000.000 / 000.000
LOG // CI
Prof. Dr.
Oliver Kramer
Professor of Computational Intelligence · University of Oldenburg
> We develop computational intelligence methods that connect evolutionary optimization, learning, cognition, and AI in application areas like computational biology.
01_evolutionary_projects
EvoLabInteractive studio for evolution strategies on ten classic benchmarks — tune population, selection, recombination, and step size while the search unfolds.[EXPLORE][EXPLORE]
MolEvolver Mini LabEvolves a molecule to match a pharmacophore you place in 3D, searching a library of 10,150 synthesis-constrained compounds right in the browser.[REPO][REPO]
LMAPUnfolds messy, high-dimensional data into a visible map of its structure by combining local PCA models with global MDS — privately, in the browser.[MAP][MAP]02_teaching_material
Introduction to Artificial IntelligenceScripted lecture from k-nearest neighbors and k-means through convolutional networks, attention, and large language models — each chapter with worked examples, exercises, and Colab notebooks.[PDF][PDF]
Machine Learning with Evolution StrategiesHands-on Colab course: SVM, MLP, clustering, and CNNs written from scratch in NumPy and trained with one derivative-free optimizer — the (1+1)-ES.[REPO][REPO]
Introduction to Evolution StrategiesA tour of evolution strategies on Medium — from the (1+1)-ES and the 1/5th success rule to self-adaptive step sizes on hard landscapes.[BLOG][BLOG]03_selected_publications
- 2026 Linear Evaluation Complexity of Surrogate-Assisted (1+1)-EA on OneMax — ESANN 2026
- 2026 Adaptive Search in Collatz Exponent-Code Space via 2-adic and 3-adic Constraints — CoRR abs/2607.10041
- 2025 An LLM-Based Multi-Agent Framework for Evolutionary Blackbox Optimization — GECCO Companion 2025: 671–674
- 2025 Enhancing Evolutionary Algorithms Through Meta-Evolution Strategies — IEEE CAI 2025: 1292–1297
- 2024 LLaMA Tunes CMA-ES — ESANN 2024
04_books
2026Artificial Intelligence Essentials[SPRINGER]
2017Genetic Algorithm Essentials[SPRINGER]
2016Machine Learning for Evolution Strategies[SPRINGER]
2014A Brief Introduction to Continuous Evolutionary Optimization[SPRINGER]
2013Dimensionality Reduction with Unsupervised Nearest Neighbors[SPRINGER]
2009Computational Intelligence[SPRINGER]
2008Self-Adaptive Heuristics for Evolutionary Computation[SPRINGER]
05_essays_&_position
Position: AI SafetyWhy institutional control of the AI frontier should be refused — and what free research makes possible in medicine, against poverty, and for the climate.[!][!]
Beyond Kohlberg: Evolving Moral Psychology for Artificial SuperintelligenceHuman stage theories of moral development were never written for machines — a moral psychology for superintelligence that evolves instead of being imposed.20252025
Evolutionary Multi-Objective Optimization with Rake SelectionRake selection spreads a population evenly along the Pareto front with rake lines, keeping multi-objective search diverse without expensive density estimation.2023202306_creative_side_projects
07_ask_the_robot
Research droid // online
Ask me about Kramer's research. Optimism was not included in my assembly kit.
> For example: What does Oliver Kramer research?
AI answers may be wrong. Check the linked sources.
END OF TRANSMISSION