Digital Health Technology Photo

Digital Health Technology

Digital health tools have the vast potential to improve our ability to accurately diagnose and treat disease and to enhance the delivery of health care.

This area of study will integrate faculty expertise from Computer Science, Bioengineering, Electrical and Computer Engineering, Computational Medicine and the David Geffen School of Medicine.

The curriculum will focus on analyzing biomedical data, combining data sciences, mobile health, health information technology, wearable devices and personalized medicine.

Prof. Eleazar Eskin Photo

“At UCLA, there is groundbreaking research going on — both in engineering and medicine. Digital Health Technology is designed to connect both of these fields to improve quality of life.”

Area Director: Prof. Eleazar Eskin

 

Sample Curriculum

Fall Winter Spring Summer

COM SCI CM222
Algorithms in Bioinformatics

(Instructor: Prof. E. Eskin)

COM SCI M225
Computational Methods in Genomics

(Instructor: Prof. J. Ernst)

COM SCI CM224
Machine Learning Applications in Genetics

(Instructor: Prof. E. Halperin)

Capstone Project

COM SCI M226
Machine Learning in Bioinformatics

(Instructor: Prof. S. Sankararaman)

BIOENGR C275
Machine Learning and Data-Driven Modeling in Bioengineering

(Instructor: Prof. A. Meyer)

Engineering Professional Development Elective Engineering Professional Development Elective
Engineering Professional Development Elective      
12 Units 8 Units 8 Units 8 Units