Master of Science in Biomedical Data Analytics

This program aims to introduce BME graduate students to the mathematical and computational methods of biomedical data analysis and to demonstrate the application of these methods to selected domains of high importance for Biomedical Engineering (e.g. biomedical signal and system analysis, medical imaging, clinical diagnostics and treatment monitoring). In other words, our students will be able to use computational methods to extract new, valuable knowledge from measurements made in hospital and laboratory settings. The general philosophy of this program is that Data Analytics will be a key factor in the development of the “new medicine” in the 21 century. Graduates will have a firm knowledge of not only the “know how,” but also the “know why” of Data Analytics in BME.

International Students: This program is eligible for the OPT STEM extension.

Please Note: Requirements for graduation, course offerings, course availability, track offerings and any other degree requirements are subject to change. Students should consult with an academic advisor prior to registering for any classes.

Program of Study

Select one of the following degree completion options:

Option 1: Coursework Only

Option 2: Coursework + Master's Thesis

Degree Course Requirements

A minimum of 28 units is required for this degree.

1. Required 5 courses (20 units)

  • BME 511 | Physiological Control Systems (4 units)
  • BME 513 | Signal and Systems Analysis (4 units)
  • BME 514 | Physiological Signals and Data Analytics (4 units)
  • BME 515 | Data Analytics in Biomedical Engineering (4 units)
  • BME 528 | Medical Diagnostics, Therapeutics and Informatics Applications (4 units)

2. Technical Electives (select a minimum of 8 units from the following courses)

  • BME 423 | Statistical Methods in Biomedical Engineering (4 units)
  • BME 501 | Advanced Topics in Biomedical Systems (4 units)
  • BME 502 | Advanced Studies of the Nervous System (4 units)
  • BME 530 | Introduction to Systems Biology (4 units)
  • DSCI 552 | Machine Learning for Data Science (4 units)
  • DSCI 553 | Foundations and Applications of Data Mining (4 units)

***All information contained here is summarized from the USC Catalogue and is considered non-official. For all rules, regulations, procedures, and outlines, please see the current academic year USC catalogue.

There is no comprehensive exam requirement.