Structural summaries that encode dependency and statistical pattern in interpretable graph form.
Idriss Olivier Bado
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.

Recent research and writing
A study of structural change detection through topology, statistics and machine learning.
A working note on additive reduction and arithmetic structure in analytic settings.
Core themes
Arithmetic and Number Theory
Questions of additive structure, analytic reduction, and arithmetic identities in mathematically grounded settings.
Topology and Geometric Methods
Persistent structure, continuity, and invariants as tools for understanding complex systems.
Topological & Statistical Data Analysis
Feature extraction, regime detection, and model interpretation in data-rich scientific contexts.
Machine Learning & Research Engineering
Scientific ML workflows, reproducible pipelines, and reliable computational infrastructure.
Research notes
This note studies additive decompositions through a reduction framework and explores structural identities relevant to Goldbach-type questions.
This note explores structural identities and computational patterns in the study of fifth-power taxicab-type equations.
Selected technical work
A pipeline combining topological data analysis and machine learning to understand economic transitions and structural regime changes.
A content and research platform architected to manage publications, notes, and professional knowledge in one coherent system.

Professional profile
Idriss Olivier Bado works at the intersection of software engineering, applied mathematics, data science, and institutional AI. He designs backend systems, full-stack products, analytics platforms, and ML workflows that are grounded in rigor, maintainability, and operational reliability. His experience spans public-sector software, mobile-money systems, industrial data infrastructure, and research-driven analytics.
More about me