SICSA Summer School
Inference, optimisation and modelling for the engineering of interactive systems
22nd-26th June 2015
interaction. This will encompass modelling of interaction, deriving and engaging with statistical models of content, automatic learning of preferences and computer-assisted optimisation of interfaces. Applied machine learning and appropriate quantitative analysis, suitable for real-time, closed-loop interactions will be key elements of the summer school school programme.
The course content will include quantitative user modelling, machine learning, intelligent signal processing, crowdsourced and mass-scale interface optimisation techniques and automatic interface optimisation . The school will cover techniques interconnection of large statistical models and low-level interaction primitives, from optimising keyboards from language models, interface layout optimisation from preference learning, synthesising crowdsourced sensor data for ubiquitous computing, to optimising pointing and gesturing.
The distinctive flavour of the school will be in applying these techniques in concrete human-centred applications, with real-world data and real-time, online contexts.
There will be a strong focus on developing applied skills through practical sessions integrated into the school programme, which will give students practical experience in using well-grounded, cutting edge analysis, modelling and inference in engineering interactive systems.
One of the school outcomes will be a self-contained preprepared development and testing environment including development languages and libraries, datasets, links to online resources and the presented course content.