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

  1. Conversation Moderator project
  2. Automated Pupil Dilation measurement
  3. Automated Activity Counts
  4. Hidden Markov Models to improve static classification of sensor data