Prof. Dr. Oliver Kramer
Head of Computational Intelligence Lab 
Room: A5-2-231
E-Mail: oliver.kramer@uol.de
GoogleScholar, DBLP, GitHub, ResearchGate, LinkedIn,TowardsDataScience, ResearchGate
Private: Beatport, Spotify

CV

Oliver Kramer studied computer science at the University of Bielefeld and TU Dortmund, completing his degree in 2003 and earning a PhD in Artificial Intelligence from the University of Paderborn in 2008 in the Wissensbasierte Systeme Group of Hans Kleine Büning in the International Graduate School of Dynamic Intelligent Systems. After postdoctoral research at the Computational Intelligence Group of Günter Rudolph of the TU Dortmund and Algorithms Group of Richard Karp at ICSI Berkeley, he became a Junior Professor for Stochastics and Optimization at the Institute of Structural Mechanics at Bauhaus University Weimar in 2011. In 2013, he completed his habilitation at the University of Oldenburg. Since 2017, he has been a Professor of Computational Intelligence at the Carl von Ossietzky University of Oldenburg, where he represents his field in research and teaching.

Teaching

Bachelor's Program in Computer Science
Lecture: Introduction to Artificial Intelligence (inf530)
Proseminar: Genetic Algorithms (inf800)

Master’s Program in Computer Science
Lecture: Evolution Strategies (inf535)
Lecture: Deep Learning (inf536)

Responsible for the Specialization in Artificial Intelligence in the Master’s Program in Computer Science

Books

Selected Recent Publications

2025

• Oliver Kramer, Jill Baumann: Unlocking Structured Thinking in Language Models with Cognitive Prompting. ESANN 2025

2024

• Jill Baumann, Oliver Kramer: LLaMA Tunes CMA-ES. ESANN 2024
• Jill Baumann, Oliver Kramer: Towards Explainable Evolution Strategies with Large Language Models. ESANN 2024
• Jill Baumann, Oliver Kramer: Evolutionary Multi-objective Optimization of Large Language Model Prompts for Balancing Sentiments. EvoApplications@EvoStar 2024: 212-224
• Jill Baumann, Oliver Kramer: Evolutionary Multi-Objective Optimization of Large Language Model Prompts for Balancing Sentiments. CoRR abs/2401.09862 (2024)
• Oliver Kramer: Large Language Models for Tuning Evolution Strategies. CoRR abs/2405.10999 (2024)
• Jill Baumann, Oliver Kramer: Towards Explainable Evolution Strategies with Large Language Models. CoRR abs/2407.08331 (2024)
• Oliver Kramer, Jill Baumann: Unlocking Structured Thinking in Language Models with Cognitive Prompting. CoRR abs/2410.02953 (2024)

2023

• Oliver Kramer: Enhancing Evolution Strategies with Evolution Path Bias. ESANN 2023
• Oliver Kramer, Jill Baumann: Wind Power Prediction with ETSformer. ESANN 2023

2022

• Oliver Kramer: A Fast and Simple Evolution Strategy with Covariance Matrix Estimation. ESANN 2022
• Tim Cofala, Oliver Kramer: An Evolutionary Fragment-Based Approach to Molecular Fingerprint Reconstruction. GECCO 2022: 1156-1163

2021

• Patrick Burke, Jonas Prellberg, Oliver Kramer: Evolutionary Deep Multi-Task Learning. ESANN 2021
• Tim Cofala, Oliver Kramer: Transformers for Molecular Graph Generation. ESANN 2021
• Tim Cofala, Thomas Teusch, Oliver Kramer: Spatial Generation of Molecules with Transformers. IJCNN 2021: 1-7

2020

• Oliver Kramer: Learning Step Size Adaptation in Evolution Strategies. ESANN 2020: 435-440
• Nils Worzyk, Stefan Niewerth, Oliver Kramer: Adversarials-1 in Speech Recognition: Detection and Defence. ESANN 2020: 619-624
• Stefan Oehmcke, Thomas Teusch, Thorben Petersen, Thorsten Klüner, Oliver Kramer:
  Modeling H2O/Rutile-TiO2(110) Potential Energy Surfaces with Deep Networks. IJCNN 2020: 1-7
• Jonas Prellberg, Oliver Kramer: Learned Weight Sharing for Deep Multi-Task Learning by Natural Evolution Strategy and Stochastic Gradient Descent. IJCNN 2020: 1-8
• Lars Elend, Sebastian A. Tideman, Kerstin Lopatta, Oliver Kramer: Earnings Prediction with Deep Learning. KI 2020: 267-274
• Tim Cofala, Lars Elend, Philip Mirbach, Jonas Prellberg, Thomas Teusch, Oliver Kramer: Evolutionary Multi-objective Design of SARS-CoV-2 Protease Inhibitor Candidates. PPSN (2) 2020: 357-371