Yu Ni | Biology | Best Researcher Award

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Dr. Yu Ni | Biology | Best Researcher Award

Qingdao Agricultural University | China

Dr. Yu Ni is a highly accomplished professor at the College of Agronomy, Qingdao Agricultural University, China, with extensive experience in plant stress biology, molecular genetics, and biochemistry, particularly focusing on drought tolerance, cuticular wax biosynthesis, and stress adaptation mechanisms in key crops such as Arabidopsis, Brassica napus, and Sorghum bicolor. She earned her Ph.D. in Agronomy from Southwest University, Chongqing, and has since held prominent academic positions, including a professorship at Southwest University before joining Qingdao Agricultural University. Dr. Ni has an outstanding record of teaching both undergraduate courses, including Plant Physiology, Biochemistry, and Molecular Biology, and graduate courses such as Molecular Genetics, while supervising numerous student research projects. Her research skills are reflected in her leadership of multiple national and international projects, extensive collaborations with global research teams, and her proficiency in multi-omics analyses, gene expression profiling, and plant physiological assessments. She has authored over 40 high-impact publications in reputed journals including New Phytologist, Plant Biotechnology Journal, Plant, Cell & Environment, and BMC Plant Biology, with key contributions to understanding plant drought tolerance and cuticular wax regulation. Dr. Ni’s professional memberships, mentorship roles, and community involvement further demonstrate her dedication to advancing plant science and fostering the next generation of researchers. Her awards and honors, including the Best Researcher Award, recognize her sustained impact on both scientific discovery and education. Areas for future improvement include expanding publications in Q1 journals, increasing international collaborations, and engaging in more keynote presentations and editorial responsibilities. Overall, Dr. Yu Ni is exceptionally deserving of the Best Researcher Award due to her innovative contributions to plant molecular biology, her leadership in research and mentorship, and her potential to drive global advancements in plant stress biology through continued research excellence and international engagement.

Profile: Scopus

Featured Publications

Ni, Y., et al. (2025). Enhancing sweet sorghum emergence and stress resilience in saline-alkaline soils through ABA seed priming: Insights into hormonal and metabolic reprogramming. BMC Genomics.

Ni, Y., Jin, S., Wang, Y., Song, Y., Fan, S., Luo, N., Gan, Q., & Guo, Y. (2025). Dual regulation of cuticle and cell wall biosynthesis by BnaC9.MYB46 confers drought tolerance in Brassica napus. Plant Biotechnology Journal.

Luo, N., Wang, Y., Liu, Y., Wang, Y., Guo, Y., Chen, C., Gan, Q., Song, Y., Fan, Y., Jin, S., & Ni, Y. (2024). 3-ketoacyl-CoA synthase 19 contributes to the biosynthesis of seed lipids and cuticular wax in Arabidopsis and abiotic stress tolerance. Plant, Cell & Environment, 47, 4599–4614.

Saba Amiri | Biology | Best Researcher Award

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Assist. Prof. Dr. Saba Amiri | Biology | Best Researcher Award

Shahid Beheshti University of Medical Sciences | Iran

Assist. Prof. Dr. Saba Amiri, an accomplished biomedical engineer and neuroscientist, has established herself as a leading figure in biomedical engineering, neuroimaging, and neuroscience research. She earned her Ph.D. in Biomedical Engineering from Tehran University of Medical Sciences  and her M.Sc. in Biomedical Engineering from Shiraz University of Medical Sciences , where she consistently ranked among the top students in her cohort. Professionally, Dr. Amiri has served as Assistant Professor at the Neuroscience Research Center of Shahid Beheshti University of Medical Sciences since , while previously holding roles as research assistant, clinical researcher, and lecturer at leading Iranian universities and hospitals. She has also collaborated with international institutions such as the University of Antwerp, contributing to longitudinal fMRI studies on Alzheimer’s disease. Her research interests include biomedical engineering, neural engineering, neurorehabilitation, medical imaging, machine learning, deep brain stimulation, and the use of artificial intelligence in clinical neuroscience. Skilled in neuroimaging software such as SPM, FSL, DPARSF, and BRAPH, along with proficiency in Matlab, Python, and C#, she applies advanced computational and statistical methods to investigate brain connectivity, psychiatric disorders, and neurodegenerative diseases. Dr. Amiri’s work has produced impactful publications in prestigious journals such as npj Aging, Epilepsy & Behavior, Progress in Neuro-Psychopharmacology and Biological Psychiatry, and Annals of General Psychiatry, alongside presentations at IEEE EMBC conferences. Her excellence has been recognized through numerous awards, including first rank in the national Ph.D. entrance exam in biomedical engineering, the Best Platform Presentation Award, and first place in the Value Creation of Clinical Research competition at the Brain Mapping Symposium. With her strong academic background, technical expertise, and dedication to advancing neuroscience, Dr. Amiri exemplifies the qualities of an innovative scholar and is highly deserving of the Best Researcher Award for her outstanding contributions to science and society.

Profile: Orcid | Google Scholar

Featured Publications

Amiri, S., Arbabi, M., Kazemi, K., Parvaresh-Rizi, M., & Mirbagheri, M. M. (2021). Characterization of brain functional connectivity in treatment-resistant depression. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 111, 110346.

Amiri, S., Mirbagheri, M. M., Asadi-Pooya, A. A., Badragheh, F., Zibadi, H. A., & others. (2021). Brain functional connectivity in individuals with psychogenic nonepileptic seizures (PNES): An application of graph theory. Epilepsy & Behavior, 114, 107565.

Amiri, S., Mehvari-Habibabadi, J., Mohammadi-Mobarakeh, N., & others. (2020). Graph theory application with functional connectivity to distinguish left from right temporal lobe epilepsy. Epilepsy Research, 167, 106449.

Amiri, S., Movahedi, M. M., Kazemi, K., & Parsaei, H. (2017). 3D cerebral MR image segmentation using multiple-classifier system. Medical & Biological Engineering & Computing, 55(3), 353–364.

Zareie, M., Parsaei, H., Amiri, S., Awan, M. S., & Ghofrani, M. (2018). Automatic segmentation of vertebrae in 3D CT images using adaptive fast 3D pulse coupled neural networks. Australasian Physical & Engineering Sciences in Medicine, 41(4), 1009–1020.