Andrea Tri Rian Dani | Statistics | Research Excellence Award

Mr. Andrea Tri Rian Dani | Statistics  | Research Excellence Award

Statistics Study Program at Mulawarman University, Indonesia

Mr. Andrea Tri Rian Dani is an academic and lecturer at Mulawarman University since 2022, with a strong background in statistics. He is currently pursuing a Doctorate in Statistics (MIPA) at Airlangga University (2025–present), after completing his Master’s degree in Statistics at the Sepuluh Nopember Institute of Technology and his undergraduate degree in Statistics at Mulawarman University. Over the last five years, he has been actively involved in applied research and development projects with significant industry collaboration. His work includes the Samarinda City Price Monitoring Survey (2022–present) and the Strategic Food Price Information Center Survey (2022–present), both conducted in partnership with Bank Indonesia. Additionally, he contributed to the Survey of Public Reading Enthusiasm and Literacy Levels  in collaboration with the East Kalimantan Provincial Library, reflecting his engagement in data-driven policy support and socio-economic development initiatives.

Citation Metrics (Scopus)

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Featured Publications


Nonparametric Regression Mixed Estimators of Truncated Spline and Gaussian Kernel Based on CV, GCV, and UBR Methods

– International Journal on Advanced Science, Engineering and Information Technology, 2021

 

Josephine Kagunda | Biostatistics | Best Researcher Award

Dr. Josephine Kagunda | Biostatistics | Best Researcher Award

Dr. Josephine Kagunda | Ohio State University | Kenya

Dr. Josephine Wairimu Kagunda is an accomplished applied mathematician and biostatistics researcher with a Ph.D. in Applied Mathematics from the University of Lorraine, France, an M.Sc. in Applied Mathematics from the University of Nairobi, and a B.Sc. in Mathematics and Education from Egerton University, Kenya. She currently serves as a Biostatistics Research Fellow at The Ohio State University’s College of Public Health, Division of Biostatistics, where she develops stochastic and dynamical survival analysis models for public health systems under the HEALMOD project. Her expertise lies in mathematical modeling, Bayesian methods, and data-driven epidemiological modeling using Python and R. She previously served as a lecturer in Applied Mathematics at the University of Nairobi and at the Technical University of Kenya, mentoring several Ph.D. and M.Sc. students. Dr. Kagunda’s research advances public health through the mathematical modeling of infectious diseases, particularly malaria and HIV/AIDS, integrating behavioral, socioeconomic, and environmental parameters. Her work extends to AI innovation, where she curates, annotates, and evaluates mathematical content to enhance the reasoning capabilities of large language models (LLMs), leveraging reinforcement learning with human feedback (RLHF) and advanced LaTeX workflows. As part of the HANDSHAKE MOVE Fellowship, she designs and assesses domain-specific mathematical prompts to evaluate LLM performance, ensuring precision and depth in complex topics like calculus, differential equations, and survival analysis. Dr. Kagunda has published multiple peer-reviewed journal articles, including in the Journal of Theoretical Biology and has presented invited talks at leading universities such as Politecnico di Torino, University of Florida, and Ohio State University. She has organized several international workshops and CIMPA Schools in Kenya, focusing on mathematical modeling, data analysis, and women’s advancement in STEM. Her leadership in international collaborations has secured multiple grants and fellowships, including CIMPA, Erasmus+, IMU/CDC, and the Carnegie African Diaspora Fellowship. A dedicated journal reviewer for Journal of Mathematical Biology, JBS, IACM, and UJAM, she contributes to advancing global mathematical research standards. Dr. Kagunda’s scholarly impact is reflected in her 117 citations, h-index of 6, and i10-index of 33, marking her as a leading figure in applied mathematics, biostatistics, and the integration of mathematical sciences with artificial intelligence for public health innovation.

Profiles:  Scopus Orcid Google Scholar | Staff Page

Featured Publications

Ronoh, M., Jaroudi, R., Fotso, P., Kamdoum, V., Matendechere, N., Wairimu, J., … (2016). A mathematical model of tuberculosis with drug resistance effects. Applied Mathematics, 7(12), 1303–1316.

Ngonghala, C. N., Wairimu, J., Adamski, J., & Desai, H. (2020). Impact of adaptive mosquito behavior and insecticide-treated nets on malaria prevalence. Journal of Biological Systems, 28(2), 515–542.

Ronoh, M., Chirove, F., Wairimu, J., & Ogana, W. (2020). Evidence-based modeling of combination control on Kenyan youth HIV/AIDS dynamics. PLOS ONE, 15(11), e0242491.

Wairimu, J., Chirove, F., Ronoh, M., & Malonza, D. M. (2018). Modeling the effects of insecticides resistance on malaria vector control in endemic regions of Kenya. Biosystems, 174, 49–59.

Wairimu, J., & Ronoh, M. (2016). Modeling insecticide resistance in endemic regions of Kenya. Applied Mathematics, 7(6), 542–555.

Lugoye, J., Wairimu, J., Alphonce, C. B., & Ronoh, M. (2016). Modeling Rift Valley fever with treatment and trapping control strategies. Applied Mathematics, 7(6), 556–568.

Ronoh, M., Chirove, F., Wairimu, J., & Ogana, W. (2020). Modeling disproportional effects of educating infected Kenyan youth on HIV/AIDS. Journal of Biological Systems, 28(2), 311–349.

Wairimu, J. K. (2012). Mathematical analysis and dynamical systems: Modeling Highland malaria in western Kenya [Doctoral dissertation, Université de Lorraine]. Université de Lorraine Institutional Repository.

Wairimu, J., Gothard, A., & Rempala, G. (2025). Poisson network SIR epidemic model. Afrika Matematika, 36(3), 119.

Wairimu, J., Sallet, G., & Ogana, W. (2014). Mathematical analysis of a large-scale vector SIS malaria model in a patchy environment. Applied Mathematics, 5(13), 1913–1926.