UC’s MS in EECS fuses hardware innovation with algorithmic prowess, preparing students for semiconductor, AI, and embedded-systems leadership.
RISC-V processor extension accelerating homomorphic-encryption workloads
Neuromorphic memristor array mimicking hippocampal sequence learning
Millimeter-wave phased-array transceiver for 6G mobile communications
SLAM algorithm optimized for swarms of micro-drones in GPS-denied indoor spaces
On-device federated-learning accelerator for health-monitoring wearables
Spin-orbit torque MRAM cell design reducing write energy by 50 %
Edge-AI video analytics system for smart intersection traffic safety
Chiplet-based heterogeneous integration methodology for AI/5G SoCs
Time-synchronized mesh network improving industrial IoT reliability
Quantum-dot infrared imager readout circuit for autonomous night vision
Li-ion battery state-of-health estimator using Kalman-filter neural hybrids
Secure boot architecture resisting side-channel attacks on embedded medical devices
Robotic arm with tactile-sensor skin learning manipulation via deep reinforcement learning
Photonic neural network accelerator leveraging silicon microring resonators
Open-source EDA toolchain plugin for power-intent verification
Energy harvesting rectenna powering remote environmental sensors
Policy brief on semiconductor supply-chain resilience for national security
Workshop series teaching PCB design to underrepresented engineering students
Conference on ethical AI hardware co-design for sustainability
Public demo kit showing magnetic-levitation control with PID tuning
Invent the hardware-software future with UC’s trailblazing MS.
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