Dr. Chadha Henchiri | Conference | Editorial Board Member

University of Sfax | Tunisia

Dr. Chadha Henchiri is a materials science researcher with strong expertise in magnetism, dielectrics, and MATLAB-based modulation of magnetic properties. He has hands-on experience in synthesizing nanopowders using high-energy ball milling, solid-state, sol-gel, and hydrothermal methods, and has designed high-temperature impedance spectroscopy holders for both bulk and film samples. His technical skills include handling VSM, XRD, XPS, SEM/TEM, TGA-DSC, pellet pressing, and quartz-tube vacuum sealing. He is proficient in structural and magnetic characterization, Rietveld refinement, impedance spectroscopy, and XPS analysis using professional software packages such as FULLPROF, MAUD, Origin, ZView, and CASA XPS. He has participated in multiple scientific events, received specialized training in research communication and scientific publishing, and supervised several postgraduate research projects in magnetism, perovskites, and spinel ferrites. Alongside his research activities, he also contributes as a teaching professional in physics and materials science.

Profile: Scopus

Featured Publication

Ying Xia, Xin Yang, Lei Chang, Hua Zhou, Tao He, Chadha Henchiri,Fatma Argoubi, Ahmed Ben-Ismaïl, Hai-Shan Zhou, Guang-Nan Luo. (2025). Characteristics and mechanism of heat deposition in a helicon plasma source with a cusp magnetic field configuration using permanent magnets. Physics of Plasmas

Ms. Yubo Wang | Interactions and Fields | Editorial Board Member

Innovation Research Institute of CETC Taiji Computer Corp | China

Ms.Yubo Wang works at the Innovation Research Institute and Big Data Research Institute of CEC Taiji Computer Co., with prior experience at the CRRC Research Institute. His work focuses on artificial intelligence, data science, and new materials, emphasizing research, application, and experimentation. He has developed a parallel hierarchical clustering approach using a divide-and-conquer strategy to enhance efficiency in ensemble clustering, achieving significant performance improvements. He has published several research papers on big data analysis, artificial intelligence, and material technology, contributing to advancements in virus monitoring, disaster rescue systems, and agricultural simulation modeling. With multiple patents and software copyrights, his innovations have been applied across agriculture, industry, emergency rescue, medical, and rail transportation fields. His leadership in big data intellectual property and product development has driven practical applications and national-level project implementations.

Profile: Scopus

Featured Publication

Wang, Y., Saraswat, S. K., & Komari, I. E. (2023). Big data analysis using a parallel ensemble clustering architecture and an unsupervised feature selection approach. Journal of King Saud University - Computer and Information Sciences.