Prof Sanboh Lee | Mechanical Properties of Materials | Best Researcher Award

Prof. Sanboh Lee is an eminent materials scientist and engineer, currently serving as Professor Emeritus at the Department of Materials Science and Engineering, National Tsing Hua University, Taiwan. With a Ph.D. from the University of Rochester and over four decades of academic and research leadership, he has significantly advanced multiple domains in materials science. He has authored over 280 journal papers and delivered 150 international presentations, solidifying his reputation as a global thought leader. His distinguished career reflects deep expertise in dislocation mechanics, phase transformation, composite materials, and nanotechnology.

Prof Sanboh Lee, National Tsing Hua University, Taiwan

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🎓 Education

Prof. Sanboh Lee holds a prestigious academic background rooted in physics and materials science. He earned his Ph.D. in Materials Science from the University of Rochester in 1980 🧪🎓, where he developed deep expertise in defect mechanics and transport phenomena. Prior to that, he completed an M.S. in Physics from National Tsing Hua University in 1972 ⚛️📘, and a B.S. in Physics from Fu Jen Catholic University in 1970 📐🔬. His rigorous education across these renowned institutions laid a solid foundation for a lifelong contribution to scientific research and engineering innovation 🌍📚.

🏫 Experience

Prof. Sanboh Lee is a renowned academic in materials science with decades of experience across premier institutions 🌏📚. He served as Professor at National Tsing Hua University from 1985 to 2018 and is currently a Professor Emeritus 🧑‍🏫🏅. His global research engagements include roles as Adjunct Professor at the University of Science and Technology Beijing 🇨🇳, Guest Scientist at NIST, USA 🧪🇺🇸, and Visiting Scholar at Lehigh University 🏫🔬. Earlier roles include Research Associate at the University of Rochester and Postdoctoral Researcher at Xerox’s Webster Research Center 🧫⚙️—a career deeply rooted in innovation, international collaboration, and advanced materials engineering.

🏅 Honors & Funding

Prof. Sanboh Lee is a globally acclaimed materials scientist recognized for his groundbreaking work in nano-composite materials and nanotechnology 🧪🔬. He received research funding from the Ministry of Science and Technology, Taiwan for advancing mechanical properties in nanomaterials ⚙️🧫. His remarkable honors include the Lifetime Achievement Award by VDGOOD (2022), SAS Eminent Fellow (2021), and Fellow of ASM International and MRS-Taiwan 🏅🌏. Celebrated for his studies on defect interactions, fracture mechanics, and polymer transport, Prof. Lee’s awards reflect his lasting impact in academia and industry 🧠📚. His excellence spans decades of innovation, leadership, and global recognition 🌍🥇.

🔬 Research Focus

Prof. Sanboh Lee’s research spans a wide spectrum of advanced materials science topics including nano-composites, defect mechanics, fracture behavior, and transport phenomena in metals and polymers 🧬🧪. His recent work, funded by the Ministry of Science and Technology, Taiwan, investigates the mechanical properties of nano-composite materials and nanotechnology ⚙️🔍. He explores diffusion-induced stress, hydrogen transport, polymer phase behavior, and magnetic and optical properties of materials under complex environments 🌡️🧲📐. His interdisciplinary contributions bridge micro/nano mechanics, biomaterials, and semiconductor devices, pushing the boundaries of modern materials engineering and applied physics 🔬🌍.

📚 Publications

Kinetic Analysis of the Cracking Behavior in Methanol-Treated Poly(methyl methacrylate)/Functionalized Graphene Composites

Authors: Bing-Hong Yang, Shou-Yi Chang, Yulin Zhang, Fuqian Yang, Sanboh Lee
Journal: Journal of Composites Science (Feb 2025)

Cracking in UV-Irradiated Poly(methyl methacrylate)/Functionalized Graphene Composites: Solvent Effect

Authors: Bing-Hong Yang, Shou-Yi Chang, Yulin Zhang, Fuqian Yang, Sanboh Lee
Journal: Journal of Polymer Research (Sept 2024)

Analysis of the Thermal Aging Kinetics of Tallow, Chicken Oil, Lard, and Sheep Oil

Authors: Yun-Chuan Hsieh, Hao Ouyang, Yulin Zhang, Donyau Chiang, Fuqian Yang, Hsin-Lung Chen, Sanboh Lee
Journal: Molecules (Sept 2024)

Creep-Recovery Deformation of 304 Stainless-Steel Springs Under Low Forces

Authors: Ming-Yen Tsai, Shou-Yi Chang, Yulin Zhang, Fuqian Yang, Sanboh Lee
Journal: Mechanics of Materials (June 2024)

A Mechanical Model for Stress Relaxation of Polylactic Acid/Thermoplastic Polyurethane Blends

Authors: Yi-Sheng Jhao, Hao Ouyang, Chien-Chao Huang, Fuqian Yang, Sanboh Lee
Journal: Journal of Composites Science (May 2024)

Thermal Degradation of Vegetable Oils

Authors: Yi-Hsiou Tsai, Donyau Chiang, Yu-Ting Li, Tsong-Pyng Perng, Sanboh Lee
Journal: Foods (April 2023)

Brownian Motion of Poly(divinylbenzene) Nanoparticles in Water

Authors: Ching-Bin Lin, Chia-Wei Lee, Hao Ouyang, Fuqian Yang, Sanboh Lee
Journal: Journal of Applied Physics (March 2023)

Mr Sicheng Wang | Smart Materials | Best Researcher Award

Mr Sicheng Wang, Beijing University of Posts and Telecommunications, China

Mr. Sicheng Wang, a graduate in Information and Computing Science from Beijing University of Posts and Telecommunications, excels in applying artificial intelligence and machine learning to energy systems. He has authored three notable papers, including one published in the SCI-indexed journal Computers and Electrical Engineering, focusing on spatio-temporal PV prediction. Recognized with multiple national awards, such as the Second Prize in Mathematical Modeling and the Bronze Award in Innovation Competitions, Mr. Wang showcases exceptional research and problem-solving skills. His work in energy management and smart grids highlights his vision for sustainable technology solutions. 🏆⚡📚

Academic Excellence 🎓📊

Mr. Sicheng Wang holds a degree in Information and Computing Science from Beijing University of Posts and Telecommunications, demonstrating a solid foundation in computational methods and data-driven research. His academic journey is distinguished by multiple prestigious awards, including the Second Prize in the National Undergraduate Mathematical Modeling Contest and the Bronze Award in the China International College Students’ Innovation Competition. These achievements reflect his exceptional analytical thinking, problem-solving abilities, and commitment to academic excellence. His dedication to applying advanced computational techniques makes him a standout in his field. 🏅🔬✨

Awards and Competitions 🏆📚

Mr. Sicheng Wang has earned multiple prestigious awards in national and provincial competitions, highlighting his excellence in innovation and problem-solving. In September 2023, he secured the Second Prize in the National Undergraduate Mathematical Modeling Contest. He later achieved the Bronze Award in the China International College Students’ Innovation Competition in September 2024. Additionally, he won the Third Prize in the National Undergraduate Computer Design Contest (June 2024) and the First Prize in the Beijing Division of the Innovation Competition (July 2024). His accolades also include a Second Prize in the National Undergraduate Mathematics Contest (October 2023). 🏅🔢✨

Academic Engagement 🎓💼

He has been actively engaged in advanced studies and research in Information and Computing Science, focusing on innovative applications of artificial intelligence and machine learning. His academic involvement includes participation in high-impact research projects and national competitions, showcasing his dedication to both theoretical and practical advancements in technology. His ongoing commitment to research and learning reflects his drive for excellence in the field of computing. 🧠🔬📊

Research Focus⚡🔬

Mr. Sicheng Wang’s research focuses on the application of artificial intelligence and machine learning in energy systems and smart grids. He has authored several high-impact papers, including a study on spatio-temporal PV prediction using a convolutional-based hybrid network, published in Computers and Electrical Engineering (SCI Q3, IF 4.0). His other notable works include an AI diagnostic model presented at AUTEEE 2023 and a multi-task learning framework for medium-term load forecasting accepted at APPEEC 2024. His research addresses critical challenges in energy prediction and management, contributing to sustainable technological advancements. 🧠📊⚡