Food security · Climate and conflict shocks · Earth observation · Applied econometrics · Sahel and Sub-Saharan Africa
I am a Research Analyst and Data Scientist at the International Food Policy Research Institute (IFPRI / CGIAR), Development Strategies and Governance Unit, based in Dakar, Senegal. My work turns household surveys, routine surveillance data, satellite observations and conflict event records into reproducible evidence for food security and humanitarian decision making.
- Research focus: food security measurement, household shocks and coping strategies, political violence and conflict diffusion, climate variability, outbreak epidemiology and disease surveillance, impact evaluation (including mental health and psychosocial outcomes).
- Methods: applied econometrics, spatial statistics, species distribution modelling, machine learning, AI agent development, survey harmonisation, cost-benefit analysis.
- Current direction: operational early warning systems that combine satellite data, climate reanalysis and sparse ground records into calibrated, interpretable risk signals.
- Teaching: visiting lecturer in statistics, spatial data science and Python at ENSAE Dakar and Université Numérique Cheikh Hamidou Kane.
Click any project title to open the repository. All pipelines are designed to be reproducible; where microdata belong to governments or partners, the code is public and the data are available from the data owners on request.
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Food security · Survey harmonisation Config-driven, tested workflow harmonising 14 rounds of Chad's national food security survey (ENSA, Oct 2018 to Oct 2025; 197,947 households) into comparable thematic datasets: food consumption, coping strategies, expenditure and more. Indicators are recomputed and validated against the original analysts' scores, with provenance manifests. |
Earth observation · Species distribution modelling R package with a Shiny interface that makes species distribution modelling accessible to non-programmers: raster predictors and occurrence data in, spatially blocked cross-validation (blockCV), predictor screening (CENFA), MaxEnt and other models out, plus the generated R code for full reproducibility. Example data: agroforestry tree species in Niakhar, Senegal. |
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Public health surveillance · Impact evaluation R pipeline on the weekly IDSR surveillance database for Ituri province (DRC): automated weekly epidemiological bulletin in Word, a French-language dashboard (diseases, health zones, malaria, Ebola, data quality) and a controlled interrupted time series analysis of routine morbidity and Ebola burden across 36 health zones. Runs end to end on synthetic data with |
Public health surveillance · Forecasting Ten years (2015 to 2024) of Niger's weekly notifiable disease reports cleaned into tidy, source-validated tables and served in an R Shiny dashboard: disease trends, meningitis alert thresholds, reporting completeness, maternal deaths and a DHIS2 comparison. A modelling module fits negative binomial, hurdle and endemic-epidemic models with forecasts. |
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Earth observation · Agricultural land Google Earth Engine workflow that maps arable land at 30 m resolution across African countries by combining cropland extent (NASA GFSAD 2015) and cleared forest, then masking steep slopes (>15%), permanent water and impervious surfaces. One script per country, from Burkina Faso to Uganda. |
Teaching · Spatial data science · Course website Eleven practical sessions taught at ENSAE Dakar: vector and raster data, zonal statistics, risk mapping, combining health, WorldPop and ACLED conflict data into composite indicators, spatial autocorrelation, species distribution modelling and Sentinel-2 spectral indices (NDVI, NDWI, NDBI). In French, CC BY 4.0. |
Tool-using LLM assistants built on top of my data pipelines. The model answers questions in English or French only through read-only, tested tools; the server validates every published table and chart, attaches the analytical cautions, and lists the tool calls behind each answer. No household record ever reaches the model. Each assistant runs on invented demo data out of the box, and the tools work without an API key. Status: tested offline; the quality of live-model answers is measured by each repository's evaluation questions.
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AI agent · Food security surveys, Chad Ask how the 14 ENSA rounds were harmonised and what they show. 15 read-only tools trace any variable across rounds, explain recodes and quality checks, compare 58 indicators by round, region and sex of the household head, and draft crosswalk mappings for a new round. Regional cells under 30 households are suppressed. |
AI agent · Resilience programme surveys, Chad Ask how the 10 survey rounds of WFP's Integrated Resilience Programme (17,255 households) were merged, which validation checks fail, which data issues remain open, and what 55 indicators show by round and region, with WFP's reconciled costs. The server refuses charts that join lean-season and post-harvest rounds. Evaluated on 18 questions with expected values and caveats. |
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AI agent · Disease surveillance, Niger Ask what Niger's weekly notifiable disease surveillance shows: trends, seasonality, like-for-like year comparisons, meningitis epidemic thresholds, reporting completeness and model estimates with confidence intervals. 19 read-only tools enforce the rules an epidemiologist would: partial years are never compared with full years, missing reports are never read as zero, and case-definition changes are always flagged. |
AI agent · Epidemiological surveillance, DRC · work in progress Question-and-answer agent on Ituri's IDSR surveillance data, packaged as a Claude Code skill. Indicators are computed by the R pipeline, never by the model, and a parity test checks the tools against the pipeline across diseases, zones and weeks. Evaluated on 30 questions against answers computed independently in R. Real data stay locked until a written data-sharing agreement is in place. |
Venture: FAYAMA.AI, the AI startup I founded to build decision tools for food security, poverty targeting and agricultural transformation in Africa, combining satellite data, household surveys and machine learning.
Analysis code behind IFPRI working papers, policy briefs and technical notes. Survey microdata are not redistributed; scripts document every step from raw data to published estimates.
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Impact evaluation · Cost-benefit analysis · 2018 to 2023 · Report Household dataset for IFPRI's cost-benefit analysis of WFP's Integrated Resilience Programme in Chad: 10 survey rounds, 17,255 households, 626 columns from 26 modules, WFP costs reconciled by activity, a Shiny dashboard of checks and results, and a package for public release on IFPRI Dataverse. Known defects are documented, and each fix writes a new versioned file. |
Outbreak epidemiology · Health surveillance · 2026 Reproducible pipeline for the MSF Ebola treatment centre in Mongbwalu, Ituri: weekly epidemiological sitrep, line-list analysis report, a daily data quality checklist for the data entry team, and DHIS2 analyses (epidemic curves, transmission chains, Rt). Patient data never leave the analyst's machine; CI and demos run on synthetic data. Code © MSF OCG; reuse requires agreement. |
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Conflict · Climate · Spatial exposure measures Exposure measures for survey clusters (10, 25 and 50 km buffers) and the 519 Admin 3 units of the DRC: ACLED conflict events 1997 to 2025, WorldPop population and age-sex structure 2015 to 2025, and ERA5-Land temperature anomalies 1991 to 2025, with an ACLED versus UCDP GED validation. Outputs in CSV and Stata. |
Food systems · Labour · Data acquisition · in progress Data acquisition for the Mastercard Foundation agrifood scenarios study with IFPRI: a verified source matrix and access register for the labour force and household surveys of 17 countries, with scripts that validate the register, build the Excel deliverables, download from the World Bank Microdata Library and block any microdata from being committed. |
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Shocks · Coping strategies · 2019 to 2023 How households respond to conflict, climate and price shocks, using eleven waves of cross-sectional household survey data linked to an extensive set of shock indicators compiled from external sources. |
Shocks · Coping strategies · 2018 to 2023 Companion analysis for Mali using association rule mining to identify which coping strategies households combine when facing different kinds of shocks and stressors. |
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Conflict · Spatial indicators Implementation in Google Earth Engine of ACLED's conflict diffusion indicator: share of populated 10 km grid cells with high levels of violence, built from WorldPop and ACLED and aggregated to admin 2, with sensitivity analysis on the population and event thresholds. Prepared for WFP. |
Poverty mapping · Small area estimation Poverty headcount (FGT0) below the levels where the EHCVM 2021 survey is representative (provinces and communes), comparing direct, Fay-Herriot and machine learning estimates with conflict and climate covariates. Part of a series also covering Senegal, Mali, Niger, Benin and Côte d'Ivoire. |
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Food systems · Data engineering Configuration-driven, provenance-tracked pipeline assembling 30 sources across five layers (geography, soil, food, health, policy) into one database keyed on a county and sub-county crosswalk, built for soil-to-nutrition pathway analysis. Every object carries publisher, licence, checksum and extraction date. |
Earth observation · Agriculture · replication guide Guide to replicating the Fields of The World global field boundary map at 10 m for Burkina Faso: cloud-free Sentinel-2 mosaics, inference with the PRUE U-Net model, polygon extraction and confidence filtering, for seasonal updates or local fine-tuning. |
Software for the field side of the data: collecting it where connectivity is poor, and supervising survey quality while teams are still in the field.
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Offline-first field data collection · Phase 1 Platform for collecting field data in low-connectivity areas, built by extending ODK: ODK Central hosted on AWS in Africa (af-south-1), a branded ODK Collect, and an encrypted SMS fallback when there is no data connection. The SMS codec and the bridge service into ODK Central are built and tested; the infrastructure is written and validated but not yet deployed. |
Survey supervision · Senegal · in French Supervision tools for the ANSD survey of beehive productivity in Senegal, collected on tablets with Survey Solutions: fieldwork progress by day, region and enumerator, 39 consistency checks, and a ready-to-use list of interviews to reject. An R Shiny app and a Python script give identical results. |
| Experience | Research Analyst, IFPRI (2022 to present) · Data Analyst, IOM (2022 to 2023): impact evaluations and MHPSS survey analysis in West Africa · Remote Sensing and ML Engineer, CIRAD (2020 to 2021): tree species distribution in agroforestry parklands |
| Education | MITx MicroMasters, Data, Economics, and Design of Policy (2024) · MITx MicroMasters, Statistics and Data Science (2023) · Statistician Engineer with distinction, ENSAE Dakar (2020) · BSc Computer Science with distinction, University of Ouagadougou (2016) |
| Languages | French, Bambara, Senoufo (native) · English (professional) |
Cards regenerated daily by a GitHub Action in this repository.

