Johannes Textor
Associate Professor (Universitair Hoofddocent)
Institute for Computing and Information Sciences
Radboud University,
Nijmegen, The Netherlands

Radboud Institute for Molecular Life Sciences,
Tumor Immunology department,
Radboud University Medical Center,
Nijmegen, The Netherlands

Contact Information

Radboud University:
Mercator building
Second floor, room 17
Toernooiveld 212
6525 EC NIJMEGEN

Radboudumc:
Medical BioSciences
Geert Grooteplein 26-28, 5th floor
6525 GA Nijmegen
The Netherlands

mail: johannes.textor }at{ ru.nl
or: johannes.textor }at{ gmx.de

Research

I lead the Computational Immunology group at the Data Science section of the Institute for Computing and Information Sciences at Radboud University and the department of Tumor Immunology at the Radboud Institute for Molecular Life Sciences, Radboud University Medical Center (Radboudumc), Nijmegen, The Netherlands.

We use simulation models (like this one), machine learning, and causal inference methods (like DAGs) to study information processing in the adaptive immune sytem.

Our work has two main goals. First and foremost, we want to understand how the immune system perceives and interacts with "abnormal" information coming from pathogens or tumors. Such knowledge is useful to design immunological treatments such as vaccines or tumor immunotherapies.

Second, we are interested in designing immunologically inspired machine learning and information processing systems -- Artificial Immune Systems. We use these to understand more fundamentally how the immune system stores, retrieves and modifies information, and how this differs from the second major information-processing system in our bodies, the central nervous system. Ultimately, our goal is to understand why these two marvelously complex information-processing systems exist in our bodies, why they are so different in their architecture, and how they complement each other.

We collaborate with inspiring colleagues -- at the Tumor Immunology department in Nijmegen, and other researchers groups around the world -- trying our best to help them in their research by helping to address computational questions and identifying appropriate statistical methodology.

Publications

Show: complete list | selected publications

Author order is highlighted where it is meaningful (e.g. it is not meaningful in theoretical computer science, but it is in computational biology). If two or more authors are highlighted, this means they contributed equally.

Preprints

2025

2024

2023

Johannes Textor, Franka Buytenhuijs, Dakota Rogers, Ève Mallet Gauthier, Shabaz Sultan, Inge M. N. Wortel, Kathrin Kalies, Anke Fähnrich, René Pagel, Heather J. Melichar, Jürgen Westermann, Judith N. Mandl:
Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity
Cell Systems, 14:1-15, 2023. doi: 10.1016/j.cels.2023.11.004
The T cell receptor (TCR) is pivotal in determining T cell fate, yet analyzing the enormous diversity of TCRs is challenging. We built a machine learning algorithm that scores the self-reactivity of TCR beta chains, and show that this algorithm can stratify complex TCR sequencing data ranging from cells responding to viral infections, to regulatory cells, to thymocytes.
Ian Shrier, Steven D. Stovitz, Johannes Textor:
Identifiability of causal effects in test-negative design studies.
International Journal of Epidemiology, 2023. doi: 10.1093/ije/dyad102
Daniel R. Parisi, Lucas E. Wiebke, Judith N. Mandl, Johannes Textor:
Flow rate resonance of actively deforming particles.
Scientific Reports, 2023. doi: 10.1038/s41598-023-36182-5
Jeroen H.A. Creemers, Ankur Ankan, Kit C.B. Roes, Gijs Schröder, Niven Mehra, Carl G. Figdor, I. Jolanda M. de Vries, Johannes Textor:
In silico cancer immunotherapy trials uncover the consequences of therapy-specific response patterns for clinical trial design and outcome.
Nature Communications 14: 2348, 2023.
Late-stage cancer immunotherapy trials often lead to unusual survival curve shapes, like delayed curve separation or a plateauing curve in the treatment arm. It is critical for trial success to anticipate such effects in advance and adjust the design accordingly. We simulate immunotherapy trials using three different mathematical models to assemble virtual patient cohorts undergoing late-stage immunotherapy, chemotherapy, or combination therapies. All three models predict the distinctive survival curve shapes commonly associated with immunotherapies. We demonstrate how, by simulating various possible scenarios, the robustness of trial design choices such as sample size and randomization rate can be scrutinized, and possible pitfalls can be identified in advance. We provide readily usable, web-based implementations of our three trial simulation models to facilitate their use by biomedical researchers, doctors, and trialists.
Inge Wortel, Johannes Textor:
Interpreting T-cell search “strategies” in the light of evolution under constraints.
PLoS Computational Biology 19(2): e1010918. doi: 10.1371/journal.pcbi.1010918
Ankur Ankan, Inge M. N. Wortel, Kenneth A. Bollen, Johannes Textor:
Combining Graphical and Algebraic Approaches for Parameter Identification in Latent Variable Structural Equation Models.
Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, PMLR 206:7252-7264, 2023.
Ankur Ankan, Johannes Textor:
A Simple Unified Approach to Testing High-Dimensional Conditional Independences for Categorical and Ordinal Data.
Proceedings of the AAAI Conference on Artificial Intelligence 37(10), 12180-12188, 2023. doi: 10.1609/aaai.v37i10.26436

2022

2021

Dakota Rogers, Aditi Sood, HanChen Wang, Jasper J. P. van Beek, Thomas J. Rademaker, Patricio Artusa, Caitlin Schneider, Connie Shen, Dylan C. Wong, Marie-Éve Lebel, Stephanie A. Condotta, Martin J. Richer, Andrew J. Martins, John S. Tsang, Luis Barreiro, Paul Francois, David Langlais, Heather J. Melichar, Johannes Textor, Judith N. Mandl:
Pre-existing chromatin accessibility and gene expression differences among naïve CD4⁺ T cells influence effector potential.
Cell Reports 37(9):110064, 2021. doi: 10.1016/j.celrep.2021.110064
Bettina Weigelin, Annemieke Th Den Boer, Esther Wagena, Kelly Broen, Harry Dolstra, Rob J De Boer, Carl G Figdor, Johannes Textor, Peter Friedl:
Cytotoxic T cells are able to efficiently eliminate cancer cells by additive cytotoxicity.
Nature Communications 12:5217, 2021. doi: 10.1038/s41467-021-25282-3
Inge M N Wortel, Katharina Dannenberg, Jeffrey C Berry, Mark J Miller, Johannes Textor:
CelltrackR: an R package for fast and flexible analysis of immune cell migration data.
Immunoinformatics, 2021. doi: 10.1016/j.immuno.2021.100003
Jeroen H.A. Creemers, Willem J. Lesterhuis, Niven Mehra, Winald R. Gerritsen, Carl G. Figdor, I. Jolanda M. de Vries, Johannes Textor:
A tipping point in cancer-immune dynamics leads to divergent immunotherapy responses and hampers biomarker discovery.
Journal for Immunotherapy of Cancer 9:e002032, 2021. doi: 10.1136/jitc-2020-002032
It remains hard to predict how cancer patients will respond to immunotherapy. Despite efforts to identify new biomarkers using advanced techniques, only a few make it to clinical use. We used computational modeling to simulate the interactions between tumors and the immune system, and used our model to investigate the effects of immune checkpoint inhibition (ICI) on patient survival. Our models showed that the transition from immune control to evasion occurs occurs suddenly rarther than gradually. Patients near this tipping point may therefore benefit significantly from ICI, while those farther away may not. This insight suggests that the varying success of immunotherapy in different patients may be explained by their proximity to this tipping point. We show that this implies that immunological and tumor-related markers need to be combined when aiming to predict tratement success, as these factors jointly determine a patient's position relative to the tipping point.
Inge M N Wortel, Ioana Niculescu, Martijn Kolijn, Nir Gov, Rob J de Boer, Johannes Textor:
Local actin dynamics couple speed and persistence in a Cellular Potts Model of cell migration.
Biophysical Journal, 2021. doi: 10.1016/j.bpj.2021.04.036
Jeroen H.A. Creemers, Maarten J. van der Doelen, Sandra van Wilpe, Rick Hermsen, Tjitske Duiveman-de Boer, Diederik M. Somford, Marcel J.R. Janssen, J. P. Michiel Sedelaar, Niven Mehra, Johannes Textor, Harm Westdorp:
Immunophenotyping reveals longitudinal changes in circulating immune cells during radium-223 therapy in patients with metastatic castration-resistant prostate cancer.
Frontiers in Oncology 11:667658, 2021. doi: 10.3389/fonc.2021.667658
Inge M N Wortel, Johannes Textor:
Artistoo: build, share, and explore simulations of cells and tissues in the web browser.
eLife 10:e61288, 2021. doi: 10.7554/eLife.61288
The cellular Potts model (CPM) can simulate biological processes at tissue scale. Artistoo (Artificial Tissue Toolbox) is a JavaScript library for building ‘explorable’ CPM simulations where viewers can change parameters interactively, exploring their effects in real time. Simulations run directly in the web browser and do not require third-party software, plugins, or back-end servers. The JavaScript implementation imposes no major performance loss compared to frameworks written in C++; Artistoo remains sufficiently fast for interactive, real-time simulations. Artistoo provides an opportunity to unlock CPM models for a broader audience: interactive simulations can be shared via a URL in a zero-install setting. Artistoo has applications in CPM research, science dissemination, open science, and education.
Simone P Sittig, Jasper JP van Beek, Georgina Flórez‐Grau, Jorieke Weiden, Sonja I Buschow, Mirjam C van der Net, Rianne van Slooten, Marcel M Verbeek, P Ben H Geurtz, Johannes Textor, Carl G Figdor, I Jolanda M de Vries, Gerty Schreibelt:
Human type 1 and type 2 conventional dendritic cells express indoleamine 2, 3‐dioxygenase 1 with functional effects on T cell priming.
European Journal of Immunology, 2021. doi: 10.1002/eji.202048580
Ankur Ankan, Inge M N Wortel, Johannes Textor:
Testing Graphical Causal Models Using the R Package "dagitty".
Current Protocols 1(2):e45, 2021. doi: 10.1002/cpz1.45
Peter WG Tennant, Wendy J Harrison, Eleanor J Murray, Kellyn F Arnold, Laurie Berrie, Matthew P Fox, Sarah C Gadd, Claire Keeble, Lynsie R Ranker, Johannes Textor, Georgia D Tomova, Mark S Gilthorpe, George TH Ellison:
Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review & recommendations
International Journal of Epidemiology 50(2), 2021. doi: 10.1093/ije/dyaa213

2020

Stefania Di Blasio, Glenn F van Wigcheren, Anouk Becker, Anne van Duffelen, Mark Gorris, Kiek Verrijp, Irene Stefanini, Gert-Jan Bakker, Martine Bloemendal, Altuna Halilovic, Angela Vasaturo, Ghaith Bakdash, Stanleyson V Hato, Johanne de Wilt, Joost Schalkwijk, I Jolanda M de Vries, Johannes Textor, Ellen H van den Bogaard, Marcella Tazzari, Carl Figdor:
The tumour microenvironment shapes dendritic cell plasticity in a human organotypic melanoma culture.
Nature Communications 11(1):2749, 2020. doi: 10.1038/s41467-020-16583-0
Inge M N Wortel, Can Keşmir, Rob J De Boer, Judith N Mandl, Johannes Textor:
Is T Cell Negative Selection a Learning Algorithm?
Cells 9(3): 690, 2020. doi: 10.3390/cells9030690
The immune system uses cell repertoires to process and store information. Here we build a computer model of such a cell repertoire and show that it's capable of distinguishing between different languages. We use this "toy problem" to show how the immune system could "learn" to distinguish foreign pathogens from the body's own cells. Our model predicts that immunological learning should benefit if the T cell repertoire is "trained" in a certain way during development. We outline experimental approaches to test our prediction.
Nicolas Levernier, Johannes Textor, Olivier Bénichou, and Raphaël Voituriez:
Inverse Square Lévy Walks are not Optimal Search Strategies for d≥2.
Physical Review Letters 124(8), 2020. doi: 10.1103/PhysRevLett.124.080601
Postprint
Jasper JP van Beek, Georgina Flórez-Grau, Mark AJ Gorris, Till SM Mathan, Gerty Schreibelt, Kalijn F Bol, Johannes Textor, I Jolanda M de Vries:
Human pDCs Are Superior to cDC2s in Attracting Cytolytic Lymphocytes in Melanoma Patients Receiving DC Vaccination.
Cell Reports 30(4):1027-1038.e4, 2020. doi: 10.1016/j.celrep.2019.12.096

2019

Benny Chain, Victor Greiff, Johannes Textor, Gur Yaari:
Editorial: Methods and Applications of Computational Immunology.
Frontiers in Immunology, 2019. doi: 10.3389/fimmu.2019.02818
Kasper Soekarjo, Johannes Textor, Rob J de Boer:
Local Attachment Explains Small-World-Like Properties of Fibroblastic Reticular Cell Networks in Lymph Nodes.
Journal of Immunology, 2019. doi: 10.4049/jimmunol.1801016
Preprint
Kellyn F Arnold, George TH Ellison, Sarah C Gadd, Johannes Textor, Peter WG Tennant, Allison Heppenstall, Mark S Gilthorpe:
Adjustment for time-invariant and time-varying confounders in 'unexplained residuals' models for longitudinal data within a causal framework and associated challenges.
Statistical Methods in Medical Research 28 (5): 1347-1364, 2019.
Benito van der Zander, Maciej Liskiewicz, Johannes Textor:
Separators and Adjustment Sets in Ancestral Graphs: Complete Criteria and an Algorithmic Framework.
Artificial Intelligence 270:1-40, 2019. doi: 10.1016/j.artint.2018.12.006
Postprint
The program dagitty.net is widely used to help building graphical models for causal inference. As the researcher builds their model, dagitty analyzes its structure in real time. To make this possible, we needed to develop novel efficient algorithms. This paper collects those algorithms and proves formally that they work as intended. Our methods have since then been picked up by various other researchers and underpin other algorithmic methods and software in addition to our own.
Erinke van Grinsven, Johannes Textor, Lucie S. P. Hustin, Katarina Wolf, Leo Koenderman and Nienke Vrisekoop:
Immature Neutrophils Released in Acute Inflammation Exhibit Efficient Migration despite Incomplete Segmentation of the Nucleus.
Journal of Immunology 202(1):207-217, 2019. doi: 10.4049/jimmunol.1801255

2018

Thijs Roelofsen, Christina Wefers, Mark A. J. Gorris, Johannes Textor, Leon F. A. G. Massuger, I. Jolanda M. de Vries and Anne M. van Altena:
Spontaneous Regression of Ovarian Carcinoma After Septic Peritonitis; A Unique Case Report.
Frontiers in Oncology 8:562, 2018.
Johannes Textor, Anke Fähnrich, Martin Meinhardt, Cornelia Tune, Sebastian Klein, René Pagel, Peter König, Kathrin Kalies, Jürgen Westermann:
Deep Sequencing Reveals Transient Segregation of T Cell Repertoires in Splenic T Cell Zones During an Immune Response.
Journal of Immunology 201(2):350-358, 2018.
Emilija Perković, Johannes Textor, Markus Kalisch, Marloes H. Maathuis:
Complete graphical characterization and construction of adjustment sets in Markov equivalence classes of ancestral graphs.
Journal of Machine Learning Research 18(220):1−62, 2018.
Felix Thoemmes, Yves Rosseel, Johannes Textor:
Local Fit Evaluation of Structural Equation Models Using Graphical Criteria.
Psychological Methods 23(1):27-41, 2018.
Postprint | R code
Model testing is a crucial part of causal inference because all causal inference predictions are predicated on the underlying model being true, or at least not too wrong. This paper unifies various types of model testing under one common umbrella: local testing, where we do not only aim to check whether our model is false, but also where exactly the problem lies. We also present software to perform this type of testing easily.
Mark A. J. Gorris, Altuna Halilovic, Katrin Rabold, Anne van Duffelen, Iresha N. Wickramasinghe, Dagmar Verweij, Inge M. N. Wortel, Johannes Textor, I. Jolanda M. de Vries, Carl G. Figdor:
Eight-Color Multiplex Immunohistochemistry for Simultaneous Detection of Multiple Immune Checkpoint Molecules within the Tumor Microenvironment.
Journal of Immunology 200(1):347-354, 2018.

2017

2016

2015

Ioana Niculescu, Johannes Textor, Rob J. de Boer:
Crawling and Gliding: A Computational Model for Shape-Driven Cell Migration.
PLoS Computational Biology 11(10):e1004280, 2015.
Xiangyu Rao, Ilka Hoof I, Debbie Van Baarle, Can Keşmir, Johannes Textor:
HLA Preferences for Conserved Epitopes: A Potential Mechanism for Hepatitis C Clearance.
Frontiers in Immunology 6:552, 2015.
People who have the gene "HLA-B27" are more likely to clear Hepatitis C virus (HCV) infections. We show that the immune system of such people is likely to attack conserved regions of the HCV genome (marked in red), which the virus cannot easily mutate. This could explain why HLA-B27 is a beneficial gene for controlling HCV.
Jürgen Westermann, Tanja Lange, Johannes Textor, Jan Born:
System Consolidation During Sleep – A Common Principle Underlying Psychological and Immunological Memory Formation.
Trends in Neurosciences 38: 583-595, 2015.

In this opinion article, we note some intriguing parallels between memory in the central nervous system and memory in the immune system. Based on these, we argue why sleep strengthens memory in both systems.
Highlighted in EurekAlert!
Justin M. Richner, Grzegorz B. Gmyrek, Jennifer Govero, Yizheng Tu, Gerritje J. W. van der Windt, Talibah U. Metcalf, Elias K. Haddad, Johannes Textor, Mark J. Miller, Michael S. Diamond:
Age-Dependent Cell Trafficking Defects in Draining Lymph Nodes Impair Adaptive Immunity and Control of West Nile Virus Infection.
PLoS Pathogens 11(7): e1005027, 2015.
Highlighted in EurekAlert!
Johannes Textor, Alexander Idelberger, Maciej Liskiewicz:
Learning from Pairwise Marginal Independencies.
In Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), pp. 882-891. AUAI Press, 2015.
Emilija Perkovic, Johannes Textor, Markus Kalisch, Marloes Maathuis:
A Complete Generalized Adjustment Criterion.
In Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), pp. 682-691. AUAI Press, 2015.
Benito van der Zander, Johannes Textor, Maciej Liskiewicz:
Efficiently Finding Conditional Instruments for Causal Inference.
In Proceedings of the 24th International Joint Conference on Artificial Intelligence (IJCAI 2015), pp. 3243-3249. AAAI Press, 2015.
Paola Masuzzo, Lennart Martens, 2014 Cell Migration Workshop Participants:
An open data ecosystem for cell migration research.
Trends in Cell Biology 25(2):55-8, 2015.

2014

Johannes Textor, Sarah E. Henrickson, Judith N. Mandl, Ulrich H. von Andrian, Jürgen Westermann, Rob J. de Boer, Joost B. Beltman:
Random Migration and Signal Integration Promote Rapid and Robust T Cell Recruitment.
PLoS Computational Biology 10(8): e1003752, 2014.

The immune system's T cells are constantly on the move: they migrate between different lymphoid organs approximately once per day (A), and move within these organs in a random fashion (B), changing their direction every few minutes. We model this two-scale search and show how this contributes to quick detection of invading pathogens.
PDF preprint
Benito van der Zander, Maciej Liskiewicz, Johannes Textor:
Constructing Separators and Adjustment Sets in Ancestral Graphs.
In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI 2014), pp. 907-916. AUAI Press, 2014.
Technical report version (including proofs)
Johannes Textor, Katharina Dannenberg, Maciej Liskiewicz:
A Generic Finite Automata Based Approach to Implementing Lymphocyte Repertoire Models.
In Proceedings of the 2014 conference on genetic and evolutionary computation (GECCO'14), pp. 129-137. ACM, 2014.
PDF preprint
David Banczyk, Kathrin Kalies, Lars Nachbar, Lars Bergmann, Philipp Schmidt, Ulrike Bode, Bianca Teegen, Philipp Steven, Tanja Lange, Johannes Textor, Ralf J Ludwig, Winfried Stöcker, Peter König, Eric Bell, and Jürgen Westermann
Activated CD4(+) T cells enter the splenic T-cell zone and induce auto-antibody-producing germinal centers through bystander activation.
European Journal of Immunology 44 (1):92-102, 2014.

2013

2012

2011

Johannes Textor:
Our Moral Ancestors: Determining Adjustment Sets in Causal Diagrams with Ease (in German).
Gesundheitswesen, 73:897-900, 2011.
Johannes Textor, Juliane Hardt, Sven Knüppel:
DAGitty: A Graphical Tool for Analyzing Causal Diagrams.
Epidemiology, 5(22):745, 2011.
Rüdiger Reischuk, Johannes Textor:
Stochastic Search With Locally Clustered Targets: Learning from T Cells.
In 10th International Conference on Artificial Immune Systems (ICARIS 2011), Volume 6825 of Lecture Notes in Computer Science, pp. 146-159. Springer, 2011.
PDF preprint
Johannes Textor, Antonio Peixoto, Sarah E. Henrickson, Mathieu Sinn, Ulrich H. von Andrian, Jürgen Westermann:
Defining the Quantitative Limits of Intravital Two-Photon Lymphocyte Tracking.
PNAS, 108(30):12401-12406, 2011.
Two-photon imaging allows to track cells in living animals. But lymphocytes may spend days in lymph nodes, and two-photon imaging can only run for a few hours. We wondered how much this limits the precision with which we can describe lymphocyte motion based on such experiments. By simulating T cell motion in a realistic artificial lymph node that we reconstructed from tissue slices, we show that important behaviors can indeed escape two-photon imaging.
Johannes Textor, Maciej Liskiewicz:
Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective.
In Proceedings of the 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011), pp. 681-688. AUAI Press, 2011.
PDF preprint
Michael Elberfeld, Johannes Textor:
Negative Selection Algorithms on Strings with Efficient Training and Linear-Time Classification.
Theoretical Computer Science, 412(6):534-542, 2011.
PDF preprint

2010

Maciej Liskiewicz, Johannes Textor:
Negative Selection Algorithms Without Generating Detectors.
In Proceedings of the 12th annual conference on Genetic and evolutionary computation (GECCO'10), pp. 1047-1054. ACM, 2010.
PDF preprint

2009

2008

Johannes Textor, Björn Hansen:
Improved Simulation Algorithms for Agent Based Models of the Immune Response.
In Proceedings of the 19th European Meeting on Cybernetics and Systems (EMCSR 2008), pp. 476-481. Austrian Society for Cybernetic Studies, 2008.
PDF preprint

2007

Johannes Textor, Jürgen Westermann:
Modeling Migration, Compartmentalization, and Exit of Naive T Cells in Lymph Nodes Without Chemotaxis.
In 6th International Conference on Artificial Immune Systems (ICARIS 2007), Volume 4628 of Lecture Notes in Computer Science, pp. 228-239. Springer, 2007.
PDF preprint

PhD Dissertation

My PhD thesis was carried out at the Institute of Theoretical Computer Science, University of Luebeck, Germany, under joint supervision of Rüdiger Reischuk (Theoretical Computer Science) and Jürgen Westermann (Immunology).

Johannes Textor:
Search and Learning in the Immune System: Models of Immune Surveillance and Negative Selection.
PhD Dissertation, University of Luebeck, 2011.
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Software

Some software I wrote for my research is available for download. You can also visit my profile on github.

An experimental implementation of my work on efficient negative selection algorithms written in Java.
DAGitty, a tool to draw and analyze causal diagrams written in JavaScript.
LImmSim, an agent-based simulation of the immune system written in C++.
R packages for epitope prediction, cell track analysis, and causal analysis.

Awards & important grants

Dates listed refer to the year in which the award was given.

Program Grant (USD 1050K), Human Frontiers Science Program, 2020.
Vidi Grant (€ 800K), Netherlands Organization for Scientific Research, 2019.
Bas Mulder Award (€ 500K), Dutch Cancer Research Foundation, 2017.
IBM Best Student Paper Award 2014 for our paper (first author: Benito van der Zander) "Constructing Separators and Adjustment Sets in Ancestral Graphs" at UAI 2014.
Stephan Weiland Preis, young investigator's award by the German society for Epidemiology, 2012.
GI Dissertationspreis 2011, joint award by the German, Austrian and Swiss societies for computer science for the best computer science dissertation of the year, 2012.

Press releases (in German): GI | Uni Lübeck
Staatlicher Universitätspreis 2011, award for the best STEM dissertation, University of Lübeck, Germany, 2012.
Best paper awards at the international conference on artificial immune systems (ICARIS) in 2012 and 2009; best student paper award at ICARIS in 2007; nominated for best paper award at GECCO 2010 (genetics based machine learning track).