Researcher • Mathematician • Data / AI Engineer

Idriss Olivier Bado

I build reliable software, AI systems, and data platforms for organizations operating in real-world, low-connectivity, and high-stakes environments.

Current focus

Idriss Olivier Bado
Research areas
7
Publications
2
Research notes
2
Projects
2

Research statement

My work connects mathematical reasoning, machine learning, and software engineering to solve real problems in data, institutions, and decision systems. I focus on explainable AI, statistical rigor, and scalable architecture to build tools that are both technically strong and operationally useful.

Selected research

Research themes and active directions

Browse all research

Information Graphs of Statistical Summaries

Structural summaries that encode statistical patterns and dependencies in interpretable graph representations.

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Topological Feature Engineering

Machine-learning pipelines that use topological features to detect economic regime transitions.

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Mathematical Notes in Number Theory

Research notes exploring reduction techniques and additive identities in analytic and arithmetic settings.

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Research Knowledge Graph Platform

A content infrastructure connecting publications, notes, and technical artifacts into a coherent research system.

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Publications

Selected publications

All publications

Projects

Featured engineering work

All projects
Machine LearningActive
Topological Regime Detection for Economic Signals

A pipeline combining topological data analysis and machine learning to understand economic transitions and structural regime changes.

PythonPyTorchscikit-learnTopological Data AnalysisPostgreSQL
Software EngineeringCompleted
Research Knowledge Graph Platform

A content and research platform architected to manage publications, notes, and professional knowledge in one coherent system.

Next.jsTypeScriptPrismaPostgreSQLNeon

Research areas

Current themes

Research overview

Number Theory

Arithmetic structure, modular identities, and analytic methods that connect classical number theory to computational modeling.

Topology and Geometry

Geometric invariants and topological structures that reveal continuity, shape, and stability in complex systems.

Topological Data Analysis

Persistent homology and geometric summaries for feature extraction from complex data ecosystems.

Probability & Statistics

Statistical inference, summarization, and probabilistic modeling for uncertain, high-dimensional systems.

Machine Learning

Statistical learning and predictive modeling with a focus on structure-aware, explainable, and rigorous systems.

Data Engineering

Data pipelines, platform design, and scalable systems for reliable scientific and operational analytics.

Artificial Intelligence

AI methods grounded in mathematical structure, reliability, and scientifically interpretable outputs.

Current work

Ongoing research and practice

Mathematical notes

Long-form mathematical writing combining technical argumentation with formal notation and structured references.

Computational methods

Interpretable pipelines for statistical summaries, regime detection, and topology-driven feature engineering.

Research engineering

Production-oriented systems that connect mathematical ideas to reliable, auditable software artifacts.

Professional snapshot

Academic and technical timeline

Research engagement

  • 2025 — Publication in Afrika Statistika on information graphs of statistical summaries.
  • 2026 — Preprint on topological feature engineering for economic regime detection.
  • Ongoing — Research notes and mathematical writing focused on arithmetic and topology.

Engineering practice

  • Systems — Data and research platform design with PostgreSQL, Next.js, and Prisma.
  • AI — Machine learning and applied AI workflows using rigorous data-driven methods.
  • Research software — Scientific content systems and computational tools for data analysis.

Professional profile

Research, engineering, and data systems.

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