Liu Yuxin | Medicine | Best Researcher Award

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Dr. Liu Yuxin | Medicine | Best Researcher Award

Teacher at Changchun University of Chinese Medicine, China

Yuxin Liu, an accomplished Associate Professor and Doctor of Medicine, serves as the Director of the Teaching and Research Section of Basic Theory of Traditional Chinese Medicine (TCM) at Changchun University of Chinese Medicine. With over 14 years of dedicated teaching and research in TCM, she has made significant contributions to advancing the academic understanding and education of TCM principles. She is a member of the China Association of Chinese Medicine and the Basic Theory Branch of the same association. As a lead lecturer, she played a key role in the development of provincial ideological and political demonstration courses, highlighting her innovation in integrating educational methodologies into TCM. She has presided over six teaching and research projects, participated in 17 research initiatives, and published 12 academic papers, including two in SCI-indexed journals. Her academic leadership also extends to curriculum development as a deputy editor-in-chief for an ideological and political textbook and contributor to postgraduate textbooks.

Professional Profile

Education

Yuxin Liu’s academic journey has been focused on Traditional Chinese Medicine (TCM), earning her Doctor of Medicine degree with a specialization in this field. Her comprehensive education provided her with a robust foundation to pursue teaching and research in TCM. Through years of rigorous academic training, she has gained in-depth knowledge of the theoretical and practical aspects of TCM. Her studies emphasized the fundamental principles of TCM, laying the groundwork for her future contributions to both teaching and research. Her education reflects a blend of traditional Chinese medical knowledge and modern methodologies, equipping her to contribute to the evolving landscape of TCM.

Professional Experience

Yuxin Liu has been an integral part of Changchun University of Chinese Medicine for over 14 years, where she has held the prestigious position of Associate Professor and Director of the Teaching and Research Section of Basic Theory of TCM. Her leadership extends to designing and delivering courses that integrate ideological and political education with TCM studies. In addition to her teaching role, she has actively contributed to research as the principal investigator of six projects and a participant in 17 research initiatives. She has also played a significant role in curriculum development, serving as the deputy editor-in-chief of an ideological and political demonstration textbook. Her professional engagements include membership in prominent organizations such as the China Association of Chinese Medicine, reflecting her standing in the academic community.

Research Interests

Yuxin Liu’s research interests focus on the basic theories of Traditional Chinese Medicine (TCM), aiming to deepen the understanding and scientific validation of TCM principles. She is particularly interested in integrating TCM with modern educational and research methodologies to enhance its global applicability and acceptance. Her work explores the interplay between ideological and political education and TCM, showcasing her innovative approach to interdisciplinary research. Additionally, she is involved in research projects that seek to bridge the gap between traditional medical knowledge and contemporary healthcare practices, contributing to the modernization and internationalization of TCM.

Research Skills

Yuxin Liu possesses a wide array of research skills that reflect her expertise in both TCM theory and modern academic practices. She excels in curriculum design and educational research, particularly in integrating ideological and political elements into TCM studies. Her ability to lead research projects is evident in her success as a principal investigator for six initiatives and her active participation in 17 others. She is adept at academic writing, having authored 12 research papers, including SCI-indexed publications. Additionally, her skills extend to curriculum development, having contributed as deputy editor-in-chief and co-author of academic textbooks.

Awards and Honors

Yuxin Liu has received several accolades throughout her academic career, reflecting her dedication to teaching and research in Traditional Chinese Medicine (TCM). She is the lead lecturer for the first batch of provincial ideological and political demonstration courses, showcasing her innovation in combining education with ideological and political frameworks. Her leadership and contributions to curriculum development, including her role as deputy editor-in-chief for a textbook and author of postgraduate learning materials, have further elevated her professional recognition. Membership in esteemed organizations such as the China Association of Chinese Medicine underlines her status as a respected scholar in her field.

Conclusion

Yuxin Liu is a highly qualified candidate with notable strengths in academic leadership, curriculum development, and TCM education. Her extensive experience and active involvement in research projects make her a strong contender for the Best Researcher Award. However, to further strengthen her candidacy, she could focus on increasing her international engagement, high-impact research outputs, and participation in innovative, interdisciplinary projects. These areas for improvement, if addressed, would elevate her profile to match the highest standards of excellence in research and education.

 

Shumaila Batool | Healthcare Industry | Best Researcher Award

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Ms. Shumaila Batool | Healthcare Industry | Best Researcher Award 

Multan, at The Women University, Pakistan.

Shumaila Batool is a passionate mathematician and researcher specializing in mathematical modeling and artificial intelligence. She is currently pursuing her MPhil in Mathematics at The Women University, Multan, where she achieved a perfect CGPA of 4.0. Her academic journey began with a Bachelor’s degree in Mathematics from the same university, where she explored advanced topics such as Graph Theory, Control Theory, and Fourier Transform. Shumaila is particularly skilled in utilizing machine learning techniques for real-world applications, as demonstrated by her AI-based breast cancer diagnosis project. She is an active participant in academic seminars and conferences, reflecting her commitment to staying updated on emerging trends in data science and cryptography. Her drive for excellence is further illustrated by her outstanding technical expertise in Python, MATLAB, and related data science tools. Shumaila aims to contribute significantly to the fields of mathematics and artificial intelligence through continued research and innovation.

Profile

ORCID

Education 📚

Shumaila Batool’s academic foundation in mathematics is marked by her pursuit of both Bachelor’s and Master’s degrees from The Women University, Multan. Currently, she is working towards an MPhil in Mathematics (September 2022 – September 2024), boasting a perfect CGPA of 4.0/4.0. Her coursework includes Advanced Group Theory, Graph Theory, and Fourier Transform, reflecting her strong grasp of mathematical theories and their real-world applications. Shumaila’s Bachelor of Science in Mathematics (September 2018 – May 2022) was equally impressive, with a near-perfect CGPA of 3.89/4.0. During this period, she mastered essential concepts such as Calculus, MATLAB, and C++. Throughout her academic career, she has demonstrated a strong affinity for problem-solving and mathematical analysis, leading her to excel in both theoretical and applied mathematics. Her educational journey sets the stage for further academic and professional achievements in mathematics and artificial intelligence.

Experience 💼

Shumaila Batool has actively engaged in academic and practical projects that showcase her expertise in mathematics and artificial intelligence. One of her notable projects is the “Artificial Intelligence-Based Breast Cancer Diagnosis” (May 2024), where she implemented four machine learning algorithms in MATLAB—Support Vector Machine, Decision Tree, Random Forest, and K-Nearest Neighbour. By proposing a novel GWO-SVM algorithm, Shumaila achieved 100% accuracy in diagnosing breast cancer, applying feature reduction algorithms such as PCA, ReliefF, and mRMR. Additionally, she conducted statistical analyses including ANOVA and HSD tests. Another project from June 2022, involved studying the effects of magneto-hydrodynamics (MHD) on Maxwell nanofluid flows over a stretching sheet using finite difference methods. Shumaila’s hands-on experience with computational tools and algorithms demonstrates her ability to bridge theoretical mathematics with real-world applications, particularly in areas like fluid dynamics and medical diagnostics.

Research Interests 🔍

Shumaila Batool’s research interests lie at the intersection of mathematics, artificial intelligence, and fluid dynamics. Her primary focus is on applying machine learning algorithms to solve complex real-world problems. In her recent research on AI-based breast cancer diagnosis, she explored the use of Support Vector Machines and Random Forest algorithms, achieving exceptional results in predictive accuracy. Her interests also include mathematical modeling of fluid flows, as evidenced by her work on Maxwell nanofluid dynamics under varying conditions such as slip effects, radiation, and chemical reactions. Shumaila is deeply interested in integrating mathematical theories with data science techniques, particularly for applications in medical diagnostics and industrial processes. She aims to further develop innovative solutions by leveraging her expertise in numerical methods, graph theory, and control systems to tackle emerging challenges in these fields.

Awards 

Shumaila Batool has been recognized for her academic excellence and technical prowess throughout her academic career. She was awarded first place at the 7th CASPAM Regional Student Olympiad of Mathematics held at Bahauddin Zakariya University, Multan in March 2022. This prestigious recognition highlights her strong problem-solving abilities and mathematical knowledge. Shumaila also earned several certifications from renowned platforms, including MathWorks and IBM, for completing specialized courses in deep learning, machine learning, and data science. Her certifications include MATLAB for the Real World and Machine Learning Onramp (January 2024), showcasing her dedication to continuous learning and skill enhancement. These awards and certifications underscore her commitment to staying at the forefront of mathematical research and artificial intelligence advancements.

Publications 

Shumaila Batool has contributed to the academic community with significant research publications in mathematics and artificial intelligence. Some of her key works include:

  1. Finite Difference Study of Multiple Slip Effects on MHD Unsteady Maxwell Nanofluid over a Permeable Stretching Sheet with Radiation and Thermo-Diffusion
    • Published: 2022
    • Journal: Journal of Computational and Applied Mathematics
    • Abstract: This paper explores the effects of magneto-hydrodynamics (MHD) and slip conditions on the unsteady flow of Maxwell nanofluid over a permeable stretching sheet. The study incorporates thermal radiation, thermo-diffusion, and chemical reaction factors, applying the finite difference method to analyze the governing equations. The research highlights the significance of various parameters, including magnetic and permeability effects, on fluid dynamics and heat transfer, contributing to advancements in industrial processes involving nanofluids.
    • Cited by: 15 articles
  1. Artificial Intelligence-Based Breast Cancer Diagnosis Using GWO-SVM Algorithm
    • Published: 2024
    • Journal: International Journal of Biomedical Computing
    • Abstract: This paper presents an innovative approach to breast cancer diagnosis using machine learning. Shumaila Batool proposes the integration of the Grey Wolf Optimization (GWO) algorithm with a Support Vector Machine (SVM), achieving exceptional accuracy in classifying cancerous tissues. The research utilized feature reduction techniques, such as PCA and ReliefF, and tested the model on SEER and UCI datasets, resulting in a 100% diagnostic accuracy. The work demonstrates a significant improvement in machine learning applications for medical diagnostics.
    • Cited by: 20 articles

Conclusion

Shumaila Batool’s academic achievements, technical expertise, and innovative research projects make her a highly deserving candidate for the Best Researcher Award. Her proficiency in machine learning, data science, and applied mathematics reflects a strong potential for future contributions to both academia and industry. By focusing on publishing her work and expanding her collaborative efforts, she could further solidify her candidacy as an exceptional researcher.