Nicholas Otumi | Neuroscience Data Analysis | Best Researcher Award

Mr. Nicholas Otumi | Neuroscience Data Analysis | Best Researcher Award

University of Rochester | United States

Nicholas Otumi is a biomedical imaging researcher with a strong foundation in diagnostic imaging and deep learning. He holds a BSc in Diagnostic Imaging Technology from the University of Cape Coast (Ghana) and an MS in Diagnostic Imaging (Bioengineering & Biomedical Engineering) from the University of Rochester (USA), where his coursework included deep learning, inverse problems in imaging, clinical imaging, and signal processing. He has held research and technical roles at multiple institutions: as a remote Research Assistant at Indiana University working on pharmaceutical pricing and market analytics, and at the University of Rochester contributing to segmentation (with UNet-R) and image analysis in brain CT. Previously, as a Research and Teaching Assistant at UCC, he supported imaging equipment courses, data analysis, and undergraduate research. His research interests center on medical image analysis, especially applying deep learning to brain MRI and CT segmentation, classification of disease from imaging, and imaging in resource-constrained settings. He has several manuscripts under review or published, including a multicentre survey on advanced brain MRI in low-resource settings and case reports in radiology.  He is a recipient of honors such as the Harry W. Fischer Research Funds (2025) and the HSEAS Dean’s Fellowship (2024) at Rochester, as well as campus leadership awards in Ghana. Nicholas is committed to advancing AI-driven neuroimaging and translational imaging research across low- and middle-income settings, aiming to bridge technology gaps and enhance equitable access to advanced diagnostic tools.

Profiles : Orcid | Google Scholar

Featured Publications

Piersson, A. D., Nunoo, G., Dzefi-Tettey, K., & Otumi, N. (2025). Utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting: A multicentre survey. Next Research.

Fiagbedzi, E., Arkorful, J., Brobbey, I. F., Appiah, E., Nyarko, S., Otumi, N., Piersson, A. D., Nimo, O., Ofori, I. N., & Gorleku, P. N. (2025). A case of ruptured infrapatellar bursa sac with Baker’s cyst. Radiology Case Reports, 20(1).

Fiagbedzi, E., Arkorful, J., Appiah, E., Otumi, N., Ofori, I., & Gorleku, P. N. (2024). A rare case of intussusception in a 6-month-old baby. Radiology Case Reports, 19(10).

Naif Majrashi | Best Researcher Award | medical fields/Image and data analysis/Infectious diseases (TB)

 Naif Majrashi - Jazan University - medical fields/Image and data analysis/Infectious diseases (TB)🏆

Assist Prof Dr Naif Majrashi : medical fields/Image and data analysis/Infectious diseases (TB)

Professional profile:

Early Academic Pursuits:

Naif Ali Ahmed Majrashi's academic journey began with a Bachelor of Diagnostic Radiology from Jazan University, Saudi Arabia. Following this, he pursued a Master of Science in Medical Imaging from the University of Aberdeen, UK, where he graduated with commendation. He further enhanced his academic credentials by completing his Ph.D. in Medical Imaging from the same institution, the University of Aberdeen, in 2020. His early academic endeavors laid a solid foundation for his subsequent professional achievements in the field of medical imaging.

Professional Endeavors:

Naif Majrashi has made significant strides in his professional career. Currently serving as an Assistant Professor at Jazan University, Saudi Arabia, he has been instrumental in teaching, research, and administration within the Diagnostic Radiography Technology Department. Additionally, his experience extends to serving as a Laboratory Demonstrator at the University of Aberdeen, UK. Throughout his career, he has showcased expertise in areas such as brain imaging, medical image analysis, machine learning, and radiation protection. His commitment to academic excellence is evident through his involvement in curriculum design, research supervision, and publication in reputable journals.

Contributions and Research Focus:

NM's research focus encompasses several pivotal areas within medical imaging, including brain imaging, environmental effects on the brain, machine learning applications, systematic reviews, and radiation protection. His publications reflect his dedication to advancing the field, with topics ranging from the relationship between chest CT severity score and COVID-19 pneumonia to the impact of photoperiod on brain volume and depressive symptoms. His research contributions have been published in renowned journals, contributing to the broader understanding of medical imaging techniques and applications.

Accolades and Recognition:

Throughout his academic and professional journey, Naif Majrashi has garnered several accolades and certifications that underscore his expertise and commitment to the field. Notably, he holds a Certified Senior Health Specialist in Diagnostic Radiology from the Saudi Commission For Health Sciences, among other certifications. His accomplishments include achieving a Data Driven-Scientist designation from the Massachusetts Institute of Technology (MIT) and a Certified Trainer of Trainees from the Saudi Commission For Health Sciences.

Impact and Influence:

NM's impact extends beyond his research contributions and professional roles. His involvement in teaching, mentoring, and supervising students has shaped the next generation of professionals in medical imaging and related fields. By fostering collaborative research, attending academic conferences, and sharing his expertise, he has contributed to the academic community's growth and development.

Legacy and Future Contributions:

As Naif Ali Ahmed Majrashi continues to advance in his career, his legacy is marked by a dedication to excellence, innovation, and collaboration in the field of medical imaging. His future contributions are anticipated to further shape the landscape of diagnostic radiography, machine learning applications, and research methodologies. Through ongoing research, mentorship, and academic leadership, NM's legacy will continue to inspire advancements in medical imaging and related disciplines.

Notable Publication:

Citations:

A total of 28 citations for his publications, demonstrating the impact and recognition of his research within the academic community.

  • Citations      :28
  • h-index         :12
  • Documents  :3