for various international and governmental bodies, such as FAO and SABIC, and has been pivotal in advancing dates technology. His contributions to the field have been recognized with several prestigious awards, including the International Prize of King Salman for Innovations (2017) and the International Khalifah Prize for Date Palm Technology

Research Interests: 🌾

Prof. Alhamdan specializes in Food Processing Engineering, focusing on:

Design of food industry production lines and food packaging

Applications of heat and mass transfer in food processing

Postharvest chain management

Dates processing and industry, including storage, freezing, and utilization of palm tree by-products

Development of innovative dairy and date-based products

Professional Activities: 🌟

Director of the Date Industry and Technology Chair (CDIT) at King Saud University

Board Member, Administrative Council of Irrigation and Drainage Authority, Ahsa

Board Member, Administrative Council of National Center of Date Palm (NCDP)

International Expert at FAO

Consultant to various organizations, including Saudi Development Fund, Arab Authority for Agricultural Investment and Development (AAAID), and more

Publication top Notes:

Impact of Storage Conditions on Fruit Color, Firmness and Total Soluble Solids of Hydroponic Tomatoes Grown at Different Salinity Levels

Non-Destructive Evaluation of the Physiochemical Properties of Milk Drink Flavored with Date Syrup Utilizing VIS-NIR Spectroscopy and ANN Analysis

Utilizing VIS-NIR Technology to Generate a Quality Index (Qi) Model of Barhi Date Fruits at the Khalal Stage Stored in a Controlled Environment

Utilizing Near-Infrared (NIR) Technology to Predict the Quality Index (Qi) Model of Barhi Dates Fruit at Khalal Stage Stored in a Controlled Environment