Our research has a general focus on developing new approaches for performing energy-efficient computing, which is highly interdisciplinary, incorporating material science, physics, electrical engineering, and computer science, and encompasses both theoretical and experimental work.
We are involved in developing functional materials, exploring novel electronic devices and high-performance circuit architectures for both general-purpose and application-specific tasks, and creating relevant algorithms and software tools.
"Highly durable and energy-efficient probabilistic bits with h-BN/SnS2 interface for integer factorization", InfoMat, 2025
"SnS2 memtransistor-based Lorenz chaotic system for true random number generation", Nano Energy, 2024
"Energy-efficient and reconfigurable complementary filter based on analog–digital hybrid computing with SnS2 memtransistor", Nano Energy, 2023
"Analog–digital hybrid computing with SnS2 memtransistor for low-powered sensor fusion", Nature Communications, 2022
We are actively seeking self-motivated, resourceful, and dedicated students who are interested in the emerging computing systems.
Currently, we have 1~2 openings for graduate courses.
We are also looking for postdoctoral researchers.
Interested candidates may contact Prof. Sungho Kim