Head of the Group

Richard Röttger, Associate Professor, Dr. rer. nat.

I am an Associate Professor for Bioinformatics at the University of Southern Denmark (SDU) at the Department for Mathematics and Computer Science (IMADA) and head of the Computational Biology Group. I started at SDU in Summer 2014 as Assistant Professor (promotion to Associate Professor in November 2017) and have since been actively research in various kinds of machine learning of biomedical data. I furthermore spent 5 month on a Sabbatical leave at the University of Cambridge at the Medical Research Council Laboratory of Molecular Biology (MRC-LMB) in the group of Prof. Madan Babu. Before I joined SDU, I received my PhD (Dr. rer. nat.) from the Max-Planck-Institute for Informatics, in Saarbrücken for my work on Active Transitivity Clustering. I was awarded an International Max Planck Research School (IMPRS) PhD fellowship for my research at the Max Planck Institute. Before my PhD studies, I studied computer science at the Technical University of Munich (TUM) and Technology Management at the Center for Digital Technology and Management (CDTM). During my studies I had two research visits at the University of California at Berkeley at the School of Information as well as at the International Computer Science Institute where my diploma thesis originated. My thesis on the completeness of gene regulatory networks was awarded with the prestigious Siemens price.

Office: V9-601a-2. Interactive Room map.
Hours: just write me an email
Web: http://imada.sdu.dk/~roettger

Group Memebers

Anne Hartebrodt

I am a PhD student in the Computational Biology group headed by Richard Roettger since February 2019.

I graduated from the joint Bioinformatics programme at Technical University of Munich (TUM) and Ludwig-Maximilians-Universitaet Munich (LMU). In my Master’s Thesis at the Chair of Experimental Bioinformatics I worked on probabilistic de-novo pathway detection in biological networks using OMICs data under the supervision of Markus List and Jan Baumbach.

The focus of my PhD project is on privacy-aware federated machine learning, more specifically unsupervised learning and federated data normalization methods. As part of the H2020 FeatureCloud Consortium, I work on enabling the use of sensitive medical data for research purposes while preserving patient privacy.

Office: V9-601b-2. Interactive Room map.

Dominika Hozakowska-Roszkowska

I am a PhD student since December 2018. I hold a uniform MSc degree in Medical Laboratory Science from Medical University of Warsaw (Poland) and MSc degree in Computational Biomedicine from University of Southern Denmark. Currently, I am working on a large-scale analysis and machine learning of the distribution of genetic traits in populations.

Office: V9-601b-2. Interactive Room map.

Mathias Emil Bøgebjerg

I have a Bachelor Degree in Computer Science from IMADA on SDU, and started my PhD as a 4+4 on the 15th of September 2018. Medications have many years of research behind them, yet they are often ineffective on patients. We believe that the reason for this is that the patients are ill-classified; they show the same phenotypic symptoms, but might have different underlying causes. I work on patient stratification using unsupervised learning, to find these hidden causes.

Office: V9-601b-2. Interactive Room map.

Affiliated Members

Christian Wiwie, PhD

I'm a Postdoc the University of Southern Denmark since March 2017. Currently, I am involved in developing unsupervised methods for integrated analysis of time-series data together with biological networks. Previously, I was a PhD student in Jan's group where I developed ClustEval, a framework for cluster analysis, and TiCoNE, an integrated clustering approach for time-series data together with biological network.

Office: V9-601b-2.

Simon Larsen

Office: Room V9-602a-2

Philipp Weber

I am a PhD student in the Computational Biology group at the University of Southern Denmark since September 2017. Earlier in 2017 I obtained my master’s degree in bioinformatics from the University of Tübingen. In my PhD project I focus on developing new methods for the processing and analysis of breath and biogas data with the help of deep neural network architectures. My research interest also includes the development of new approaches for detection and treatment of cancer in a personalized setting.

Office: Room V9-602a-2

Tobias Frisch

Since March 2017 I am a PhD student at the Computational Biology group at the University of Southern Denmark. In my work I collaborate with the group of Prof. Zsolt Illés from the neurology department at Odense University Hospital. I am interested in un/supervised machine learning in OMICS data with a focus in RNA-Sequencing. Additionally, I am developing machine learning methods for privacy-aware federated machine learning. I am holding a MSc degree in Bioinformatics from Freie Universität Berlin and a BSc degree in Bioinformatics from Saarland University, Saarbrücken.

Office: Room Ø16-512-1

Alexander Grønning

Office: Room Ø16-512b-1 Kontor


I'm a PhD student affiliated with the Computational Biology group at the University of Southern Denmark, the Clinical Genetic Department and the Neurological Research Group of Zsolt Illes at Odense University Hospital since February 2017. Before, I studied biomedicine at the University of Southern Denmark. During my education I have also stayed abroad in Austria at Institute of Neurology, Medical University of Vienna, in Sweden at Department of Chemistry and Molecular Biology, Gothenburg University and in England at Division of Brain Sciences, Imperial College, London. I have experience with animal models, cell biology, molecular biology, histopathology and genetics. During my PhD, we are exploring molecular signatures (transcriptome and methylome) and nuclei signatures of human brain lesions from multiple sclerosis patients. We are examining markers related to damage and repair in the human brain, and exploring novel repair-related pathways with the main focus on identifying key molecules for potential treatments.

Office: SUND

Jesper Lund

Office: SUND

Weilong Li

Office: SUND

Afsaneh Mohammadnejad

Office: SUND

Student Members

  • Mads Kempf

  • Extraction, analysis and processing of near-infrared spectroscopy spectra for fish feed quality control

  • Hans Kristian Møller

    Autoamted generation of 3D-models using generative adveserial networks.

  • Aleksandrs Aksjonovs

    Time-series clustering of gene expression data using deep neural networks

  • Tobias Greisager Christensen

    Tandem-Mass spectrometry prediction based on Liquid Chromatography-Mass Spectrometry chromatogram using deep neural networks

  • Mathias Strange Hansenn

    Comprehensive performance analysis of state-of-the-art scRNA imputation methods

  • Magnus Ganer Jespersen

    Combining convolutional neural networks and hyperspectral imaging to detect bacteria on meat.

  • Klaus Thomas Kristiansen

    Deciphering the Barcode of Chemokines

  • Juan Francisco Marin Vega

    Natural Language Generation in a copywriting context

  • Luca Dorigo

    Building a database for computer-aided diagnosis using natural language processing

  • Arianna Tonazzolli

    Viral transcripts in Multiple Sclerosis