Welcome Bastian Rieck

After several years at the Machine Learning and Computational Biology Lab of ETH Zurich in Switzerland, Bastian Rieck returns to Germany.

At Helmholtz Zentrum München, Bastian will work at the interface of Helmholtz AI and HPC, taking advantage of this close collaboration to focus on the development of topological machine learning techniques in the context of healthcare applications. 


1. Welcome to Helmholtz Zentrum München and welcome to Munich. What are your expectations as a PI at HPC? What will be the focus of your research at HMGU?

Bastian: Thank you very much for the warm welcome! I am very excited about stepping into this role, and I look forward to building up a team to tackle challenges at the intersection of machine learning and healthcare. I expect that this will be quite an adventure: I will have to build a research group from scratch, get people excited about my research agenda, and much more. When it comes to the focus of my research, I want to stay partially true to my roots in topological machine learning, but I am also looking forward to expanding my research interests quite considerably. When it comes to the healthcare applications I envisioned, there is definitely a multitude of approaches that I want to try out. I have already some projects planned that build on my previous work in the analysis of MRI data sets, for instance. Recently, I also got interested in single-cell data analysis and helped in organising a data analysis competition. I am sure that this could become another interesting direction to pursue!

2. You are not only PI at HPC, but you will also be routed in the new Institute of Artificial Intelligence for Health and closely working with the computational community at Helmholtz Munich and Hemholtz_AI. What advantages do you expect for your research by working at such an exciting scientific interface?

Bastian: That is something I find extremely enticing! There are so many scholars, all experts in their respective fields, being brought together under the auspices of Helmholtz and the Munich-based science community at large. I am over the moon to be part of such an endeavour and 'get in on the ground floor,' as they say. In my opinion, many important discoveries and scientific advancements have in the past and continue to happen at exactly the intersection of multiple fields. Progress in machine learning is also largely driven by groups that can work synergistically, combining numerous perspectives and backgrounds. I am confident that together,Helmholtz, Helmholtz_AI and the HPC will help shape this new exciting chapter in the biomedical sciences!

3. You spent the last few years at ETH Zurich after doing your PhD in Heidelberg. Are there differences in science between Germany and Switzerland? Or what distinguishes scientific work in the two countries?

Bastian: Both countries have a lot to offer when it comes to research! I am happy to see that they are investing in AI research; this will be a key technology for the next decades. The largest differences I observed relate to Switzerland being a relatively small country (and I mean this in a very positive way): in Switzerland, it is possible to build national consortia rather easily and with extremely flat hierarchies. This does unfortunately not scale to a country such as Germany whose size necessitates additional layers to manage everything! However, larger initiatives also bear the promise of acquiring more data, which is crucial for training modern machine learning algorithms in many cases...
I am looking forward to continuing my collaborations with Swiss institutions and other international partners, and connecting them to our hub for AI and Healthcare here in Munich!

4. You've only been in Munich for a short time. Is there anything you are particularly looking forward to?

Bastian: I am mostly looking forward to visiting all the parks! If the pandemic has taught me anything, it is that I can easily recharge my batteries while strolling through nature. If the weather plays its part, I intend to make the best use of my time during autumn. As a photography buff, autumn is the best season in any case because of the great light conditions.