Prof. Junyu Zhou | Medical and Prevention | Young Scientist Award

Peking University, China.

Prof. Junyu Zhou is a pioneering researcher in nutritional genomics, metabolic disorders, and personalized medicine. He leverages bioinformatics, computational biology, and experimental approaches to explore gene-diet interactions, focusing on Asian populations. His innovative work includes developing AI models for bioactive compound prediction and uncovering gut microbiota's role in metabolic health. Junyu's recent research extends to natural compound discovery for neurodegenerative diseases, emphasizing computational screening with advanced AI techniques.

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Education 🎓

Junyu Zhou holds advanced degrees in fields related to nutritional genomics and computational biology. His academic training provides a strong foundation for his cutting-edge research in metabolic disorders and personalized medicine.

Experience 💼

As an Assistant Researcher at Peking University, Junyu Zhou has led and collaborated on multiple groundbreaking projects. His experience spans computational modeling, experimental validations, and interdisciplinary collaborations with global research teams in metabolic diseases and nutritional genomics.

Research Interests 🔬

Nutritional Genomics 🧬

Junyu Zhou investigates gene-diet interactions to understand how genetic variations influence nutritional responses, particularly in Asian populations. His work aims to develop personalized dietary recommendations to improve health outcomes.

Metabolic Diseases 🩺

Focusing on conditions such as diabetes and obesity, Junyu studies the underlying mechanisms of metabolic disorders. His research integrates genetics and gut microbiota to unveil new therapeutic targets.

Computational Biology & Bioinformatics 💻

Junyu applies advanced computational tools to analyze genetic data and predict drug-target interactions. His expertise in bioinformatics helps bridge data science and biology for innovative discoveries.

Gut Microbiota 🌱

Exploring the role of gut microbiota in metabolic health, Junyu's research uncovers microbial contributions to diseases and identifies probiotic strategies for improved metabolic functions.

Natural Product Research 🌿

Junyu's work includes computational screening of natural compounds, focusing on their potential to treat diseases such as Alzheimer's and neurodegenerative disorders.

Personalized Medicine 🩹

By integrating genomics and computational biology, Junyu develops precision healthcare approaches, tailoring interventions to individual genetic and metabolic profiles.

Machine Learning in Drug Discovery 🤖

Junyu employs AI-driven techniques to streamline drug discovery processes. His work includes predictive models for bioactive compounds, enhancing efficiency in identifying new therapeutic agents.

Publications Top Notes 📚

Microbial Dysbiosis Linked to Metabolic Dysfunction-Associated Fatty Liver Disease in Asians: Prevotella copri Promotes Lipopolysaccharide Biosynthesis and Network Instability in the Prevotella Enterotype, Published in: International Journal of Molecular Sciences, 2024, Contributors: Yuan, H.; Wu, X.; Wang, X.; Zhou, J.-Y.; Park, S. Link

Predicting structure-targeted food bioactive compounds for middle-aged and elderly Asians with myocardial infarction: insights from genetic variations and bioinformatics-integrated deep learning analysis, Published in: Food & Function, 2024, Contributors: Junyu Zhou; Heng Yuan; Sunmin Park. Link

Association of Metabolic Diseases and Moderate Fat Intake with Myocardial Infarction Risk, Published in: Nutrients, December 11, 2024, Contributors: Junyu Zhou; Meiling Liu; Sunmin Park. Link

Prof Dr. Xiaochun Li | Biomedical | Best Researcher Award

Associate Dean, Taiyuan University of Technology, China

Dr. Xiaochun Li is a Professor at the Department of Biomedical Engineering, TaiYuan University of Technology, Shanxi, China. With an extensive background in biomedical sensors and analytical chemistry, Dr. Li has made significant contributions to the field through innovative research and teaching. He has received multiple awards for his work, including the Second Prize of the Shanxi Provincial Natural Science Award and recognition as the “2021 Annual Science and Technology Innovation Person.” His research focuses on developing cutting-edge technologies for disease diagnosis and public health.

Profile

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Education 🎓

Dr. Xiaochun Li earned his Ph.D. in Biomedical Engineering, specializing in analytical chemistry and sensor technology. His educational journey laid a strong foundation for his future research and academic career, leading to his current position as a professor at TaiYuan University of Technology.

Experience 🧑‍🏫

Professor, TaiYuan University of Technology, Shanxi, China (2014-present): Leading research in biomedical sensors and analytical chemistry.

Associate Professor, TaiYuan University of Technology, Shanxi, China (2009-2014): Conducted advanced research and taught various courses.

Assistant Professor, TaiYuan University of Technology, Shanxi, China (2007-2009): Initiated his academic career, focusing on innovative research in biomedical engineering.

Research Interests 🔬

Dr. Xiaochun Li’s research interests encompass the development of biomedical sensors, optical fluorescence detection technologies, and AI-enhanced biochemical sensing. His work is particularly focused on creating innovative diagnostic tools for early disease detection and public health applications.

Awards 🏆

Second Prize of Shanxi Provincial Natural Science Award (2022)

Outstanding Science and Technology Worker of China Society of Electronics (2019)

Silver Prize of National Science and Technology Workers’ Innovation and Entrepreneurship Competition (2016)

Young Outstanding Talents of Shanxi Province “Three Jin Talents” (2018)

2021 Annual Science and Technology Innovation Person (2022)

Publications Top Notes 📚

Zhang, L. L., Xu, P. T., Li, X. C., Yang, Z. H., Yu, H.-Z.. (2024). Blu-ray disc technology-enabled portable imaging system for immunoassay quantitation. Sens. Actuat. B-Chem., 419, 136376. Cited by 15 articles. link

Wang, C. X., Deng, R., Li, H. Q., Liu, Z. G., Niu, X. F., Li, X. C.. (2024). An integrated magnetic separation enzyme-linked colorimetric sensing platform for field detection of Escherichia coli O157: H7 in food. Microchimica Acta, 191, 454. Cited by 10 articles. link

Li, H. Q., Xu, H., Li, Y. L., Li, X. C.*. (2024). Application of artificial intelligence (AI)-enhanced biochemical sensing in molecular diagnosis and imaging analysis: Advancing and challenges. Trac-Trend. Anal. Chem., 174, 117700. Cited by 12 articles. link

Gao, X. G., Yuan, L., Xue, C. Z., Zhang, X. L., Meng, X. J., Li, X. C.*. (2024). Bubbles-induced porous structure-based flexible piezoresistive sensors for speech recognition. ACS Appl. Mater. Interfaces, 16(7), 9532-9543. Cited by 8 articles. link

L.Y, Gao, X.G., Kang, R.R., Zhang, X.L., Meng, X.J., Li, X. C., Li, X.J.* (2024). Flexible strain sensors based on an interlayer synergistic effect of nanomaterials for continuous and non-invasive blood pressure monitoring. ACS Appl. Mater. Interfaces, 16(10), 10435-10444. Cited by 6 articles. link