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LPSoC Lab.

Representative Projects

FiCABU: A Fisher‑Based, Context‑Adaptive Machine Unlearning Processor for Edge AI

LoRA-Edge: Tensor-Train–Assisted LoRA for Practical CNN Fine-Tuning on Edge Devices

TT-Edge: A Hardware–Software Co-Design for Energy-Efficient Tensor-Train Decomposition on Edge AI

STARC: Crafting Low-Power Mixed-Signal Neuromorphic Processors by Bridging SNN Frameworks and Analog Designs

E-BTS: A Low-Power Event-Driven Blink Tracking System with Hardware-Software Co-Optimized Design for Real-Time Driver Drowsiness Detection  

ASAP-FE: Energy-Efficient Feature Extraction Enabling Multi-Channel Keyword Spotting on Edge Processors

HH-PIM: Dynamic Optimization of Power and Performance with Heterogeneous-Hybrid PIM for Edge AI Devices

Radar-PIM: Developing IoT Processors Utilizing Processing-in-Memory Architecture for Ultra-Wideband Radar-based Respiration Detection 

Day-Night Architecture: Development of an Ultra-Low Power RISC-V Processor for Wearable Anomaly Detection

Florian: Developing a Low-power RISC-V Multicore Processor with   a Shared Lightweight FPU   

Temporary Caching for RISC-V Multicore Platforms

RISC-V eXpress (RVX)

TEI-inspired ULP SoC Platform

AI-TEI Controller

TEI-aware Dynamic Power Mangement

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