Bayesian Signal Processing Lab
The Bayesian Signal Processing group uses modern statistical and computational techniques to make inferences from complex data sets, with a particular emphasis on continuous sensor processing ranging from video, audio, or other rich sensor signals.
The lab is a loosely-organized group of research students led by Ting Xiao, who is currently a full-time particle physics postdoctoral fellow at Northwestern University but also teaching as an adjunct in Loyola University Chicago's computer science department.
Current projects of the Bayesian Signal Processing group
- Conversation Moderator project
- Automated Pupil Dilation measurement
- Automated Activity Counts
- Hidden Markov Models to improve static classification of sensor data