Napoleon Bellua Sam | Epidemiology and Biostatistics | Best Researcher Award

Posted on by Shen Awards

Dr. Napoleon Bellua Sam | Epidemiology and Biostatistics | Best Researcher Award

University for Development Studies, Tamale, Ghana.

Dr. Napoleon Bellua Sam is a biostatistician, epidemiologist, and Senior Lecturer at the University for Development Studies (UDS), Ghana. With a Ph.D. in Epidemiology and Biostatistics, he has significant expertise in medical research, data governance, biostatistical modeling, and public health analytics. Dr. Sam has held roles including Research Development Officer and Statistician at UDS, and Senior Tutor at the University of Cape Coast. He has led multiple impactful research projects on disease trends, healthcare efficiency, and treatment adherence. Internationally engaged, he serves as Co-PI for the NIHR Global Health Group on equitable healthcare and actively contributes to workshops, editorial boards, and training programs across Africa and Asia. Dr. Sam’s work aims to enhance healthcare systems through advanced statistical applications and evidence-based practices, with a strong passion for mentoring and capacity building in research and academia.

Professional Profile

Education

Dr. Napoleon Bellua Sam holds a Ph.D. in Epidemiology and Biostatistics from Anhui Medical University, China (2017–2020), a Master’s degree in Industrial Mathematics from Kwame Nkrumah University of Science and Technology, Ghana (2010–2012), and a BSc. in Statistics from the University of Cape Coast (2004–2008). He also earned a Higher National Diploma in Electrical/Electronic Engineering from Takoradi Polytechnic (2000–2003). In addition to his formal education, Dr. Sam has undertaken extensive global training through short courses on biostatistics, research ethics, statistical software, data management, climate science, and machine learning in countries such as Kenya, India, Nigeria, and South Africa. He also holds a diploma in Pastoral Counseling from Rhema Leadership Institute and is a ministerial candidate at Trinity Theological Seminary. These multidisciplinary credentials have shaped his expertise in statistical analysis, epidemiological modeling, and health research governance, enabling his leadership in academic and public health research domains across Africa and beyond.

Professional Experience

Dr. Napoleon Bellua Sam has amassed over 15 years of academic and research experience. He currently serves as a Senior Lecturer in the Department of Medical Research and Innovation at UDS. Previously, he was Research Development Officer (2016–2021) and Assistant Research Development Officer (2014–2016) at UDS. He also worked as a Senior Technician (Statistician) from 2009–2014. Concurrently, he has been a Senior Tutor at the University of Cape Coast’s Center for Distance Education since 2012. His academic contributions include teaching graduate-level courses in Biostatistics, Research Methods, and Health Statistics. Earlier in his career, he completed national service at Takoradi Polytechnic and the University of Cape Coast. His diverse roles have allowed him to bridge teaching, statistical consultancy, and research administration. Dr. Sam’s teaching and leadership roles underscore his commitment to enhancing academic excellence, research productivity, and evidence-informed policy-making in health and education systems.

Research Interests

Dr. Napoleon Bellua Sam’s research focuses on applying advanced biostatistics and epidemiological methods to improve public health outcomes, particularly in resource-limited settings. His current projects explore the efficiency of healthcare delivery using data envelopment analysis, longitudinal quality of life assessments among leprosy patients, and statistical modeling of disease patterns such as cerebrospinal meningitis in Northern Ghana. He applies survival analysis, structural equation modeling, and time-series forecasting in his studies. Dr. Sam is also engaged in systematic reviews and meta-analyses, particularly in inflammatory biomarkers like myeloperoxidase in rheumatoid arthritis patients. His research supports decision-making in health policy and planning. As Co-PI of the NIHR Equi-Injury project, his work centers on equitable healthcare access for injured populations across low- and middle-income countries. Passionate about data science for health systems strengthening, Dr. Sam continuously integrates machine learning and modern analytics to address complex healthcare challenges in Africa and beyond.

Awards and Honors

Dr. Napoleon Bellua Sam has been honored with multiple prestigious awards and grants. He was named Best Postgraduate Foreign Student upon graduation from Anhui Medical University in 2020 and served as Alumni Liaison Ambassador for Ghana and Africa graduates of the university. He received a fully funded Ph.D. scholarship from the Chinese Scholarship Council in 2017. He has secured several competitive international grants, including travel and training grants from institutions such as NIHR Global Surgery Unit, NAMBARI/DSSD, and the Data Science Initiative for Africa. These funded his participation in workshops on machine learning, climate change, health systems, and statistical data analysis in countries like Kenya, Nigeria, South Africa, India, and Liberia. As a Co-PI of the NIHR Global Health Group project, he is currently involved in a multi-country research program on equitable access to quality healthcare, managing a substantial grant of over £213,000. These recognitions affirm his impactful contributions to global health research.

Publications Top Notes

Dr. Masoumeh Javanbakhat | Digital Health | Best Researcher Award

Posted on by Shen Awards

Dr. Masoumeh Javanbakhat | Digital Health | Best Researcher Award

Postdoctoral Researcher at Digital Health, Hasso Plattner Institute, Germany

Masoumeh Javanbakhat is a Postdoctoral Research Fellow at the Hasso-Plattner-Institute, specializing in Digital Health and Machine Learning. Her research focuses on applying machine learning techniques to digital health applications, with a particular interest in probabilistic AI, Bayesian deep learning, and modeling uncertainties in computer vision and medical images. Masoumeh’s work aims to improve healthcare outcomes through innovative technology and data analysis.

Professional Profiles:

Education:

Dr. Masoumeh Javanbakhat completed her Bachelor of Science in Applied Mathematics at Isfahan University, Iran, from 2005 to 2009. She pursued a Master of Science degree at Shahed University, Iran, from 2009 to 2012, focusing on Mathematics, with a thesis on combinatorial designs for key distribution in wireless sensor networks. Dr. Javanbakhat then completed her Ph.D. studies at Hakim Sabzevari University, Iran, from 2013 to 2018, under the guidance of Dr. Amir Hashemi, Dr. Leila Sharifan, and Prof. H. Michael Möller, with a thesis on the symbolic computation of H-bases, Gröbner bases, and minimal bases for syzygies. She collaborated as a Research Collaborator at Passau University, Germany, during 2017-2018, working on the numerical computation of H-bases. Currently, she is a Postdoctoral Research Fellow at the Hasso-Plattner-Institute in Potsdam, Germany, under the mentorship of Prof. Christoph Lippert, focusing on Probabilistic AI, Bayesian deep learning, and modeling uncertainties with applications in computer vision and medical images.

Honors:

Dr. Masoumeh Javanbakhat has received several honors throughout her academic career. She was awarded the Best PhD Graduate by the Faculty of Mathematics and Computer Science at Hakim Sabzevari University, Iran, in 2018. In 2017, she won the Award of University of Passau Research Collaboration from the Ministry of Science, Research, and Technology of Iran. Dr. Javanbakhat achieved a ranking of 1 out of 25 among Ph.D. students at Hakim Sabzevari University in 2018, demonstrating her academic excellence. During her Master’s studies at Shahed University, Iran, she was ranked 3 out of 20 among M.Sc. students in 2012. Similarly, during her Bachelor’s studies at Isfahan University, Iran, she was ranked 3 out of 20 among B.Sc. students in 2009. These honors reflect her outstanding academic performance and dedication to her field.

Academic Experience:

Dr. Masoumeh Javanbakhat has a strong background in academia, with experience both as a teacher and a researcher. From 2021 to 2023, she served as a Teaching Assistant for Mathematics for Machine Learning at the Hasso-Plattner-Institute. Prior to this, she worked as a Research Collaborator at the University of Passau, Germany, under the guidance of Prof. Tomas Sauer, from 2017 to 2018. Dr. Javanbakhat also has experience as an Instructor in Numerical Computation at Amin University from 2018 to 2019. She further enhanced her teaching skills as a Teaching Assistant for Computational Algebra at Isfahan University of Technology from 2018 to 2019, and for Basics of Algebra as well as Basics of Combinatorics at Shahed University from 2012 to 2013. Her academic experience demonstrates her dedication to both learning and teaching in the field of mathematics.
🔧 Programming: Python, MATLAB, Maple
💻 VSC & OS: Git, Linux, Unix
📊 Technical Skills: Data Analysis using Scikit-Learn, NumPy, Pandas, Matplotlib, Seaborn
🤖 Machine Learning: Supervised and Unsupervised Learning, Deep Learning, Computer Vision, Probabilistic AI, Bayesian Deep Learning, PyTorch, Weights and Biases
📚 Courses: Python, Deep Learning, Machine Learning, Probabilistic AI, AI for Medical Diagnosis
📜 Certifications: Hands-on Machine Learning with AWS and NVIDIA (In progress)
🧠 Soft Skills: Problem-solving, critical thinking, innovation, and creativity; Ability to deal with complexity and ambiguity; Communication and supervising

Publications:

  1. Key predistribution scheme for clustered hierarchical wireless sensor networks based on combinatorial designs
    1. Authors: M Javanbakht, H Erfani, HHS Javadi, P Daneshjoo
    2. Citations: 17
    3. Year: 2014
  2. Numerical computation of H-bases
    1. Authors: M Javanbakht, T Sauer
    2. Citations: 8
    3. Year: 2019
  3. On the construction of staggered linear bases
    1. Authors: A Hashemi, M Javanbakht
    2. Citations: 3
    3. Year: 2021
  4. On -Closed Graphs
    1. Authors: L Sharifan, M Javanbakht
    2. Citations: 3
    3. Year: 2017
  5. A probabilistic approach to self-supervised learning using cyclical stochastic gradient MCMC
    1. Authors: M Javanbakhat, C Lippert
    2. Citations: 1
    3. Year: 2023
  6. Computing H-bases via minimal bases for syzygy modules
    1. Authors: A Hashemi, M Javanbakht
    2. Citations: 1
    3. Year: 2020
  7. Algebraic invariants of certain projective monomial curves
    1. Authors: M Javanbakht, L Sharifan
    2. Citations: 1
    3. Year: 2019