Twitter Mastodon GitHub Email

Domingo López Rodríguez

Professor at the Department of Applied Mathematics, University of Málaga.

My recent work focuses on Formal Concept Analysis (FCA) and its applications in data science and knowledge discovery.

Learn more about me →

fcaR Package

Formal Concept Analysis in R. A comprehensive toolset for FCA including formal contexts, concept lattices, and implications.

Teaching

Teaching materials and resources for undergraduate and graduate courses in Mathematics and Engineering.

Publications

A complete list of my scientific tracking, including journal papers, conference proceedings, and book chapters.

Latest Updates

Unlocking Hidden Patterns in Big Data: How We Scaled Boolean Matrix Factorization to Thousands of Features
Unlocking Hidden Patterns in Big Data: How We Scaled Boolean Matrix Factorization to Thousands of Features
Uncovering meaningful, interpretable patterns in massive binary datasets often comes with an overwhelming computational cost. We developed a novel algorithm, RSF-ES, that uses order-theoretic smart pruning to dramatically speed up Boolean Matrix Factorization without losing mathematical exactness.
15 June 2026
Cracking the Speed Code in Fuzzy Data Reasoning: How We Made Fuzzy FCA Blazing Fast
Cracking the Speed Code in Fuzzy Data Reasoning: How We Made Fuzzy FCA Blazing Fast
Calculating logical closures in fuzzy data used to be a massive computational bottleneck. In our latest paper, we introduce a new framework and algorithm that makes computing direct-optimal fuzzy implicational systems orders of magnitude faster.
12 June 2026
Teaching Algorithms to 'Speak Fuzzy' Natively: A Faster Way to Mine Nuanced Data
Teaching Algorithms to 'Speak Fuzzy' Natively: A Faster Way to Mine Nuanced Data
Analyzing fuzzy data shouldn't mean drowning in computational bottlenecks. By adapting the Close-by-One algorithm family to process degrees of truth natively, our research team eliminated the need for cumbersome data scaling and drastically boosted execution speeds.
15 November 2025
Divide and conquer... the 'if-then' rules in your data
Divide and conquer... the 'if-then' rules in your data
The 'CARVE' algorithm is a super-fast 'divide-and-conquer' method for finding data concepts. We upgraded it to 'CARVE+' so it can find all the 'if-then' logical rules at the same time, giving us the best of both worlds.
19 April 2025
We built an open-source tool to find a city's worst 'heat island' hotspots
We built an open-source tool to find a city's worst 'heat island' hotspots
We present URSUS_UHI, a new open-source software tool that helps urban planners automatically find the most unfavourable areas in a city: the places with the highest temperatures and the least green space.
1 February 2025
Beyond just 'correct': new logic rules to make data insights easier to read
Beyond just 'correct': new logic rules to make data insights easier to read
Our previous work created a logic to find correct rules from positive and negative data. Now, we've added new logical equivalences to 'shrink' those rules, making them shorter, simpler, and more useful for humans.
18 January 2025
No matching items

View all posts →