M.S. Concentration in Internet-of-Things
IoT broadly refers to networked embedded computers & sensors that are loosely or tightly connected to remote computing resources, and can take on many form factors that range from remotely-deployed sensors to wearable health monitors.
The design of IoT systems necessitates energy-efficient hardware and software design at its core. However, these systems are becoming increasingly dependent on emerging 5G radio technologies, AI hardware accelerators, & access to edge cloud computing resources.
Students completing the concentration will take five approved courses as part of satisfying the requirements of our existing master's program in ECE.
- Embedded Systems: Design, Modeling, and Verification (E&C-ENG 622)
- Design Principles for Low Power Embedded Computing Systems (E&C-ENG 623)
- Networked Embedded Syst. Design (E&C-ENG 635)
- AI-based Wireless Network Design (E&C-ENG 627)
- Data-Driven Decarbonization of Electricity Networks (E&C-ENG 628)
- Applied Machine Learning (E&C-ENG 629)
- Computer Networks (E&C-ENG 671)
- Green Computing (E&C-ENG 674)
- Mobile and Ubiquitous Computing (COMPSCI 528)
- Advanced Wireless Networking and Sensing in IoT (COMPSCI 654)
Featured faculty
Jeremy Gummeson
Designs small form factor embedded computer systems that gracefully scale performance with available harvested energy
Fatima Anwar
Emerging Embedded Technologies; Cyber-physical Systems Security; Distributed Learning for the Edge; Time-Aware System Design; Human-centered Computing.
Beatriz Lorenzo
B5G/6G networks, wireless networks, mobile computing, network economics, AI, quantum networks
David Irwin
Adjunct, Computer Science
Leads the Sustainable Computing Lab, which focuses on designing distributed software systems with an emphasis on improving efficiency and sustainability.
Application information & deadlines
Please direct questions to Emily Krems, academic advisor.
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