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Member Profile (24)
(Prof) S. M. Lee
(Ph.D) J. S. Kwon
(Ph.D) M. J. Kang
(Ph.D) S. H. Hong
(Ph.D) S. H. Cho
(Ph.D) J. H. An
(Ph.D) S. H. Lee
(Ph.D) H. J. Yun
(Ph.D) Y. H. Lee
(Ph.D) S. H. Park
(M.S.) J. Y. Jeong
(M.S.) M. J. Kim
(M.S.) B. I. Jeong
(M.S.) J. Y. Byeon
(M.S.) J. K. Phi
(M.S.) G. H. Jeon
(M.S.) H. J. Lee
(M.S.) J. H. Park
(M.S.) K. H. Seong
(B.S.) J. H. Kim
(B.S.) J. H. Lee
(B.S.) H. S. Kim
(B.S.) J. Y. Lee
Collaborators
(Prof) S. H. Lee
(Dr. ) D. K. Lee
(Mr. ) D. K. Jung
Contact
KNU-Location
Since 2014

Our Team

Dongkyu Lee (Ph.D. and Korea Electronics Technology Institute (KETI))

Brief Bio Sketch

Mr. Lee received the B.S degree (Summa Cum Laude) in Electronics Engineering at Kyungpook National University, Daegu, Korea in 2018. His research interests include high performance acceleration on big data processing. His research was focused on designing energy-efficient cloud-connected processors in VLSI chip level. He is pursuing toward obtaining his Ph.D degree in KNU. Mr. Lee published several journal/conference papers in Cloud-connected IoT software hardware architecture. He is an lecturer of C-Programming Language in KNU. [Homepage] [Google Scholar] [About]

Selected Publications

  • Dongkyu Lee, Hyeongyun Moon, Sejong Oh and Daejin Park. mIoT: Metamorphic IoT Platform for On-Demand Hardware Replacement in Large-Scale IoT Applications (SCI) Sensors , 2020.

  • Sanghoon Lee, Dongkyu Lee, Pyung Choi, and Daejin Park. Accuracy-Power Controllable LiDAR Sensor System with 3D Object Recognition for Autonomous Vehicle (SCI) Sensors 20(19):5706-5725, 2020.

  • Dongkyu Lee, Seungmin Lee, Sejong Oh, and Daejin Park. Energy-Efficient FPGA Accelerator with Fidelity-Controllable Sliding-Region Signal Processing Unit for Abnormal ECG Diagnosis on IoT Edge Devices (SCI) IEEE Access, 2021.

  • Taewon Chong, Dongkyu Lee, and Daejin Park. Semantic Depth Data Transmission Reduction Techniques based on Interpolated 3D Plane Reconstruction for Lightweighted LiDAR Signal Processing Platform (SCI) Electronics, 11(14):2135-2152, 2022.

  • Dongkyu Lee and Daejin Park. On-Cloud Linking Approach Using a Linkable Glue Layer for Metamorphic Edge Devices (SCI) Electronics, 2023.

  • Dongkyu Lee and Daejin Park. On-Cloud Code Streaming-based Firmware Partial Update for Embedded Edge Devices (SCI) (Under Review) IEEE Access, 2024.

Jisu Kwon (Ph.D. Student @ KNU)

Brief Bio Sketch

Mr. Kwon received his B.S. degree in Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea in 2019. He is currently a integrated Ph.D. student in School of Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests include the behavior changeable neuromorphic deep learning processor based on partial software partial replacement and hardware reconfiguration architecture, especially designing ultra-low-power AI accelerator for resource-limited embedded systems. Currently, he is focusing on energy-efficient/fast/low-memory-cost binary firmware (FW) replacement via FW segmentation. He is the first student enrolled with B.S./M.S./Ph.D.-integrated course in KNU. [Homepage] [Google Scholar] [About]

Selected Publications

  • Jisu Kwon, Moon Gi Seok, and Daejin Park. User Insensible Sliding Firmware Update Technique for Flash-Area/Time-Cost Reduction toward Low-Power Embedded Software Replacement In 2020 IEEE COOLChips, 2020.

  • Jisu Kwon, Moon Gi Seok, and Daejin Park. Low-Power Fast Partial Firmware Update Technique of On-Chip Flash Memory for Reliable Embedded IoT Microcontroller (SCI) IEICE Transactions on Electronics, 2021.

  • Jisu Kwon, Sejong Oh, and Daejin Park. Metamorphic Edge Processors Using Flexible Runtime Partial Replacement of Software-Embedded Verilog RTL Models In IEEE ISCAS 2021, 2021.

  • Jisu Kwon and Daejin Park. Efficient Sensor Processing Technique using Kalman Filter-based Velocity Prediction in Large-Scale Vehicle IoT Application (SCI) IEEE Access, 2022.

  • Jisu Kwon, Heuijee Yun, and Daejin Park. Dynamic MAC Unit Pruning Techniques in Runtime RTL Simulation for Area-Accuracy Efficient Implementation of Neural Network Accelerator In IEEE MWSCAS 2023, 2023.

  • Jisu Kwon and Daejin Park. Efficient Partial Weight Update Techniques for Lightweight On-Device Learning on Tiny Flash-Embedded MCUs In ACM International Conference on Embedded Software (EMSOFT 2023), 2023.

  • Jisu Kwon and Daejin Park. Micro-Accelerator-in-the-Loop Framework for MCU Integrated Accelerator Peripheral Fast Prototyping In ACM International Conference on Embedded Software (EMSOFT 2023), 2023.

  • Jisu Kwon and Daejin Park. Efficient Partial Weight Update Techniques for Lightweight On-Device Learning on Tiny Flash-Embedded MCUs (SCI) IEEE Embedded Systems Letters, 15(4):206-209, 2023.

  • Seungmin Lee, Jisu Kwon, and Daejin Park. Runtime Tracking-based Replication of On-Chip Embedded Software using Transfer Function Learning for Dust Particle Sensor Systems (SCI) IEEE Access, 2023.

  • Jisu Kwon and Daejin Park. Sliding-Window-based Fast and Lightweight ADC Pseudo-Randomness Compensation Technique for Low-Cost ADC (SCI) (Under Review) IEICE Electronics Express, 2024.

Myeongjin Kang (Ph.D. Student @ KNU)

Brief Bio Sketch

Mr. Kang received his B.S. degree in Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea in 2020. He is currently pursuing toward a Ph.D. in School of Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests include Embedded low-power action with Hue based algorithm and Parallelized ECC Block. Currently, he is focusing on low-power robust processor architecture with ECC protection unit. In the future, he will focus on various way for processor's low power, stable action. [Homepage] [Google Scholar] [About]

Selected Publications

  • Myeongjin Kang and Daejin Park. Lightweight Microcontroller with Parallelized ECC-based Code Memory Protection Unit for Robust Instruction Execution in Smart Sensors (SCI) Sensors, 2021.

  • Juneseo Chang, Myeongjin Kang, and Daejin Park. Accelerated SVM Algorithm for Sensors Fusion-Based Activity Classification in Lightweighted Edge Devices In IEEE 40th International Conference on Consumer Electronics, 2022.

  • Juneseo Chang, Myeongjin Kang, and Daejin Park. Low-Power On-Chip Implementation of Enhanced SVM Algorithm for Sensors Fusion-based Activity Classification in Lightweighted Edge Devices (SCI) Electronics, 11(1):139-159, 2022.

  • Myeongjin Kang, Ho Kim, Jungwon Park, Seongbum Yang, Junseo Yun, and Daejin Park. Low-Power Streamable AI Software Runtime Execution based on Collaborative Edge-Cloud Image Processing in Metaverse Applications (KCI) Journal of the Korea Institute of Information and Communication Engineering, 26(11):1577-1585, 2022.

  • Myeongjin Kang, Nayoung Kwon, Seungmin Lee, and Daejin Park. Fast Bit Inversion Vulnerability Pre-estimation using Tcl and UPF in RTL Simulation Runtime In IEEE International Conference on ICT Convergence (ICTC 2023), 2023.

  • Myeongjin Kang and Daejin Park. Cloud Memory Enabled Code Generation via Online Computing for Seamless Edge AI Operation In IEEE COMPSAC 2024, 2024.

  • Myeongjin Kang and Daejin Park. Virtual Memory Enabled Code Generation via Online Computing for Seamless Edge AI Operation (SCI) (Under Review) IEEE Access, 2024.

Seongho Cho (Ph.D. Student @ KNU, Senior Researcher @ LG Display)

Brief Bio Sketch

Mr. Cho is now with LG Display as senior researcher, developing display and touch device controller including F/W for automotive. He is pursuing toward his Ph.D. degree in school of Electronics Engineering at Kyungpook National university, Daegu, Korea. He has worked on circuit design and performance verification for capacitive type in-cell touch from 2012 to 2018. His research interests include the robust circuit design and highly reliable and low power self diagnostic architecture for automotive display device for ASIL. [About] [Google Scholar]

Selected Publications

  • Seongho Cho, Sejong Oh, and Daejin Park. Robust Intra-Body Communication using SHA-ECC-CRC Inversion-based Frequency Shift Keying for Securing Electronic Authentication (SCI) Sensors, 2020.

  • Seongho Cho and Daejin Park. Electrostatic Coupling Intra-Body Communication Based on FSK Communication and Error Correction (KCI) IEMEK Journal of Embedded Systems and Applications, 15(4):159-166, 2020.

  • Sungho Cho and Daejin Park. Automatic Importance Sampling Points Extraction for Anti-Aliasing Event Signal Processing (Under Review) In IEEE ICTC 2024, 2024.

Seungmin Lee (KNU-EE Funded Professor @ KNU)

Brief Bio Sketch

Dr. Lee received B.S. and M.S. degrees in Mathematics from Kyungpook National University (KNU), in Daegu, Korea in 2010 and 2012, respectively. He expanded his research topics to the bio-inspired signal processing algorithm and electronics systems. He received his Ph.D. degree in Electronics Engineering at KNU in 2018. His research interest includes signal processing, image processing, bio-inspired signal processing, and compact system implementation. He is now with KNU as Post-doctoral researcher, supported by NRF grants. [Homepage] [Google Scholar] [About]

Selected Publications

  • S. Lee, D. Park, and K. H. Park. QRS Complex Detection Based on Primitive (SCI) Journal of Communications and Networks, 19(5):442-450, 2017.

  • Seungmin Lee, Yoosoo Jeong, Daejin Park, Byoung-Ju Yun, and Kil Houm Park. Efficient Fiducial Point Detection of ECG QRS Complex Based on Polygonal Approximation (SCI) Sensors, 18(12):4502-4517, 2018.

  • Yoosoo Jeong, Seungmin Lee, Daejin Park, and Kil Houm Park. Accurate Age Estimation Using Multi-Task Siamese Network-Based Deep Metric Learning for Frontal Face Images (SCI) Symmetry, 10(9):1-15, 2018.

  • S. Lee, Y. Jeong, J. Kwak, D. Park, and K. H. Park. Advanced Real-Time Dynamic Programming in the Polygonal Approximation of ECG Signals for a Lightweight Embedded Device (SCI) IEEE Access, 7:162850-162861, 2019.

  • S. Lee, D. Park. Real-Time Abnormal Beat Detection Method using Template Cluster for ECG Diagnosis on IoT Devices (SCI) Human-centric Computing and Information Sciences, 2021.

  • Seungmin Lee, Daejin Park. Efficient Template Cluster Generation for Real-Time Abnormal Beat Detection in Lightweight Embedded ECG Acquisition Devices (SCI) IEEE Access, 2021.

  • Seungmin Lee and Daejin Park. Adaptive ECG Signal Compression Method Based on Look-ahead Linear Approximation for Ultra Long-Term Operating of Healthcare IoT Devices (SCI) Human-centric Computing and Information Sciences (HCIS), 2021.

  • Dongkyu Lee, Seungmin Lee, Sejong Oh, and Daejin Park. Energy-Efficient FPGA Accelerator with Fidelity-Controllable Sliding-Region Signal Processing Unit for Abnormal ECG Diagnosis on IoT Edge Devices (SCI) IEEE Access, 2021

  • Seungmin Lee and Daejin Park. Intelligent Template Construction for Compressed ECG Signal Processing in Lightweighted Embedded IoT Medical Applications (SCI) Sensors, 2021.

  • Seungmin Lee and Daejin Park. Abnormal Beat Detection from Unreconstructed Compressed Signals Based on Linear Approximation in ECG Signals Suitable for Embedded IoT Devices (SCI) Journal of Ambient Intelligence and Humanized Computing, 2022

  • Seungmin Lee and Daejin Park. Comparative Neural Network based on Template Cluster for Automated Abnormal Beat Detection in Electrocardiogram Signals (SCI) Human-centric Computing and Information Sciences (HCIS), 12(51):1-17, 2022.

  • Seungmin Lee, Jisu Kwon, and Daejin Park. Runtime Tracking-based Replication of On-Chip Embedded Software using Transfer Function Learning for Dust Particle Sensor Systems (SCI) IEEE Access, 2023.

  • Seungmin Lee, Jisu Kwon, and Daejin Park. Optimized Replication of ADC-based Particle Counting Algorithm with Reconfigurable Multi-Variables in Pseudo-Supervised Digital Twining of Reference Dust Sensor Systems (SCI) Sensors, 2023.

  • Seungmin Lee and Daejin Park. LSTM-based Post-processing for Noise Reduction in SVD-based Particulate Matter Digital Twinning on Lightweight Embedded Devices (SCI) Electronics Letters, 60(4), 2024.

Sanghoon Lee (Research Professor @ KNU)

Brief Bio Sketch

Mr. Lee received the B.S degree in Electronics Engineering at Dong-A University, Busan, Korea in 2009 and M.S degree in Electronics Engineering at Kyungpook National University, Daegu, Korea in 2011. His research interests include analog ICs, ASIC design and analysis. His current fields of interest is development and implementation of LiDAR sensor. Mr. Lee was a research engineer at GITC (Gyeongbuk of IT Convergence Industry Technology) from 2015 to 2018, and have worked on signal processing and circuit design for various sensors included LiDAR sensor. Since 2018, he is now a senior researcher in CARNAVICOM Co., Ltd., and working on circuit design of LiDAR sensor. [Homepage] [Google Scholar]

Selected Publications

  • Sanghoon Lee, Dongkyu Lee, Pyung Choi, and Daejin Park. Accuracy-Power Controllable LiDAR Sensor System with 3D Object Recognition for Autonomous Vehicle (SCI) Sensors, 2020.

  • Sanghoon Lee and Daejin Park. Robust Embedded PID Control Software Execution based on Automatic Malfunction Profile Feedback (SCI) Electronics, 13(8):1526-1547, 2024.

  • Sanghoon Lee and Daejin Park. Runtime Embedded Software Malfunction Detection based on Profile Generation of Current-level Pattern Matcher (Under Review) In IEEE APCCAS 2024, 2024.

Jaeyong Jung (M.S @ KNU, Researcher @ LG Innotek)

Brief Bio Sketch

Mr. Jung is now with LG Innotek as product engineer, developing camera actuator tester process. He received his B.S. degree in Electronics Engineering in 2019 and completed his master's degree in 2021 at Kyungpook National University, Daegu, Republic of Korea. His research interests are high-speed, intelligent, optimized disturbance-robust automatic control systems. [Homepage] [Google Scholar]

Selected Publications

  • J. Jung, J. Cho, and D. Park. Energy-Efficient Signal Processors with Silent Mirror Tracer for Long-Term Activity Monitoring In 2019 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, 2019.

  • Jaeyong Jung and Daejin Park. Intelligent Microcontroller using Runtime Coefficient Update Techniques for Disturbance Robust Output Control In IEEE ICEIC 2023, 2023.

Dongkyu Jung (M.S. and Samsung Electronics)

Brief Bio Sketch

Mr. Jung is currently pursuing toward his M.S. degree in School of Electronics Engineering from Kyungpook National University, Daegu, Republic of Korea. His research interests include the pre-processor and neural network module for adaptive AI based on ARM architecture, especially designing high-speed low- power AI sight fusion algorithm for resource-limited embedded systems. Currently, he is focusing on on-chip GPU high-efficiency control and data processing using ARM SIMD (Single Instruction Multiple Data). [Homepage] [Google Scholar]

Selected Publications

  • Dongkyu Jung and Daejin Park. Accelerated On-Chip Algorithm based on Semantic Region-based Partial Difference Detection for LiDAR-Vision Depth Data Transmission Reduction in Lightweight Controller Systems of Autonomous Vehicle In 2021 IEEE 14th International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC), 2021.

  • Dongkyu Jung and Daejin Park. RTOS-based Task-Driven Scheduling for Vehicle Independent BLDC Motor Control In IEEE 49th Annual Conference of the IEEE Industrial Electronics Society (IECON 2023), 2023.

  • Dongkyu Jung and Daejin Park. Efficient Object Detection Using Semantic ROI Generation with Light-weighted LiDAR Clustering in Embedded Processors (SCI) Sensors, 2023.

  • Dongkyu Jung and Daejin Park. Optimizing Data Access for Accelerators Lightweight convolutional neural network algorithm structure (SCI) (Under Review) IEEE Access, 2024.

Heuijee Yun (Ph.D. Student @ KNU)

Brief Bio Sketch

Ms. Yun is currently pursuing toward her Ph.D. degree in electronic engineering at Kyungpook National University Daegu, Republic of Korea. Her research interests include simulating and executing autonomous driving. Her research was focused on designing simulation that is sophisticated and applicable to real-world simulation. Currently, she is focusing on integrating camera and LiDAR data to train with deep neural networks with that data to achieve more accurate object recognition by using LS1028ardb. [Homepage] [Google Scholar]

Selected Publications

  • Heuijee Yun and Daejin Park. Virtualization of Self-Driving Algorithms by Interoperating Embedded Controllers on Game Engine for Digital Twining Autonomous Vehicle (SCI) Electronics, 2021.

  • Heuijee Yun and Daejin Park. Efficient Object Detection based on Masking Semantic Segmentation Region for Lightweight Embedded Processors (SCI) Sensors, 22(22):8890-8911, 2022.

  • Jisu Kwon, Heuijee Yun, and Daejin Park. Dynamic MAC Unit Pruning Techniques in Runtime RTL Simulation for Area-Accuracy Efficient Implementation of Neural Network Accelerator In IEEE MWSCAS 2023, 2023.

  • Heuijee Yun and Daejin Park. Low-Power Lane Detection Unit with Sliding-based Parallel Segment Detection Accelerator for Lightweighted Automotive Microcontrollers (SCI) IEEE Access, 2024.

  • Heuijee Yun and Daejin Park. Deep Learning based Human Detection using Thermal-RGB Data Fusion for Safe Automotive Guided-Driving In IEEE International Conference on Pervasive Computing and Communication (Percom 2024 - Pervehicle), 2024.

  • Heuijee Youn and Daejin Park. (Under Blind Review) In IEEE International Conference on Embedded Software (EMSOFT 2024), 2024.

  • Heuijee Youn and Daejin Park. High-Speed Energy-Efficient Dynamic Pruning using Pattern-based Alignment for Convolutional Spiking Neural Network Hardware Accelerators (SCI) (On Writing) IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2024.

Joonghyun An (Ph.D. Student, Researcher @ Samsung Electronics)

Brief Bio Sketch

Mr. An received the M.S. degree in School of Electronics Engineering from Kyungpook National University, Daegu, Korea, in 2017. His research interests include ultra-low power VLSI chip design for IoT-driven applications. He was an Senior Researcher in SK Hynix Semiconductor, developing ARM-based System-on-Chip with Custom-Designed VLSI Circuit. He is now pursuing toward his Ph.D. degree in Kyungpook National University. He is now with Samsung Electronics as Principle Engineer. He published several journal/conference papers related robust processor architecture protecting abnormal clock failure. [Homepage] [Google Scholar]

Selected Publications

  • Joonghyun An, Moon Gi Seok, and Daejin Park. Automatic On-Chip Backup Clock Changer for Protecting Abnormal MCU Operations in Unsafe Clock Frequency IEICE Electronics Express, 13(24):20160808-20160808, 2016.

  • Joonghyun An and Daejin Park. Runtime Compensation Coefficient Estimation Techniques using Binary Search Algorithm for Low-Power Active Noise Cancelling Systems In IEEE ICCE-Asia 2021, 2021.

  • Joonghyun An and Daejin Park. Fast Adaptation Techniques of Compensation Coefficient of Active Noise Canceller using Binary Search Algorithm (KCI) Journal of the Korea Institute of Information and Communication Engineering, 25(11):1635-1641, 2021.

  • Junghyun An and Daejin Park. Reconfigurable Built-In Test Unit by Embedding Runtime Capture-Replay Test Vector into On-Chip SRAM (Under Review) In IEEE ICICDT 2024, 2024.

Sunghoon Hong (Ph.D. Student, SYSCON Robotics)

Brief Bio Sketch

Mr. Hong received the M.S. degree in Intelligent Robot Engineering at Hanyang University, Seoul, Korea, in 2016. His main interest is Human-Like Autonomous Driving Systems. He has a lot of experience in autonomous driving technologies such as SLAM (Simultaneous Localization And Mapping), ADAS (Advanced Driver Assistance Systems), PID (Proportional-Integral-Differential) control, machine learning, path-planning and navigation algorithms and has published several journal/conference papers. Currently, He was a research engineer at Carnavicom.Co., Ltd. from 2021 and Department of Electronics, Kyungpook National University, Daegu, Korea from 2021. He is pursuing toward his Ph.D. degree by researching technologies to optimize deep learning-based object detection algorithms for human-like artificial intelligence autonomous driving systems to be applied to low-power embedded systems. [Homepage] [Google Scholar]

Selected Publications

  • Sunghoon Hong and Daejin Park. Runtime ML-DL Hybrid Inference Platform based on Multiplexing Adaptive Space-Time Resolution for Lightweight Object Detection in Low-Power Embedded Systems (SCI) Sensors, 22(8):2998-3011, 2022.

  • Sunghoon Hong and Daejin Park. On-Chip Realization of Efficient Lane Departure Warning Systems using Inverse Perspective Transformation and Machine Learning-based Lane Prediction (SCI) IEEE Transactions on Intelligent Transportation Systems, 2023.

  • Sunghoon Hong and Daejin Park. (Under Blind Review) In IEEE International Conference on Embedded Software (EMSOFT 2024), 2024.

Taewon Chong (Ph.D. Student, Research Collaborator @ Carnavicom)

Brief Bio Sketch

Mr. Chong received the B.S degree in Electronics Engineering at Korea Polytechnic University, Korea in 2016 and M.S degree in Electronics & Computer Engineering, Chonnam University at Korea in 2018. He is now pursuing toward his Ph.D. degree, collaborating as a research engineer at Carnvicom.CO., Ltd. from 2015 and Department of Physics, Hanyang University from 2018. He has worked on LiDAR sensor signal processing, developed 3D viewer and developed domain control unit(DCU) for sensors. [Homepage] [Google Scholar]

Selected Publications

  • Taewon Chong, Dongkyu Lee, and Daejin Park. Semantic Depth Data Transmission Reduction Techniques based on Interpolated 3D Plane Reconstruction for Lightweighted LiDAR Signal Processing Platform (SCI) Electronics, 11(14):2135-2152, 2022.

  • Dongkyu Jung and Taewon Chong and Daejin Park. Efficient Object Detection Using Semantic ROI Generation with Light-weighted LiDAR Clustering in Embedded Processors (SCI) Sensors, 2023.

Yonghun Lee (Ph.D. Student)

Brief Bio Sketch

Mr. Lee received the B.S degree in Electronics Engineering at Jeonbuk National University, Jeonju, Korea in 2004. Mr. Lee was a research engineer at Samsung Electronics over 16 years from 2004 to 2020. And have worked on high speed intra-panel interface and touch sensor controller. He is currently an Ph.D. student in School of Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests include one-dimensional hardware acceleration for embedded systems. [Homepage] [Google Scholar]

Selected Publications

  • Jin-Ho Kim, Woon-Taek Oh, Tae-Jin Kim, Jae-Yong Ihm, Younghwan Chang, Youngmin Choi, Donguk Park, Naxin Kim, Yonghun Lee. LCD-TV System with 2.8Gbps/Lane Intra-Panel Interface for 3D TV Applications in SID 2012.

  • Dong Hoon Baek, Jung Pil Lim, Han Su Pae, Jae Youl Lee, Wang Yu, Young Min Choi, and Yong Hun Lee. The Enhanced Reduced Voltage Differential Signaling eRVDS Interface with Clock Embedded Scheme for ChipOnGlass TFTLCD Applications in SID 2010.

  • Yoon-Kyung Choi, Zhong-Yuan Wu, KyungMyun Kim, and YongHun Lee. A Compact Low-Power CDAC Architecture for Mobile TFT-LCD Driver ICs in ISCC 2008.

  • Yoon-Kyung Choi, Hyung Rae Kim, Wongab Jung, MinSoo Cho, Zhong-Yuan Wu, HyoSun Kim, and YongHun Lee. A 16.7M Color VGA Display Driver IC with Partial Graphic RAM and 500Mb/s/ch Serial Interface for Mobile a-Si TFT-LCDs in ISCC 2007.

  • Yonghun Lee and Daejin Park. Fast Verilog Simulation using Tcl-based Verification Code Generation for Dynamically Reloading from Pre-Simulation Snapshot In IEEE ICAIIC 2023, 2023.

  • Yonghun Lee and Daejin Park. Fast Verilog Simulation using Tcl-based Verification Code Generation for Dynamically Reloading from Pre-Simulation Snapshot (KCI) Journal of the Korea Institute of Information and Communication Engineering, 27(4):545-551, 2023.

  • Yonghun Lee and Daejin Park. In-System Test Unit Verilog RTL Generation using Capture-Replay Scheme in Dynamic Simulation (Under Review) In IEEE APCCAS 2024, 2024.

Seunghyun Park (Ph.D. Student @ KNU)

Brief Bio Sketch

Mr. Park is currently pursuing toward Ph.D degree in Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests include CNN (Convolutional Neural Network) accelerating processor implementation. He conducts research about low-power, small-size, high-speed hardware design with Verilog RTL synthesis. He also conducts research about parallel processors. With these processors, He analyzes various SW image process like low pass filter in assembly level. These processors can accelerate AI systems. [Homepage] [Google Scholar]

Selected Publications

  • Seunghyun Park and Daejin Park. Low-Power FPGA Realization of Lightweight Active Noise Cancellation with CNN Noise Classification (SCI) Electronics, 12(11):2511-2526, 2023.

  • Seunghyun Park and Daejin Park. Integrated 3D Active Noise Cancellation Simulation and Synthesis Platform Using Tcl In IEEE International Conference on Embedded Multicore Many-core Systems-on-Chip (MCSoC 2023), 2023.

  • Seunghyun Park and Daejin Park. Power-Efficient CNN Accelerator Design with Bit-Separable Radix-4 Booth Multiplier In IEEE COOLChips 2024, 2024.

  • Seunghyun Park and Daejin Park. (Under Blind Review) In IEEE International Conference on Embedded Software (EMSOFT 2024), 2024.

  • Seunghyun Park and Daejin Park. Modular Tile Chip Serial Peripheral Interface for Power Efficient Off-Chip Network (SCI) (On Writing) IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2024.

Suhwan Lee (Ph.D. Student @ KNU, Senior Researcher @ LG Electronics)

Brief Bio Sketch

Mr. Lee is now with LG Electronics as senior research engineer, developing Embedded network SW include Wi-Fi module installed in Smart home Appliances(IOT). He received the B.S degree in Computer Engineering at Korea Maritime University, Pusan, Korea in 2011 and M.S degree in Computer Engineering at Pusan National University, Pusan, Korea in 2013. He is now pursuing toward his Ph.D degree in Kyungpook National University. His research interests IoT Networking solutions and security design for weak Electric Fields. [Homepage] [Google Scholar] [SVN]

Selected Publications

  • Suhwan Lee and Daejin Park. Network-based Structured Aware Collaborative IoT Devices Control using Adaptive Sensing for Edge-Cloud Traffic Reduction (Under Review) In IEEE ICCE-Asia 2024, 2024.

Byungin Jung (M.S. Student, Senior Researcher @ Hanwha Systems)

Brief Bio Sketch

Mr. Jung is now with is now with Hanwha Systems R&D department as system engineer, researching naval combat management system(CMS) architecture, sensors&weapons system integration and verification. He received his B.S. degree in Electronics Engineering in 2013 at Kumoh Institute of Technology (KIT), Republic of Korea. Currently his research interests are Artificial Intelligence appliance/future Cyber security solution integrated with CMS structure for naval battleship.. [Homepage] [Scholar] [SVN]

Selected Publications

Jongyun Byeon (M.S. Student, Senior Researcher @ LIG Nex1)

Brief Bio Sketch

Mr. Byeon is now with LIG Nex1 as junior research engineer, solving issues during production and operation of guided missile. He received the B.S. degree in Electronics Engineering at Pusan National University, Pusan, Korea. He is now pursuing toward his M.S degree in Kyungpook National University. His research interests cover embedded systems and hardware logic design. [Homepage] [Scholar] [SVN]

Selected Publications

Minjung Kim (M.S. Student @ KNU)

Brief Bio Sketch

Mr. Kim is about to graduate from electronic engineering in Kyungpook National University. He is currently B.S student at ai-soc laboratory. His research interests include overcoming the limits of Embedded System. His recent study is about deadline scheduling algorithm and memory saving technique using struct bit field. Also, he conducts research about implementing hypervisor in MCU, by jumping to function pointer. His future work will be about safety techniques of ARM processors such as Failsafe and Trustzone. And also memory saving techniques using Scratchpad is also his interests. His final goal is to implement safe hypervisor in Embedded MCU. [Homepage] [Google Scholar] [SVN]

Selected Publications

  • Minjung Kim and Daejin Park. Efficient Execution of On-Chip Embedded Software Using Pre-Emulation on Shallow OS In 14th International Conference on Mobile Computing and Ubiquitous Networking (ICMU 2023), 2023.

  • Minjung Kim and Daejin Park. Implementation of Dynamic Round Robin Scheduling on Bare-Metal Shallow Multi-OS for Lightweighted Microcontrollers In IEEE COMPSAC 2024, 2024.

  • Minjung Kim and Daejin Park. Implementation of Hypervisor through Interrupt-based Context Switching and Memory Division Between OS in Embedded Systems (KCI) (Under Review) Journal of the Korea Institute of Information and Communication Engineering, 2024.

Gihyeon Jeon (M.S. Candidate Undergraduate Student @ KNU)

Brief Bio Sketch

Mr. Jeon is currently doing his undergraduate degree in Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests span from low-level hardware design to the domain of making hardware function. He has designed fast ternary ripple carry adder by constructing ternary logic gates and is currently conducting research on the efficient utilization of on-chip memory, specifically scratchpad memory. [Homepage] [Google Scholar] [SVN]

Selected Publications

  • Kihyun Jeon and Daejin Park. Speed-Area-Power Efficient Ternary Logic Gate Implementation based on Typical MOS transistors In International Conference on Electronics, Information, and Communication (ICEIC 2024), 2024.

  • Kihyun Jeon and Daejin Park. Defragmentation-based Efficient Allocation on On-Chip Scratch-Pad Memory for Lightweighted Microcontrollers In IEEE COOLChips 2024, 2024.

  • Gihyeon Jeon and Daejin Park. Defragmentation-based Efficient Allocation on On-Chip Scratchpad Memory for Lightweighted Microcontrollers (KCI) (Under Review) Journal of the Korea Institute of Information and Communication Engineering, 2024.

Hyunjung Lee (M.S. Candidate Undergraduate Student @ KNU)

Brief Bio Sketch

Mr. Lee is currently doing his undergraduate degree in Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests cover automotive embedded systems, specially in designing multi-camera interoperable emulation framework using embedded edge-cloud AI computing for autonomous vehicle driving. He is pursuing his research to implement the entire full stacks from low-level embedded firmware to autonomous driving algorithm, including the hardware systems, by interoperating human-interative interfaces. [Homepage] [Google Scholar] [SVN]

Selected Publications

  • Hyunjung Lee and Daejin Park. Multi-Camera Interoperable Emulation Framework using Embedded Edge-Cloud AI Computing for Autonomous Vehicle Driving In IEEE Vehicular Networking Conference (VNC), 2024.

Jaehoon Kim (Undergraduate Student @ KNU)

Brief Bio Sketch

Mr. Kim is currently doing his undergraduate degree in Electronics Engineering at Kyungpook National University, Daegu, Republic of Korea. His research interests covers the mission-critical automotive/industrial embedded systems and software for highly robust control systems, specially in AI-Stacked object detection systems. [Homepage] [Google Scholar] [SVN] [CV]

Selected Publications

  • Jaehoon Kim and Daejin Park. YOLOv8 Automatic Weapon Control with Edge-Cloud Integrated Look-Ahead Movement Estimator In IEEE ISOCC 2024.