Group @ RöttgerLab

Head of the Group

Richard Röttger

I am a 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, promotion to Full Professor November 2022) and have since been actively research in various kinds of machine learning of biomedical data.

In our work, we focus primarily on various aspects of machine learning and data mining of biomedical data and on developing innovative approaches for systems medicine. Many of the projects are conducted in the close cooperation with the Odense University Hospital as well as with the Department of Biochemistry and Molecular Biology. We are involved in several large European as well as Danish research projects.

For a detailed CV and a list of publications, see here.
For an overview of the groups projects and activities, see here.

Office: V9-601a-2. Interactive Room map.
Hours: just write me an email

Group Members


Pawel Palczynski

I have joined the Computational Biology Group at SDU as a Postdoc in November of 2021. Currently I am working on developing neural networks for protein predictions based on large scale mass spectrometry data. I hold an MEng and a PhD degree from Imperial College London in Materials Science and Engineering. During my PhD project I have worked on synthesis and physical characterisation of atomically thin 2D materials, optimising synthesis and preparing devices.

Office: V9-602b-2. Interactive Room map.

PhD Students

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.

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.

Juan Francisco Marin Vega

I am an industrial PhD student since December August 2019 in collaboration with ESoft A/S. I hold a MSc degree in computer science. Currently, I am working on advanced image enhancement techniques for copyediting in professional settings.

Office: V9-602a-2. Interactive Room map.

Jiawei Zhao

I have been a PhD candidate at SDU since May 2022, co-supervised by Prof. Röttger and Novo Nordisk. I hold an MSc degree in bioinformatics at Lund University. I gained project experience in structural protein bioinformatics, web programming, and human population genomics during my MSc studies. Currently, I am working on developing a federated metadata repository amenable to federated ML algorithms within the Screen4Care project.

Office: V9-602b-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.

Tobias Greisager Rehfeldt

I started my Ph.D. right after the completion of my Masters degree in 2020. I am currently residing in the Bioinformatics department of SDU headed by Richard Röttger.

I have a masters' degree in Computational Biomedicine and a bachelors' degree in Economics. My masters' thesis revolved around the idea of using mass spectrometry data coupled with neural networks, in an attempt to circumvent parts of the current MS pipeline. This is also the project that later developed into my Ph.D. position here at SDU.

Daily I sit and work trying to come up with new ways of extrapolating and using mass spectrometry data, and finding new and innovative neural network architectures.

Office: V9-602a-2. Interactive Room map.

Muhammad Irfan Malik

I am a PhD student in the Computational Biology group headed by Richard Röttger since April 2022.

I hold a master’s degree in computer science. I gained project experience in unsupervised Lifelong Machine learning for Data Analysis. I graduated from National University of Computer and Emerging Sciences (FAST) Pakistan.

The focus of my PhD research work is on developing a federated metadata repository amenable to privacy-aware federated machine learning algorithms within the Screen4Care project, artificial intelligence (AI)-based tools for the early identification of undiagnosed patients.

Office: V9-602b-2. Interactive Room map.

Student Members

  • Margrethe Crisostomo Thusholt

    Detecting and quantifying vulnerable exon in a splice junction database - Individual Study Activity
  • Annika Andersen and Palle Sorth Bendixen

    TBA - Master thesis Data Science
  • Rasmus Victor Jensen

    TBA - Master thesis Computational Biomedicine
  • Jennifer Rugaard Bregndahl Jensen

    Time series analysis of plasma protein profiles for randomized control trial of psoriatic arthritis patients. - Master thesis Computational Biomedicine
  • Casper Juul Majgaard Nielsen

    Applied generative adversarial networks for high resolution images - Master thesis in Computer Science
  • Villads Winton

    In silico integration of spatial transcriptomics with scRNAseq - Master thesis Computational Biomedicine
  • Zsófia Magyar

    Studying vulnerable exons and finding effective ways for prediction - Master thesis Computational Biomedicine