Mr. John Rowen Miano | Statistics | Best Researcher Award
Mr. John Rowen Miano | Statistics – Student at Cebu Technological University, Philippines
John Rowen Miano is an aspiring early-career researcher whose work sits at the intersection of computational biology and agricultural science. Based at Cebu Technological University, he is known for applying mathematical and computational tools to explore natural product chemistry, particularly in the field of agrochemical development. His independent research using molecular docking techniques to investigate plant-derived inhibitors has drawn academic interest and showcases his potential as a young innovator in sustainable agriculture. His initiative, curiosity, and analytical mindset distinguish him among his peers, making him a promising candidate for future academic and scientific excellence.
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Education:
John is currently pursuing his studies at Cebu Technological University under the Department of Mathematics and Statistics. His academic focus blends quantitative analysis with biological research, giving him a unique edge in computational studies. Through coursework and project-based learning, he has developed strong foundations in mathematics, statistics, and bioinformatics—skills that are critical for in silico research and predictive modeling. His education emphasizes both theoretical understanding and practical application, which is evident in his recent research outputs.
Experience:
John’s primary experience comes from his involvement as a student researcher at his university. During this time, he has conducted independent and guided research focused on plant-based antimicrobial agents. He has experience in molecular docking, virtual screening, database preparation, and software tools such as AutoDock and PyRx. His work has been presented at conferences and shared on academic platforms like Zenodo. He has collaborated with faculty for project feedback and scientific validation, and he is gradually building a network of fellow researchers within his institution.
Research Interests:
John’s research interests include molecular docking, phytochemistry, plant pathology, and the computational screening of bioactive compounds. He is particularly focused on identifying eco-friendly alternatives to synthetic agrochemicals by analyzing the inhibitory effects of natural phytochemicals against plant pathogens. His current study involves the evaluation of Euphorbia tirucalli compounds against Xanthomonas oryzae, the causative agent of bacterial leaf blight in rice. His broader interests also include artificial intelligence applications in drug discovery, sustainable agriculture, and the use of statistical models to predict pathogen resistance.
Awards:
As an emerging researcher, John has not yet received formal awards; however, he has been recognized at the university level for research presentation and participation. His poster presentation at a recent academic conference has gained early citations, demonstrating the relevance and growing academic attention toward his work. His nomination for the “Best Researcher Award” reflects both his existing achievements and the future potential that he holds as a developing scientific contributor.
Publications 📚:
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🧪 Phytochemicals of Euphorbia tirucalli and their Inhibitory Potential against Xanthomonas oryzae Ddl Enzyme: An In silico Evaluation for Potential Agrochemical
📅 Published: 2024 | Platform: Zenodo
🔗 DOI: 10.5281/ZENODO.12183931
📌 Cited by 2 articles
Conclusion:
John Rowen Miano is a highly motivated and intellectually capable young researcher. His contributions—although still at the early stage—exemplify innovation, relevance, and commitment to solving real-world agricultural problems. With a strong foundation in mathematical sciences and a growing body of work in computational biology, he is poised to become a key contributor to sustainable agrochemical discovery. His single-author research, proactive approach, and dedication to scientific exploration make him a strong nominee for the “Best Researcher Award” under an early-career or emerging talent category. He represents the next generation of researchers who merge computational power with natural science to address urgent agricultural and environmental challenges.