I have a background in statistics, and my main research interest has been statistical modeling of complex phenomena. I have mostly worked with statistical applications arising from the biological sciences, with the focus shifting from population genetics and evolutionary biology to ecology. During my PhD, I studied the evolution of genetic population structure based on allele frequency change ("population phylogenetics"). After that my main research direction switched to simulation-based inference methods (e.g. approximate Bayesian computation, ABC) with a special emphasis on generating predictions from individual based models in population ecology. In addition, I have worked on various other applied projects from many fields ranging from criminal psychology to computational linguistics. I have wide experience in different areas of statistics including theory, experimental design, exploratory analyses, computational statistics, inference and software development. I prefer to take a Bayesian approach to statistics, which allows us to coherently take into account all uncertainty and provides the regularization necessary for inference with complex models. Currently, in the Biodata Analytics Unit, I am continuing with ABC-based prediction research, as well as working in several applied projects using more standard statistical methods such as GLMMs.
I am a bioinformatician/computational biologist with broad knowledge in molecular and clinical data analysis. At the molecular level, I have extensive experience in transcriptomics data analysis and methods development. So far, the main focus of my projects has been on developing computational and meta-analysis techniques for detecting and characterizing molecular and clinical markers playing a role in the diagnosis and prognosis of complex diseases such as cancer. In particular, I have developed various types of clinical predictive models (e.g., survival models) using statistical and machine learning approaches. Currently, I am working on wide range of transcriptomics projects in the Biodata Analytics Unit.
I have a computer science background and in-depth expertise in theoretical and practical computation. I have been working on computational problems and software development in biology and bioinformatics since before my MSc (2005) and PhD (2009). After my PhD, I started pursuing linkage mapping and this has since become my main research direction. I have published and developed the popular software suite Lep-MAP (versions 1, 2 and 3) for linkage mapping and Lep-Anchor for linkage map guided genome anchoring. I have been developing new software and working on genome assemblies, genomics and population genetics for many groups, projects and non-model species. I have continued my research in the Biodata Analytics Unit, helping and providing expertise to many research groups at the Viikki campus on genomic and other studies.