Course Description

This course will introduce students to the emerging field of Activity-Aware Computing -- a multidisciplinary research area that draws from Machine Learning and AI, Machine Perception, Ubiquitous Computing, Human Computer Interaction, as well as psychology and sociology. Most of the course will be devoted to discussing the various machine learning approaches that have been developed to make computers and mobile devices more aware of people, their activities, and their surrounding context. Discussions will highlight the various research challenges in data collection,  representation and tractability of models, and evaluation. We will brain-storm ideas on how future research can go about tackling some of these challenges.

Students will be required to read and critique papers. Everyone will take turns in presenting the material and in leading discussions. Participation in discussions will be evaluated. I will do a brief weekly lecture on the core machine learning concepts presented in the papers assigned for that week. Students will also be required to propose and complete a final project. There will be no mid-term or final exams.

Pre-requisites: Some background in Machine Learning/AI, Statistics, Signal Processing and Ubiquitous Computing either from course work or research will be useful but not required. If you are interested in the course and but not sure whether you have the right background, please come talk to me. Must be a competent programmer and familiar with or willing to learn Matlab. 

Administration