We develop methods for efficient probabilistic inference in complex modelling problems. We develop models for genomic time series data using Gaussian processes and methods for quantitative analysis of sequencing data. We also develop theory and methods for efficient differentially private Bayesian inference.
HIIT researchers Airi Lampinen and Tapio Ikkala are contributing to timely debates on the sharing economy with their new research, published this week at the internationally renowned ACM CSCW 2014 conference. The conference is held this year in Baltimore in the United States. CSCW is the largest annual research conference focusing on computer-supported cooperative work.