Research

Research Highlights

Electrical Engineering won the 29th SAMSUNG Human Tech Paper Award

Our department was selected as ‘the most award-winning department in the university sector’ at the Human Tech Thesis Awards this year as well.
 
The 29th Human Tech Thesis Award is hosted by Samsung Electronics and has been selected since 1994 to discover outstanding human resources in the field of science and technology.
In addition to individual prizes awarded to individual winners, the Human Tech Thesis Awards award special prizes to universities and high schools (levels) that have shown outstanding achievements.
 
Department that is selected as ‘the most award-winning department in the university sector’ receive a prize of 10 million won.
Every year, our department is selected as the most award-winning department, and nine award-winning papers, including the gold award, were selected this year.
 

Details are as below.

 

분과 수상 주저자 공저자1 공저자2 공저자3 지도교수 논문제목
Circuit Design 금상 양제 김재영 임석빈 이석진 김주영 JNPU: A 1.04 TFLOPS Joint-DNN Training Processor with Speculative Quantization and Triple Heterogeneity
Circuit Design 은상 김상진 이지용 엄소연 조우영 유회준 DynaPlasia: An eDRAM In-Memory Computing-based Reconfigurable Spatial Accelerator with Triple-mode Cell
Circuit Design 동상 이민수 채종윤     문건우 A PWM Resonant Converter with Near-Zero-Ripple Input Current and High Efficiency for Fuel Cell Applications
Circuit Design 동상 한동현 류준하 김상엽 김상진 유회준 MetaVRain: A 133mW Real-time Hyper-realistic 3D NeRF Processor with 1D-2D Hybrid Neural Engines for Metaverse on Mobile Devices
Communication & Networks 은상 김재홍 이윤헌 임휘준 정영목 한동수 Co-optimizing for Flow Completion Time in Radio Access Network
Communication & Networks 동상 김재한 유명성     신승원 Heimdallr: Fingerprinting SD-WAN Control-Plane Architecture via Encrypted Control Traffic
Computer Science & Engineering 은상 김태현       박경수 Rearchitecting the TCP Stack for I/O-Offloaded Content Delivery
Physical Devices & Processes 동상 이용복 김태수 이소영   윤준보 Sub-10 fJ/bit Radiation-hard Nanoelectromechanical Non-volatile Memory
Signal Processing 장려상 신욱철 이경현     권인소 Spectral-Invariant Monocular Depth Estimation