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Computation Efficient Learning Lab.

EECS and AI Department @ DGIST

We design the future learning technology and platform.

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About Us
Primary Research Theme

Efficient AI Technology

We focus on how to redesign AI and learning technologies towards superior computing efficiency for IoT/Big Data/edge computing. We explore alternative computing solutions for future learning technology, including near data computing to push computation beyond traditional processors, and brain-inspired hyperdimensional computing that closely models the ultimate efficient processor - the human brain.

Latest News

Accepted Paper at DAC 2025, ISCA 2025, SIGMETRICS 2025

3 papers accepted : DiTTO, a novel diffusion-based framework for generating realistic, configurable, and diverse multi-device storage traces(DAC 2025); FlexNeRFer, an energy-efficient NeRF accelerator (ISCA 2025); a diffusion-based generative-AI surrogate

Continue ReadingAccepted Paper at DAC 2025, ISCA 2025, SIGMETRICS 2025

Accepted Paper at ICRA 2025, DATE 2025

3 papers accepted: Reserach on a dynamic-encoding, oversampling HD federated learning framework for mobile robots (ICRA 2025); an HD framework designed with fine-grained feature encoding and a robust training scheme

Continue ReadingAccepted Paper at ICRA 2025, DATE 2025

Hojeong Kim, Selim An, Jaewoo Gwak, Sehyeon Park, Minsang Kim joined CELL

Hojeong Kim, Selim An, Jaewoo Gwak, Sehyeon Park , Minsang Kim joined CELL in the first semester of 2025. Welcome!

Address

E3 Building Room 613, 333, Techno jungang-daero, Hyeonpung-myeon Dalseong-gun, Daegu, 42988, REPUBLIC OF KOREA

Email

yeseongkim(AT)dgist.ac.kr

Phone

(+82) 053-785-6332