I am Mohamad Amin Pourhoseingholi, Medical Statistician at the University of Nottingham, with over a decade of experience in biostatistics, recognized among the Stanford/Elsevier Top 2% Scientists. With 290+ publications, I specialize in predictive modeling, cancer survival analysis, and healthcare data innovation, driving impactful research to advance global health outcomes. I am a Medical Statistician at the University of Nottingham, specializing in applying advanced statistical methods to biomedical research, with a focus on neurodegenerative diseases, autoimmune disorders, and cancers. My work aims to bridge the gap between innovative research and practical applications, driven by a passion for improving healthcare outcomes through robust data analysis. What sets me apart is my interdisciplinary expertise, combining a strong foundation in molecular biology with advanced biostatistical modeling. This unique perspective enables me to tackle complex biomedical challenges with innovative solutions, ensuring that research findings translate into meaningful clinical advancements. I have published over 290 articles, with numerous contributions as the first or corresponding author in leading academic journals. My work has been cited more than 8,000 times, reflected in a Google Scholar H-index of 44. I have delivered multiple presentations at international conferences and am recognized among Stanford/Elsevier's Top 2% Scientists in 2023 and 2024. My research spans cancer survival analysis, predictive modeling, and chronic disease cost-effectiveness. I have contributed significantly to academic journals by peer reviewing over 150 manuscripts, ensuring the quality and rigor of published research. Additionally, I have authored several editorials (more than 10 published ones), providing insights into emerging trends in biostatistics and public health, further establishing my role as a thought leader in advancing healthcare research. My personal and professional goals center on advancing global health through innovative research and impactful collaborations. I am primarily engaged in secondary data analysis, leveraging extensive datasets like the Global Burden of Disease (GBD) to explore cancer epidemiology, chronic disease burden, and healthcare cost-effectiveness. My long-term research aims to inform evidence-based policies and improve health outcomes worldwide. I bring a unique blend of technical expertise and professional skills to my work as a Medical Statistician. My active listening and communication skills foster effective collaboration across multidisciplinary teams, ensuring clarity and shared understanding in complex research projects. My interpersonal and mentoring skills have been instrumental in guiding junior researchers and colleagues, supporting their professional growth and contributing to successful team dynamics. With strong leadership abilities, I have led national projects, such as cancer burden analysis. In my free time, I enjoy writing stories, particularly exploring themes that blend imagination with meaningful life lessons. I also have a passion for reading science fiction novels.