Precision Machining with Micro-Scale Vertical Machining Center. - Daniel J. Cox; Glynn Newby; Hyung Wook Park; Steven Y. Liang; Wang-Lin Liu; Shang-Bin Hsieh; Joon Hwang (J. Adv. Comput. Intell. Intell. Informatics, 2006)

Anticancer drug delivery for tumor targeting and therapy. - Yu Jin Kim; Il-Kyu Park; Jin Soo Kim; Joon Hwang; Eui-Sik Chung; Kang Moo Huh; Yong-kyu Lee (NEMS, 2009)

Cutting Force Adapted Control Application in Micropositioned Machining. - Joon Hwang; Eui-Sik Chung (Int. J. Autom. Technol., 2009)

Optimal design and manufacturing of infrared surveillance camera mirror. - Joon Hwang; Kun-Hee Kim; Jong-Ho Won; Eui-Sik Chung (NEMS, 2010)

Sensitivity improvement in FSI CIS using the M1ToP™ smart process technique. - Manlyun Ha; Sun Choi; DongHun Cho; Hosoo Kim; Jungyeon Cho; Youngsun Oh; Jongman Kim; Sangwon Yoon; Changhoon Choi; Juneseok Lee; Juil Lee; Joon Hwang (ISOCC, 2012)

Pixel design and photodiode process technology for image sensor applications. - Minkyu Kang; Hoon Jang; Sunjae Hwang; Soeun Park; Sanghwa Kim; Hosoon Ko; Changhun Han; Joon Hwang (ISOCC, 2012)

Spiking Neural Networks With Time-to-First-Spike Coding Using TFT-Type Synaptic Device Model. - Seongbin Oh; Soochang Lee; Sung Yun Woo; Dongseok Kwon; Jiseong Im; Joon Hwang; Jong-Ho Bae; Byung-Gook Park; Jong-Ho Lee 002 (IEEE Access, 2021)

Direct Gradient Calculation: Simple and Variation-Tolerant On-Chip Training Method for Neural Networks. - Hyungyo Kim; Joon Hwang; Dongseok Kwon; Jangsaeng Kim; Min-Kyu Park; Jiseong Im; Byung-Gook Park; Jong-Ho Lee 002 (Adv. Intell. Syst., 2021)

Novel Weight Update Scheme for Hardware Neural Network based on Synaptic Devices Having Abrupt LTP or LTD Characteristics. - Junmo Lee; Joon Hwang; Youngwoon Cho; Sangbum Kim; Jongho Lee (CoRR, 2021)

On-Chip Trainable Spiking Neural Networks Using Time-To-First-Spike Encoding. - Jiseong Im; Jaehyeon Kim; Honam Yoo; Jong-Won Baek; Dongseok Kwon; Seongbin Oh; Jangsaeng Kim; Joon Hwang; Byung-Gook Park; Jong-Ho Lee 002 (IEEE Access, 2022)

Analog Synaptic Devices Based on IGZO Thin-Film Transistors with a Metal-Ferroelectric-Metal-Insulator-Semiconductor Structure for High-Performance Neuromorphic Systems. - Dongseok Kwon; Eun Chan Park; Wonjun Shin; Ryun-Han Koo; Joon Hwang; Jong-Ho Bae; Daewoong Kwon; Jong-Ho Lee 002 (Adv. Intell. Syst., 2023)

Si-Based Dual-Gate Field-Effect Transistor Array for Low-Power On-Chip Trainable Hardware Neural Networks. - Kyu-Ho Lee; Dongseok Kwon; In-Seok Lee; Joon Hwang; Jiseong Im; Jong-Ho Bae; Woo Young Choi; Sung Yun Woo; Jong-Ho Lee 002 (Adv. Intell. Syst., 2024)

SNNSim: Investigation and Optimization of Large-Scale Analog Spiking Neural Networks Based on Flash Memory Devices. - JongHyun Ko; Dongseok Kwon; Joon Hwang; Kyu-Ho Lee; Seongbin Oh; Jeonghyun Kim; Jiseong Im; Ryun-Han Koo; Jae-Joon Kim; Jong-Ho Lee 002 (Adv. Intell. Syst., 2024)

NeuroTorch: DRAM-free nonvolatile memory-based hybrid training compute-in-memory system simulator. - JongHyun Ko; Inseok Lee; Kyu-Ho Lee; Joon Hwang; Min-Kyu Park; Jiseong Im; Jeonghyun Kim; Ryun-Han Koo; Sung-Ho Park; Jae-Joon Kim; Jong-Ho Lee (Neurocomputing, 2025)

Efficient Hybrid Training Method for Neuromorphic Hardware Using Analog Nonvolatile Memory. - Dongseok Kwon; Sung Yun Woo; Joon Hwang; Hyeongsu Kim; Jong-Ho Bae; Wonjun Shin; Byung-Gook Park; Jong-Ho Lee 002 (IEEE Trans. Neural Networks Learn. Syst., 2025)