M.S. Concentration in Data and Information Processing Systems
The practice of electrical engineering often involves data acquisition from the physical world, representation to support high-level query, storage in distributed physical media, analytical techniques for de-noising and conditioning data, analytical techniques for discovery of relationship across various data sets, feature extraction, and if appropriate, automatic labeling of data for higher-level learning systems such as artificial intelligence. Engineering principles apply throughout this data lifecycle from acquisition, transformation to feature extraction and semantic analysis for higher-level learning.
- Digital Communications (E&C-ENG 564/645)
- Digital Signal Processing (E&C-ENG 565)
- Math Tools for Data Science (E&C-ENG 579/679)
- Machine Learning for Engineers (E&C-ENG 601)
- Probability (E&C-ENG 603)
- Signal Theory (E&C-ENG 608)
- Image Processing (E&C-ENG 566)
- Applied Machine Learning for the Internet of Things (E&C-ENG 629)
- Algorithms (E&C-ENG 665)
- Data Analytics (E&C-ENG 678)
- Numerical Algorithms and Practices (E&C-ENG 679)
Please direct question to Emily Krems, academic advisor.
Featured faculty
Dennis Goeckel
Design and analysis of secure point-to-point communication links and wireless networks: security and privacy.
Hossein Pishro-Nik
Information Theory, Privacy and Security, Statistical Learning and Decision Making, Wireless Networks, Vehicular Communications and Networking.
Marco Duarte
Signal and image processing, compressive sensing, dimensionality reduction, machine learning, computational imaging, distributed sensing, sensor networks.
Electrical Engineering
Electrical Engineering students at UMass Amherst play a hands-on role in the future of technology in communication, health care, smart cities, and more.
Computer Engineering
Computer engineering students at UMass Amherst are designing and programming everything from complex software systems to autonomous vehicles—and you can, too.