Signal processing is the science of extracting information from signals of every kind, and it has two distinct aspects: characterization and categorization. Traditionally, signal characterization has been performed with mathematically-driven transforms, while categorization and classification are achieved using statistical tools. Machine learning aims to design algorithms that learn about the state of the world directly from data. An increasingly popular trend has been to develop and apply machine learning techniques to both aspects of signal processing, often blurring the distinction between the two. This course discusses the use of machine learning to process signals — from data-driven approaches for characterizing audio, speech, images and video, to machine learning methods for a variety of speech and image processing problems.

Schedule Syllabus

Course logistics

Details are confirmed shortly before the semester begins.

  • Meetings TBD Days and times are set when the university timetable is published.
  • Location TBD Room assignment pending.
  • Remote attendance TBD A Zoom link will be posted here and on Canvas.
  • Discussion & Q&A Piazza TBD The Fall 2026 Piazza space will be linked before the first lecture.
  • Assignment submissions Canvas TBD For registered students only, once the course site opens.
  • Contact Course questions go to Piazza Until it opens, email the instructor at bhiksha@cs.cmu.edu. Announcements are posted here and on Piazza.

Teaching staff

Additional teaching assistants will be added as they are confirmed.

Office hours

Published in the first week of classes.

TBD

Office hours are not scheduled yet

Times, locations and Zoom links will be posted here once the teaching staff and the class timetable are finalized for Fall 2026. Until then, please email the instructor for anything urgent.

Announcements

No announcements yet. Course announcements for Fall 2026 will appear here and on Piazza once the semester gets underway.