science

Romain Glèlè Kakaï

Romain Glèlè Kakaï is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Romain Glèlè Kakaï rather than just read about it. In short: Romain Glèlè Kakaï, whose full name is Romain Lucas Glèlè Kakaï Agbidinoukoun, born on February 28, 1973, in Cotonou, is a Beninese academic specializing in biomathematics and forest estimations and a member of the African Academy of Sciences. A lecturer at the Faculty of Agronomic Sciences of the University of Abomey-Calavi in Benin, he has distinguished himself through his research work and prolific scientific pro…

Key takeaways

Romain Glèlè Kakaï belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Romain Glèlè Kakaï to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Romain Glèlè Kakaï from memory before moving on to harder problems.

Reference excerpt

Romain Glèlè Kakaï, whose full name is Romain Lucas Glèlè Kakaï Agbidinoukoun, born on February 28, 1973, in Cotonou, is a Beninese academic specializing in biomathematics and forest estimations and a member of the African Academy of Sciences. A lecturer at the Faculty of Agronomic Sciences of the University of Abomey-Calavi in Benin, he has distinguished himself through his research work and prolific scientific production and is ranked 2nd in the top 100 scientists of Benin according to the AD Scientific Index.

Biography

Origins and studies Romain Lucas Glèlè Kakaï graduated top of his class at every stage of his academic training. He obtained a degree in General Agronomy in 1998, then a degree in Forest Agronomic Engineering in 2000 at the University of Abomey-Calavi. He continued his studies in Belgium at Gembloux Agro-Bio Tech of the University of Liège (formerly known as the University Faculty of Agricultural Sciences of Gembloux), where he earned a postgraduate diploma in applied statistics and computer science and a PhD in biometrics in 2005.

Career and research domains A Full Professor of Biostatistics at the Faculty of Agronomic Sciences of the University of Abomey-Calavi, he heads the Laboratory of Biomathematics and Forest Estimations (LABEF) at this university, and coordinates master’s and doctoral programs in biostatistics, taught in English, which have attracted students from 23 African countries. He also chaired the Scientific Council of Agronomic Sciences of his university from 2016 to 2024, and was the first president of the Scientific Council of the National Institute of Agricultural Research of Benin (INRAB) from 2017 to 2019. An expert in mathematical modeling of living systems, his research is diverse and includes biomathematics, data science, and forest estimation. He has developed and popularized in Africa the practical applications of advanced statistical and mathematical methods in the life sciences through teaching, research, and scientific publications. His current research focuses on linear and nonlinear mixed-effects models, nonlinear dynamical systems, ecology, and the restoration of mangrove ecosystems.

Laboratory The Laboratory of Biomathematics and Forest Estimations (LABEF), which he leads, aims to analyze the applicability of mathematical tools in the life sciences and to understand the interactions between ecological processes, human health, anthropogenic factors, and the structure of terrestrial ecosystems, with a clear link to management and policy.

Affiliations and recognitions Romain Lucas Glèlè Kakaï is:

Member of the African Academy of Sciences (since 2023) President of the African German Network of Excellence in Sciences: 2019–2023 Member of the Global Young Academy (GYA) (2013–2018) Young Affiliate of the World Academy of Sciences (TWAS) 2011–2015 "New Champions" of the World Economic Forum (2012) Fellow of the Alexander von Humboldt Foundation for Excellence in Science in 2007 "Jan Tinbergen" Prize for best young statistician from emerging and developing countries, awarded by the International Statistical Institute in 2005 "Heinz and Johannes" Prize for Best Research Paper in Ecology, 2007, awarded by The Support Africa International Foundation, Germany, 2007

Contributions Romain Lucas Glèlè Kakaï is an FAO expert in training and designing National Forest Inventory methodologies for West African countries. He is Director of the Humboldt Hub on socio-ecological modeling of COVID-19 in Africa. In 2023, he developed an age-structured mathematical model and associated computer code capable of analyzing the impact of different vaccination scenarios on the malaria burden in African countries. He is one of the group leaders on malaria modeling within the Vaccine Impact Modelling Consortium (VIMC), a task force that provides the GAVI and the World Health Organization with projections on the impact of vaccination on the burden of infectious diseases worldwide.

Publications Romain Lucas Glèlè Kakaï has to his credit more than 300 scientific publications including:

Books Salako K. Valère, Zanvo M.G. Serge, Sinsin B. Corine, Gnansounou S. Constant, Adomou C. Aristide. Glèlè Kakaï R. (2021). Atlas of Plant Species of the Mangroves of Benin : Diversity, Uses and Conservation. National Library, Benin Glèlè Kakaï R. (2010). Classification Rules and Error Rates in Discriminant Analysis. EEU, Germany. Glèlè Kakaï R., Sodjinou E., Fonton H. N. (2006). Conditions for the Application of Parametric Statistical Methods. National Library, Benin. Glèlè Kakaï R., Palm R., Kokode G. (2005). Decision Discriminant Analysis: Theoretical Aspects and Computer Applications. National Library, Benin Glèlè Kakaï R., Kokode G. (2004). Univariate and Multivariate Statistical Techniques: Computer Applications. National Library, Benin

Scientific articles (selection) 2025: Nonlinear Mixed Models and Related Approaches in Infectious Disease modeling: A Systematic and Critical Review 2025: A Stochastic Continuous-Time Markov Chain Approach for Modeling the Dynamics of Cholera Transmission: Exploring the Probability of Disease Persistence or Extinction 2025: Machine learning techniques for tomato yield prediction: A comprehensive Analysis 2024: Direct and Indirect Effects of Environmental and Socio-Economic Factors on COVID-19 in Africa Using Structural Equation Modeling 2024: Empirical Performance of Deep Learning Models with Class Imbalance for Crop Disease Classification 2024: Modelling the potential impact of climate change on Carapa procera DC. in Benin and Burkina Faso (West Africa) 2023: Economic Valuation of Mangroves and a Linear Mixed Model-Assisted Framework for Identifying Its Main Drivers: A Case Study in Benin 2023: Tree height-diameter, aboveground and belowground biomass allometries for two West African mangrove species 2023: Digital soil mapping: a predictive performance assessment of spatial linear regression, Bayesian and ML-based models 2023: Performance of inhomogeneous Poisson point process models under different scenarios of uncertainty in species presence-only data

Illustrations

Worked examples

Example 1 — a first encounter with Romain Glèlè Kakaï

Start with the simplest possible case. Write down what Romain Glèlè Kakaï claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Romain Glèlè Kakaï before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Romain Glèlè Kakaï ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Romain Glèlè Kakaï

In research: Romain Glèlè Kakaï appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Romain Glèlè Kakaï in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Romain Glèlè Kakaï is common in secondary-school and first-year university syllabi. It links to neighbouring topics 1973 births, Benin, Beninese scientists, so understanding it makes those chapters shorter.
In everyday life: Look for Romain Glèlè Kakaï outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Ask Teacher Smith questions about this articleOpens your AI tutor with a question about “Romain Glèlè Kakaï” →

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Romain Glèlè Kakaï in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Romain Glèlè Kakaï means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Romain Glèlè Kakaï out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Romain Glèlè Kakaï in simple terms?

Why does Romain Glèlè Kakaï matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Romain Glèlè Kakaï?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Romain Glèlè Kakaï.