CMU’s ECE MS lets you customize a technical pathway across embedded systems, signals & ML, nanoelectronics, and energy systems. Tap into ChipLab to tape-out custom RISC-V silicon, collaborate with the Power Systems Lab on AI-driven microgrids, or publish in ISSCC on quantum-dot transistors. A professional track adds management electives, while the research track positions you for PhD or advanced R&D roles.
Edge-AI accelerator ASIC reducing inference latency for AR glasses
Wide-bandgap GaN inverter for bidirectional EV fast charging
Low-power LoRa mesh network enabling wildfire early detection
FPGA prototype of neuromorphic vision processor for drones
AI-enhanced mm-wave beam-forming algorithm for 6G backhaul
Printed graphene antenna array for flexible IoT devices
Robust hardware security enclave resistant to fault injection
Quantum-dot cellular automata simulation toolkit for nano-logic
Phasor-measurement-unit data analytics detecting grid oscillations
Bio-impedance spectrometer ASIC for wearable health monitoring
Blockchain-anchored firmware update protocol for smart meters
EMI-aware PCB layout recommender using reinforcement learning
Runtime reconfigurable RF front-end for cognitive radio
On-chip optical interconnect prototype evaluating energy per bit
Policy brief on spectrum-sharing standards for uncrewed aerial systems
Design next-gen electronics and systems at CMU’s ECE powerhouse.
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