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I am 𝗔𝗞𝗜𝗠𝗔𝗡𝗔 𝗟𝗮𝘁𝗶𝗳𝗮, from 𝗥𝘄𝗮𝗻𝗱𝗮.

I am currently a second-year Master's student in Statistics, specializing 𝗕𝗶𝗼𝘀𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 at 𝗟𝗔𝗕𝗘𝗙 (𝗟𝗮𝗯𝗼𝗿𝗮𝘁𝗼𝗶𝗿𝗲 de 𝗕𝗶𝗼𝗺𝗮𝘁𝗵𝗲́𝗺𝗮𝘁𝗶𝗾𝘂𝗲𝘀 et d'𝗘𝘀𝘁𝗶𝗺𝗮𝘁𝗶𝗼𝗻𝘀 𝗙𝗼𝗿𝗲𝘀𝘁𝗶𝗲̀𝗿𝗲𝘀) at the

𝗨𝗔𝗖 (𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 𝗼𝗳 𝗔𝗯𝗼𝗺𝗲𝘆-𝗖𝗮𝗹𝗮𝘃𝗶, 𝗕𝗲𝗻𝗶𝗻).

I chose to pursue my Master’s studies at LABEF because it offers a strong academic environment where English serves as the primary language of instruction and communication in this program. This aligns well with my academic interests and long-term career aspirations in public health, biostatistics, and data science.

I am currently conducting my Master's research on:

“𝗠𝘂𝗹𝘁𝗶𝗹𝗲𝘃𝗲𝗹 𝗠𝘂𝗹𝘁𝗶𝗻𝗼𝗺𝗶𝗮𝗹 𝗮𝗻𝗱 𝗦𝗽𝗮𝘁𝗶𝗮𝗹 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗼𝗳 𝗗𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗮𝗻𝘁𝘀 𝗼𝗳 𝗕𝗼𝗱𝘆 𝗠𝗮𝘀𝘀 𝗜𝗻𝗱𝗲𝘅 𝗔𝗺𝗼𝗻𝗴 𝗪𝗼𝗺𝗲𝗻 𝗼𝗳 𝗥𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗲 𝗔𝗴𝗲 𝗶𝗻 𝗥𝘄𝗮𝗻𝗱𝗮.”

Through this research, I aim to contribute to a better understanding of the socioeconomic, demographic, and geographic factors associated with nutritional outcomes among women of reproductive age, thereby supporting evidence-based public health policies and interventions in Rwanda.

I would like to express my sincere gratitude to the Director of 𝗟𝗔𝗕𝗘𝗙 , Professor 𝗥𝗼𝗺𝗮𝗶𝗻 𝗚𝗹𝗲̀𝗹𝗲̀ 𝗞𝗮𝗸𝗮𝗶̈, and the entire 𝗟𝗔𝗕𝗘𝗙 𝗧𝗲𝗮𝗺 for their continuous guidance, creativity, mentorship and academic support throughout my studies.

I also extend my heartfelt appreciation to 𝗗𝗔𝗔𝗗 (𝗚𝗲𝗿𝗺𝗮𝗻 𝗔𝗰𝗮𝗱𝗲𝗺𝗶𝗰 𝗘𝘅𝗰𝗵𝗮𝗻𝗴𝗲 𝗦𝗲𝗿𝘃𝗶𝗰𝗲) for its generous financial support through the In-Country/In-Region Scholarship Programme, which has made this academic journey possible.

I look forward to further developing my research skills and contributing to evidence-based solutions for public health challenges in Rwanda and beyond.

#LABEF #DAADScholar #Biostatistics #PublicHealth #DataScience #Research #WomenInScience #Rwanda #Benin #EnglishForScience #AcademicExcellence #HigherEducation #YoungResearcher #AfricanResearchers #StayTuned.

𝗟𝗼𝗻𝗴 𝗹𝗶𝘃𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗟𝗔𝗕𝗘𝗙!

𝗦𝘁𝗮𝘆 𝘁𝘂𝗻𝗲𝗱 𝗳𝗼𝗿 𝘂𝗽𝗱𝗮𝘁𝗲!

Paterne M. Hounguevou, a second-year Master’s student in Biostatistics at LABEF-UAC, is pursuing research at the intersection of data science, agriculture, and health. His work focuses on AI-driven modeling and early prediction of agricultural diseases using spatio-temporal, climatic, and phytosanitary data.

Through this research, he aims to contribute to sustainable agriculture, food security, and public health while building expertise in spatial epidemiology across sub-Saharan Africa.

Paterne expresses his deep gratitude to Glèlè Kakaï for his visionary leadership, scientific creativity, and unwavering commitment to mentoring the next generation of researchers worldwide.

“His innovative mindset and dedication to academic excellence continue to inspire young scientists to pursue impactful research on a global scale.”

#LABEF #SSACAB #Biostatistics #DataScience #ArtificialIntelligence #SpatialEpidemiology #Research #ScientificExcellence #AfricanScience

I am 𝗝𝘂𝗱𝗶 𝗔𝗿𝗺𝗲𝗹 𝗕𝗢𝗨𝗥𝗢𝗕𝗢𝗨, from 𝗚𝗮𝗯𝗼𝗻. I am a PhD candidate in Biometry, with an academic background in Agronomy and Biostatistics. My doctoral thesis, funded by @𝗗𝗔𝗔𝗗 (German Academic Exchange Service), is entitled:

“𝗘𝗠𝗣𝗜𝗥𝗜𝗖𝗔𝗟 𝗔𝗦𝗦𝗘𝗦𝗦𝗠𝗘𝗡𝗧 𝗢𝗙 𝗣𝗥𝗘𝗗𝗜𝗖𝗧𝗜𝗩𝗘 𝗣𝗘𝗥𝗙𝗢𝗥𝗠𝗔𝗡𝗖𝗘 𝗢𝗙 𝗜𝗡𝗛𝗢𝗠𝗢𝗚𝗘𝗡𝗘𝗢𝗨𝗦 𝗣𝗢𝗜𝗡𝗧 𝗣𝗥𝗢𝗖𝗘𝗦𝗦 𝗠𝗢𝗗𝗘𝗟𝗦 𝗧𝗥𝗔𝗜𝗡𝗘𝗗 𝗪𝗜𝗧𝗛 𝗣𝗥𝗘𝗦𝗘𝗡𝗖𝗘-𝗢𝗡𝗟𝗬 𝗗𝗔𝗧𝗔: 𝗔𝗣𝗣𝗟𝗜𝗖𝗔𝗧𝗜𝗢𝗡 𝗧𝗢 𝗧𝗛𝗘 𝗗𝗜𝗦𝗧𝗥𝗜𝗕𝗨𝗧𝗜𝗢𝗡 𝗢𝗙 𝗧𝗔𝗕𝗘𝗥𝗡𝗔𝗡𝗧𝗛𝗘 𝗜𝗕𝗢𝗚𝗔 𝗕𝗔𝗜𝗟𝗟. 𝗜𝗡 𝗚𝗔𝗕𝗢𝗡”

The aim of my research is to empirically evaluate the predictive performance of inhomogeneous point process models (IPPMs) applied to presence-only data under realistic conditions that may compromise their validity.

This study integrates simulation experiments and real-world data on Tabernanthe iboga to evaluate the efficiency, robustness, and predictive performance of the models.

My main contributions to the scientific community are as follows:

-To review the application of IPPMs in species distribution modelling up to 2020;

- To simulate presence-only data under varying conditions of spatial autocorrelation, imperfect detection, spatial resolution, and sample size;

- To assess and quantify the effects of these factors on model performance using robust statistical metrics;

- And apply IPPMs to real presence-only data of Tabernanthe iboga to demonstrate their practical utility and limitations in a conservation context.

Overall, my work aims to support researchers, conservationists, and policymakers by providing reliable, data-driven approaches to species distribution modelling, thereby contributing to improved conservation decision-making and sustainable land management.

I would like to express my deep gratitude to Professor 𝗥𝗼𝗺𝗮𝗶𝗻 𝗚𝗟𝗘̀𝗟𝗘̀ 𝗞𝗔𝗞𝗔𝗜̈ for the quality of his supervision, his constant availability, and the decisive role he plays in my academic journey.

My sincere thanks also go to Professor 𝗔𝗱𝗮𝗻𝗱𝗲́ 𝗕𝗲𝗹𝗮𝗿𝗱𝗮𝗶𝗻 𝗙𝗔𝗡𝗗𝗢𝗛𝗔𝗡 for his moral support, encouragement, and the rigor of his scientific contributions. Finally, I am grateful to the 𝗗𝗔𝗔𝗗 for its financial support, which is essential to the completion of this work.

#LABEF #LABEFPhD #JudiArmelBouroubou #PhD #Biometry #Biostatistics #Agronomy #DataScience #Ecology #Biodiversity #AfricaResearch #Gabon #DAAD #Scholarship #YoungResearchers #STEM #ScientificResearch

𝗦𝘁𝗮𝘆 𝘁𝘂𝗻𝗲𝗱 𝗳𝗼𝗿 𝘂𝗽𝗱𝗮𝘁𝗲

𝗘𝗽𝗶𝗹𝗼𝗴𝘂𝗲 𝗼𝗳 𝗮 𝗦𝘆𝗺𝗽𝗵𝗼𝗻𝘆 𝗼𝗳 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗶𝗻 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗼𝗳 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗮𝗻𝗱 𝗣𝘂𝗯𝗹𝗶𝗰 𝗛𝗲𝗮𝗹𝘁𝗵

After five intellectually enriching days dedicated to 𝗹𝗻𝗳𝗲𝗰𝘁𝗶𝗼𝘂𝘀 𝗗𝗶𝘀𝗲𝗮𝘀𝗲 𝗠𝗼𝗱𝗲𝗹𝗹𝗶𝗻𝗴: 𝗖𝗼𝗺𝗽𝗮𝗿𝘁𝗺𝗲𝗻𝘁𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝘀, 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝗮𝗻𝗱 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝘁𝗼 𝗠𝗮𝗹𝗮𝗿𝗶𝗮 𝗨𝘀𝗶𝗻𝗴 𝗥, we conclude this remarkable journey with deep gratitude.

Our sincere appreciation goes to Professor 𝗥𝗼𝗺𝗮𝗶𝗻 𝗚𝗹𝗲̀𝗹𝗲̀ 𝗞𝗮𝗸𝗮𝗶̈, Director of LABEF, whose vision, scientific leadership, and outstanding expertise made this training a true school of excellence. We also thank 𝗗𝗿. 𝗝𝗼𝗻𝗮𝘀 𝗧. 𝗗𝗼𝘂𝗺𝗮𝘁𝗲̀for his insightful contributions to the mathematical foundations of infectious disease modelling.

Special recognition is extended to Dr. 𝗬𝘃𝗲𝘁𝘁𝗲 𝗠𝗼𝗻𝘁𝗰𝗵𝗼, 𝗗𝗿. 𝗖𝗹𝗮𝗿𝗶𝘀𝘀𝗲 𝗗𝗲́𝘁𝗲́, and 𝗣𝗵𝗗 𝗖𝗮𝗻𝗱𝗶𝗱𝗮𝘁𝗲 𝗞𝗮𝘀𝘀𝗶𝗳𝗼𝘂 𝗧𝗿𝗮𝗼𝗿𝗲́ for their exceptional guidance during the practical sessions, and to Dr. 𝗩𝗮𝗹𝗲̀𝗿𝗲 𝗦𝗮𝗹𝗮𝗸𝗼 and 𝗗𝗿. 𝗣𝗲𝗮𝗰𝗲 𝗧𝗮𝗵𝗶 𝗦𝗼𝘂𝗮𝗻𝗱 for their dedicated coordination.

Congratulations to all participants, both onsite and online, whose enthusiasm, curiosity, and active engagement enriched every discussion and learning experience.

Finally, we gratefully acknowledge 𝗟𝗔𝗕𝗘𝗙, 𝘁𝗵𝗲 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 𝗼𝗳 𝗔𝗯𝗼𝗺𝗲𝘆-𝗖𝗮𝗹𝗮𝘃𝗶, 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗩𝗮𝗰𝗰𝗶𝗻𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 𝗠𝗼𝗱𝗲𝗹𝗹𝗶𝗻𝗴 𝗖𝗼𝗻𝘀𝗼𝗿𝘁𝗶𝘂𝗺 (𝗩𝗜𝗠𝗖) and 𝗦𝗦𝗔𝗖𝗔𝗕 for their unwavering commitment to scientific excellence and capacity building.

The seminar may have ended, but the ideas it inspired will continue their journey.

𝗧𝗼𝗴𝗲𝘁𝗵𝗲𝗿, 𝘄𝗲 𝗮𝗱𝘃𝗮𝗻𝗰𝗲 𝘀𝗰𝗶𝗲𝗻𝘁𝗶𝗳𝗶𝗰 𝗲𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲.

https://chatgpt.com/c/6a2ae6c9-2a18-83ea-8540-765171cd0862

#LABEF #InfectiousDiseaseModelling #Malaria #PublicHealth #Epidemiology #Biostatistics #Research #CapacityBuilding #ScientificExcellence

Participants reflect on their experience.

𝗙𝗿𝗼𝗺 𝗗𝗲𝗱𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝗗𝗶𝘀𝘁𝗶𝗻𝗰𝘁𝗶𝗼𝗻: 𝗔𝗻𝗼𝘁𝗵𝗲𝗿 𝗣𝗵𝗗 𝗴𝗿𝗮𝗱𝘂𝗮𝘁𝗲𝘀 𝗳𝗿𝗼𝗺 𝗟𝗔𝗕𝗘𝗙

Congratulations to 𝗗𝗿 𝗕𝗼𝘂𝗿𝗼𝗯𝗼𝘂 𝗕𝗼𝘂𝗿𝗼𝗯𝗼𝘂 𝗝𝘂𝗱𝗶 𝗔𝗿𝗺𝗲𝗹 on the successful defense of his doctoral research at the 𝗟𝗔𝗕𝗘𝗙, 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 of 𝗔𝗯𝗼𝗺𝗲𝘆-𝗖𝗮𝗹𝗮𝘃𝗶 before distinguished members of jury from Nigeria, Togo and Benin.

His dissertation, entitled:“ 𝗘𝗺𝗽𝗶𝗿𝗶𝗰𝗮𝗹 𝗔𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁 𝗼𝗳 𝘁𝗵𝗲 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 𝗼𝗳 𝗜𝗻𝗵𝗼𝗺𝗼𝗴𝗲𝗻𝗲𝗼𝘂𝘀 𝗣𝗼𝗶𝗻𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀 𝗠𝗼𝗱𝗲𝗹𝘀 𝗧𝗿𝗮𝗶𝗻𝗲𝗱 𝘄𝗶𝘁𝗵 𝗣𝗿𝗲𝘀𝗲𝗻𝗰𝗲-𝗢𝗻𝗹𝘆 𝗗𝗮𝘁𝗮: 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘁𝗼 𝘁𝗵𝗲 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝗼𝗳 𝗧𝗮𝗯𝗲𝗿𝗻𝗮𝗻𝘁𝗵𝗲 𝗶𝗯𝗼𝗴𝗮 𝗕𝗮𝗶𝗹𝗹.In Gabon

This study assessed the predictive performance of Inhomogeneous Point Process Models (IPPMs) using a literature review, simulation experiments with presence-only data under varying ecological conditions, and an application to Tabernanthe iboga in Gabon.

𝗞𝗲𝘆 𝗳𝗶𝗻𝗱𝗶𝗻𝗴𝘀:

• Point process models remained generally robust despite the effects of spatial autocorrelation, detection probability, spatial resolution, and sample size.

• Detection probability and spatial autocorrelation were the main factors affecting predictive performance.

• For Tabernanthe iboga, potential evapotranspiration, precipitation, temperature seasonality, and elevation were identified as the main distribution drivers.

𝗙𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻:

1. Judi Armel Bourobou , Adandé Belarmain Fandohan, and Roman Lucas Glèlè Kakaï. "Inhomogeneous Spatial Point Process Models for Species Distribution Analysis: A Systematic Review." Applications of Modelling and Simulation 7 (2023): 49-62.

2. Judi Armel Bourobou et al. "Evaluating spatial resolution and imperfect detection effects on the predictive performance of inhomogeneous spatial point process models trained with simulated presence-only data." Modeling Earth Systems and Environment 10.4 (2024): 4675-4693

Dear Dr. 𝗕𝗼𝘂𝗿𝗼𝗯𝗼𝘂 𝗕𝗼𝘂𝗿𝗼𝗯𝗼𝘂 𝗝𝘂𝗱𝗶 𝗔𝗿𝗺𝗲𝗹, we are proud of your accomplishments and extend our best wishes as you advance to the next stages of your promising career.