Computational interaction with Bayesian methods

Per Ola Kristensson, Antti Oulasvirta, Nikola Banovic, John Williamson

Research output: Contribution to conferenceAbstractScientificpeer-review

2 Citations (Scopus)


This course introduces computational methods in human-computer interaction. Computational interaction methods use computational thinking-abstraction, automation, and analysis-to explain and enhance interaction. This course introduces the theory of practice of computational interaction by teaching Bayesian methods for interaction across four wide areas of interest when designing computationally-driven user interfaces: decoding, adaptation, learning and optimization. The lectures center on hands-on Python programming interleaved with theory and practical examples grounded in problems of wide interest in human-computer interaction.

Original languageEnglish
Number of pages6
Publication statusPublished - 2 May 2019
MoE publication typeNot Eligible
EventACM SIGCHI Annual Conference on Human Factors in Computing Systems - Glasgow, United Kingdom
Duration: 4 May 20199 May 2019


ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleACM CHI
Country/TerritoryUnited Kingdom
Internet address


  • Computational interaction
  • Inference
  • Machine learning
  • Optimization


Dive into the research topics of 'Computational interaction with Bayesian methods'. Together they form a unique fingerprint.

Cite this