Da Shi | Structural engineering | Best Researcher Award

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Dr. Da Shi | Structural engineering | Best Researcher Award

Doctor, Zhejiang University, China

Soukaina Elkadaoui is a junior scientific researcher specializing in biochemistry, microbiology, and medical science. Born on March 20, 1997, she is known for her research on the physicochemical properties of chitosans and their antibacterial and antifungal effects. Soukaina is currently pursuing her PhD and is deeply involved in research that intersects pharmaceuticals, paramedical studies, and marketing.

Profile

Scopus

🎓 Education:

Soukaina Elkadaoui is currently pursuing her PhD at the Bioresources and Food Safety Laboratory, University Cady Ayyad Marrakesh (2021-2024). She holds a Master’s degree in Metrology and Quality from the Faculty of Sciences Semlalia, University Cady Ayyad Marrakesh (2018-2020). She completed her Bachelor’s degree in Biomedical Laboratory Technology at the Higher Institute of Health Sciences, Hassan 1st Settat University (2015-2017).

💼 Experience:

Soukaina has accumulated substantial research experience through various internships. She completed a research internship at the Microbiology Laboratory CHU MVI Marrakesh in February 2024, focusing on the antibacterial, antifungal, and antioxidant activities of chitosans. From April 2021 to January 2024, she interned at the LIRBM laboratory of the National School of Education (ENS), where she worked on the preparation and characterization of chitins and chitosans from insects and marine waste. In 2019, she had an operational internship at the Microbiology Laboratory CHU MVI Marrakesh, where she developed evaluation grids according to ISO15189 standards and performed comprehensive sample analysis procedures.

🔬 Research Interests:

Soukaina’s research interests include the study of chitosans’ physicochemical properties, biochemistry, microbiology, and the development of pharmaceutical and paramedical applications. She is particularly focused on optimizing extraction conditions and characterizing chitosans derived from various sources.

📚 Publications Top Notes:

Valorization of Hermetia illucens breeding rejects by chitins and chitosans production. Influence of processes and life cycle on their physicochemical characteristics – International Journal of Biological Macromolecules, 2024.

Cited by: Articles on chitosan production and applications.

Extraction of chitin, preparation of chitosan and their structural characterization – Handbook of Natural Polymers, Volume 1, Elsevier, 2023.

Cited by: Research on natural polymer extraction and applications.

Investigation of the desert locust (Schistocerca gregaria) and its different morphological parts as a chitinous source – Submitted to Polymer Bulletin.

Cited by: Pending publication, expected to influence studies on chitin sources.

Manikandan | Civil Engineering Award | Best Researcher Award

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Mr k manikandan | Civil Engineering Award | Best Researcher Award

Mr k manikandan , national institute of technology puducherry , India 

K Manikandan is a research scholar at the National Institute of Technology Puducherry, India, specializing in the preservation of masonry heritage structures, particularly minarets. His research focuses on structural analysis, earthquake engineering, and machine learning applications in heritage conservation. Manikandan has developed a pioneering machine learning model to analyze and safeguard slender heritage structures, contributing significantly to architectural preservation. His work, published in a prestigious journal, utilizes digital documentation and ontological frameworks to mitigate structural risks. 🏛️🌍

Publication Profile

Scopus

Professional Background

K MANIKANDAN is deeply passionate about heritage preservation, showcasing expertise in structural analysis, earthquake engineering, and machine learning. His dedicated efforts are focused on safeguarding iconic architectural elements that hold immense cultural and religious significance. 🏛️ Through his research, he aims to ensure the longevity and resilience of masonry heritage structures, with a particular emphasis on minarets. This interdisciplinary approach integrates advanced engineering principles with historical preservation, addressing challenges posed by natural disasters and environmental factors. K MANIKANDAN’s work not only contributes to the preservation of tangible heritage but also fosters greater understanding and appreciation of architectural diversity across communities.

 

Research Focus

K MANIKANDAN’s research falls under the category of Structural Analysis and Machine Learning. 🏗️ His study focuses on the fundamental frequency formulation and modeling of masonry slender structures, employing a comparative analysis of machine learning and regression techniques. By exploring these advanced methodologies, he aims to enhance the understanding of structural dynamics and behavior in heritage buildings, particularly minarets. This research not only contributes to the field of earthquake engineering but also supports the preservation efforts of cultural and historical landmarks. Through innovative approaches, K MANIKANDAN seeks to ensure the resilience and longevity of these architectural treasures for future generations.

Publication Top Notes

“Fundamental frequency formulation and modeling of masonry slender structures: A comparative study of machine learning and regression techniques”