Jianzhi Li | Fiber sensing | Best Researcher Award

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Prof. Jianzhi Li | Fiber sensing | Best Researcher Award

 professor at Shijiazhuang Tiedao University,  china

Jianzhi Li is a Professor at the Key Laboratory of Structural Health Monitoring and Control, Shijiazhuang Tiedao University, specializing in fiber sensing technology and structural health monitoring. 🌉 She earned her Ph.D. from Beijing Jiaotong University and later held an academic post at Osaka University, Japan. 🚄 Her work focuses on enhancing railway infrastructure safety through innovative sensing techniques. 📚 Jianzhi has published numerous SCI papers and authored several books. 🚀 Her groundbreaking contributions in the field have earned her multiple awards, cementing her status as a leading researcher in fiber optics and structural health.

Publication Profile

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Education 🎓

Jianzhi Li earned her Ph.D. in Structural Diagnosis and Optimization from Beijing Jiaotong University in 2009. 📚 Her doctoral studies focused on identifying and solving complex structural challenges in engineering. 🌏 She further broadened her academic horizons by serving as an Associate Professor at Osaka University in Japan between 2014 and 2015. 🏛️ This role allowed her to collaborate internationally and enhance her expertise in fiber optic sensing technology. ✨ Throughout her education, she gained deep insights into the intersections of structural health and smart material technologies, which now form the cornerstone of her research endeavors.

Experience 🏢 

Jianzhi Li currently serves as a Professor at Shijiazhuang Tiedao University’s Key Laboratory of Structural Health Monitoring and Control. 🚇 She has led several high-impact projects, particularly in fiber optic sensing and structural health monitoring for railways and bridges. 🌉 During 2014–2015, she was an Associate Professor at Osaka University, contributing to international collaborations. 📊 With over 20 patents to her name and numerous published works in prestigious journals, her experience spans industry-relevant research and cutting-edge academic advancements. 💼 She also leads the China National Key Research and Development Program, contributing to the enhancement of railway infrastructure safety.

Awards and Honors  🏆

Jianzhi Li has received numerous awards, including the First Prize for Technological Invention in Hebei Province. 🌟 She was recognized with the “Best Paper” award at the 6th International Conference on Optoelectronic Sensing. 🎖️ Her outstanding research contributions have earned her prestigious honors such as the Hebei Outstanding Youth Talent Award and a place in the Hebei 333 Talent Program. 📜 She has authored three books, including an internationally recognized English-language textbook, and her innovative work in fiber sensing and structural health has placed her among the top researchers in China. 🌍 Her membership in the Chinese Optical Society and other professional groups reflects her impact on the scientific community.

Research Focus🔬

Jianzhi Li’s research is centered on fiber optic sensing technologies and structural health monitoring. 🚇 Her work addresses critical infrastructure challenges, including heavy-duty railway bridges and roadbeds. 🔧 She has been instrumental in advancing fiber-based sensing systems for monitoring railway hazards and enhancing safety through predictive detection. 🛰️ Her research extends to smart materials and their applications in dynamic environments, focusing on the early detection of structural anomalies. 🚀 Jianzhi’s contributions are practical and forward-looking, pushing the boundaries of electromagnetic and optical sensing in engineering, leading to the development of more robust and resilient civil structures.

Publication  Top Notes

Evaluation of Concrete Carbonation Based on a Fiber Bragg Grating Sensor
📅 Published: December 2023
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi15010029
Contributors: Jianzhi Li, Haiqun Yang, Handong Wu

This paper introduces a novel approach for monitoring concrete carbonation using Fiber Bragg Grating (FBG) sensors, a crucial method for assessing structural durability.

A Long-Term Monitoring Method of Corrosion Damage of Prestressed Anchor Cable
📅 Published: March 2023
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi14040799
Contributors: Jianzhi Li, Chen Wang, Yiyao Zhao

This research presents a long-term monitoring technique for detecting corrosion in prestressed anchor cables, improving infrastructure safety and longevity.

A Combined Positioning Method Used for Identification of Concrete Cracks
📅 Published: November 2021
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi12121479
Contributors: Jianzhi Li, Bohao Shen, Junjie Wang

This paper discusses a hybrid method for accurately identifying concrete cracks, advancing structural health monitoring.

A Spiral Distributed Monitoring Method for Steel Rebar Corrosion
📅 Published: November 2021
📰 Journal: Micromachines
🌐 DOI: 10.3390/mi12121451
Contributors: Jianzhi Li, Yiyao Zhao, Junjie Wang

Conclusion

Professor Jianzhi Li stands out as a strong candidate for the Best Researcher Award due to her exemplary research contributions, innovative spirit, and recognized leadership in the field of fiber sensing and structural health monitoring. Her achievements reflect not only her commitment to advancing science and technology but also her potential to further influence the field. With targeted improvements in professional engagement and industry collaboration, she could amplify her impact even more.

Mr. Bingtao Wang | Energy consumption model | Best Researcher Award

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Mr. Bingtao Wang | Energy consumption model | Best Researcher Award

Mr. Bingtao Wang, Shan Dong University, China

Bingtao Wang, currently a Master’s student in Communication Engineering at Shandong University (Weihai), holds a Bachelor’s degree in Electronic Engineering. His research focuses on energy consumption models and fault diagnosis in mobile robots. Bingtao has led multiple innovative projects, including the development of a quadcopter UAV and a visual perception crawler robot. His significant contribution lies in the creation of robust energy models and diagnostic methods that enhance the efficiency and reliability of Three-Wheeled Omnidirectional Mobile Robots (TOMRs), paving the way for future advancements in autonomous navigation and robotics.

Professional Profiles:

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🎓 Academic and Professional Background (100 words max):

Bingtao Wang, male, was born in Liaocheng City, Shandong Province in September 2001. In 2023, he graduated from Shandong University (Weihai) with a Bachelor’s degree in Electronic Engineering. He is currently pursuing a Master’s in Communication Engineering at Shandong University (Weihai), College of Electrical and Engineering. His research focuses on energy consumption model building and fault diagnosis.

📝 Self-Declaration:

I authenticate that to the best of my knowledge the information given in this form is correct and complete. At any time, I am found to have concealed any material information, my application shall be liable to be summarily terminated without notice. I have read the terms and conditions and other policies of the Awards and agree to them.

✍️Publications Top Note :

Fault Detection and Diagnosis of Three-Wheeled Omnidirectional Mobile Robot Based on Power Consumption Modeling

Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

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Dr. Katarina Djordjevic | Artificial Intelligence | Best Researcher Award

Dr. Katarina Djordjevic, University of Belgrade, Serbia

Dr. Katarina Đorđević holds a PhD in Physics and is an expert in the physics of condensed matter and photoacoustics. She has significant experience in applying neural networks for material characterization, supervised machine learning, and solving inverse problems. Dr. Đorđević is skilled in numerical testing and developing measurement procedures, as well as utilizing computational intelligence algorithms in various applications. Her work involves a blend of theoretical and practical approaches, leveraging advanced computational techniques to enhance understanding and innovation in material sciences.

 

Professional Profiles:

Google Scholar

Intelligence 🚀

Dr. Katarina Đorđević, PhD in Physics, is a renowned expert with extensive experience in the physics of condensed matter, photoacoustics, and the application of neural networks in material characterization. Her diverse expertise spans multiple cutting-edge fields, making her a leading figure in both theoretical and applied physics.

🌟 Physics of Condensed Matter:

Dr. Đorđević’s work in condensed matter physics delves into the intricate properties of matter in various states, contributing to a deeper understanding of material behavior under different conditions.

🔊 Photoacoustics:

She is well-versed in photoacoustics, a technique that combines light and sound to probe the properties of materials. This innovative approach allows for non-invasive, highly precise material characterization.

🤖 Neural Networks & Material Characterization:

Leveraging neural networks, Dr. Đorđević has advanced the field of material characterization. Her research utilizes these artificial intelligence systems to analyze and predict material properties with unprecedented accuracy.

💻 Supervised Machine Learning:

A significant portion of her work involves supervised machine learning, where she trains models to recognize patterns and make predictions based on extensive datasets. This has vast applications in materials science and beyond.

🔄 Inverse Problem Solving:

Dr. Đorđević excels in solving inverse problems, which involve determining unknown causes from known consequences. This is crucial in many scientific and engineering disciplines, where direct measurement is challenging or impossible.

🔢 Numerical Testing & Measurement Procedures:

Her expertise extends to numerical testing and developing precise measurement procedures, ensuring accuracy and reliability in experimental physics.

🧠 Computational Intelligence Algorithms:

She applies advanced computational intelligence algorithms to tackle complex problems in physics and material science, driving innovation and efficiency in her research.Dr. Katarina Đorđević’s multidisciplinary approach and profound knowledge make her a standout scientist, continually pushing the boundaries of what is possible in physics and computational intelligence. 🌍🔬✨

📖 Publications Top Note :

1. Photoacoustic Measurements of the Thermal and Elastic Properties of n-type Silicon Using Neural Networks

Authors: КL Djordjević, DD Markushev, ŽМ Ćojbašić, KL Djordjević
Journal: Silicon 12 (6), 1289-1300, 2020
Citations: 21

2. Computationally Intelligent Description of a Photoacoustic Detector

Authors: MI Jordovic-Pavlovic, AD Kupusinac, KL Djordjevic, SP Galovic, …
Journal: Optical and Quantum Electronics 52, 1-14, 2020
Citations: 19

3. Development and Comparison of Techniques for Solving the Inverse Problem in Photoacoustic Characterization of Semiconductors

Authors: M Nesic, M Popovic, K Djordjevic, V Miletic, M Jordovic-Pavlovic, …
Journal: Optical and Quantum Electronics 53, 1-16, 2021
Citations: 17

4. Photoacoustic Optical Semiconductor Characterization Based on Machine Learning and Reverse-Back Procedure

Authors: КL Djordjevic, SP Galovic, MI Jordovic-Pavlovic, MV Nesic, MN Popovic, …
Journal: Optical and Quantum Electronics 52, 1-9, 2020
Citations: 16

5. Influence of Data Scaling and Normalization on Overall Neural Network Performances in Photoacoustics

Authors: КLj Djordjević, MI Jordović-Pavlović, ŽM Ćojbašić, SP Galović, MN Popović …
Journal: Optical and Quantum Electronics 54 (501), 31-35, 2022
Citations: 14*

6. Photothermal Response of Polymeric Materials Including Complex Heat Capacity

Authors: KL Djordjevic, D Milicevic, SP Galovic, E Suljovrujic, SK Jacimovski, …
Journal: International Journal of Thermophysics 43 (5), 68, 2022
Citations: 14

7. Estimation of Linear Expansion Coefficient and Thermal Diffusivity by Photoacoustic Numerical Self-Consistent Procedure

Authors: MV Nesic, MN Popovic, SP Galovic, KL Djordjevic, MI Jordovic-Pavlovic, …
Journal: Journal of Applied Physics 131 (10), 2022
Citations: 13

8. Sintering of Fly Ash Based Composites with Zeolite and Bentonite Addition for Application in Construction Materials

Authors: A Terzić, N Đorđević, M Mitrić, S Marković, K Đorđević, VB Pavlović
Journal: Science of Sintering 49 (1), 23-37, 2017
Citations: 13

9. Inverse Problem Solving in Semiconductor Photoacoustics by Neural Networks

Authors: KL Djordjevic, DD Markushev, ŽM Ćojbašić, SP Galović
Journal: Inverse Problems in Science and Engineering 29 (2), 248-262, 2021
Citations: 11

10. Use Neural Network in Photoacoustic Measurement of Thermoelastic Properties of Aluminum Foil

Authors: К Lj Djordjević, SP Galović, MN Popović, MV Nešić, IP Stanimirović, ZI …
Journal: Measurement, 111537, 2022
Citations: 10