Meet our academics – Professor Korbinian Strimmer
Meet the School 4th April 2018
In this new series of blogs, we chat to the academics you’ll meet, be taught by and work with during your time in the School of Mathematics. In this post, we catch up with Chair in Statistics Professor Korbinian Strimmer. We asked him about his work and what he gets up to when he can tear himself away from his research.
Where were you based before moving to Manchester?
Before joining the School of Mathematics in November 2017, I was a Reader in Biostatistics and Computational Biology at Imperial College London, and before that I was a W2 Professor (equivalent to Senior Lecturer) at the University of Leipzig in Germany. My Alma Mater is the University of Munich, where I studied and did my Ph.D. and where I also held a position as Emmy Noether research group leader (similar to Lecturer) at the Institute of Statistics.
Please can you describe your research, for the layman, in 10 sentences or less?
My research is all about methods for learning from complex high-dimensional data, primarily with biomedical applications in mind. In particular, I am interested in approaches that are both computationally as well as statistically efficient, i.e. in devising methods that scale well and perform well for the large data sets common in personalised medicine and genomics. For example, I have developed methodology for learning large-scale graphical models to reconstruct molecular genetic networks, for multiple testing and signal detection in high dimensions using false discovery rates, and for variable and feature selection to help predict outcomes and identify relevant biomarkers. I am also interested in linking classical statistical approaches with modern machine learning algorithms, with the aim to develop more interpretable and less black box type approaches to data science.
How did you first become interested in your research area?
My background is actually theoretical physics, and in my diploma (MSc) thesis I worked on general relativity. It was during my Ph.D. that I discovered my interest in statistics while developing a likelihood-based framework to infer evolutionary relationships from sequence data using a stochastic process to model mutations along edges in a graph. This method was one of the first that was practically applicable for data with more than a handful of sequences, and it started my research journey into statistical learning and biomedical data science.
How are you finding your role?
It has been an exciting start for me here in Manchester. From the beginning, I have been very busy meeting many people from both within the School and across Faculties and Institutes. It is very stimulating to be part of the excellent research environment here in Manchester, spanning mathematics and statistics, computer science and machine learning, and life sciences and medicine. It is also fantastic news that Manchester is now part of the Alan Turing Institute, the national institute for data science.
What do you get up to in your spare time?
It is very likely that you will find me in a museum visiting a recently opened exhibition, or at a concert – both classical and modern – exploring the rich cultural and music scene of Manchester. For the next summer, my plan is to go hiking in the countryside around Manchester, especially the Peak District, and to see the Yorkshire Sculpture Park.
We’ll have a new academic interview for you on the blog soon.