Martin Slawski

Given his background in both Statistics and Computer Science, Martin Slawski is interested in tackling problems arising at the interface of the two fields, an area that is nowadays often referred to as "Data Science." In his research, Slawski studies computationally tractable methods that yield a compact representation of high-dimensional data. One recent focus involves randomized methods of dimensionality reduction and the associated computational-statistical trade-offs. Slawski also enjoys working on applications in interdisciplinary teams, in particular on problems involving biological data from high-throughput experiments.  

Research Interests

• High-dimensional statistical inference
• Dimension reduction
• Optimization methods for data analysis
• Statistical and computational trade-offs

Degrees

• PhD, Computer Science, Saarland University
• MSc., Statistics, LMU München