Professor
Youngmin Yi joined the School of Electrical and Computer Engineering at the University of Seoul in March 2010 and is now a Professor. He is also with the Department of Artificial Intelligence and the Department of Urban Big Data Convergence.
He received his B.S. and Ph.D. in Computer Engineering from Seoul National University in 2000 and 2007 respectively. Before joining the University of Seoul, he had been a postdoctoral researcher in the Parallel Computing Lab. at the University of California, Berkeley from 2007 to 2009, and worked for the Multi-core Software group at Samsung Advanced Institute of Technology till February 2010.
On his sabbatical leave from 2016 to 2017, he had the privilege to work with Prof. Xipeng Shen at NCSU as a visiting scholar.
His research interests include on-device deep learning, heterogeneous parallel computing, an architecture-algorithm codesign methodology for Deep Learning systems, and various deep learning and ML applications.
Ph.D students / M.S-Ph.D students
M.S. students
Eun-Gyeong Lee
Sungjae Jeon
Ilsung Jin
Undergraduate students
Seokchan Kang: 4th year
Minseok Choi: 4th year
Jiho Shin: 4th year
Mingi Joo: 4th year
Seungho Cho: 3rd year
Daye Kang: 3rd year
Alumni
Eun-Gyeong Lee (M.S., 2024)
Thesis: 3D Parallel Distributed Deep Learning Time Estimation of Transformer Model Considering ZeRO Optimization
Sunyeol Hwang (M.S., 2023) is currently with Korean Air (MLOps)
Thesis: Optimal Heterogeneous Cluster Configurations and Parallel Strategies for Distributed Deep Learning of Transformer Models
Sumin Kim (M.S., 2022) is currently with RTst
Thesis: CNN Accelerator Architecture Search for Exploiting Input Sparsity
Chanyoung Oh (Ph.D., 2021) is currently an Assistant Professor at the Dept. of Software, Kongju National University after ETRI and KT AI2XL.
Thesis: A Software Framework for Efficient Pipeline Computations on Heterogeneous Platforms
Hyeonjin Jung (M.S., 2021) is currently with IntelliSys.
Thesis: GPU-accelerated Gradient Compression Method for Efficient Distributed Deep Learning
Gunjoo Park (M.S., 2021) is currently with ETRI after Hyundai AutoEver.
Thesis: Neural Architecture Search for Optimal Conditional Convolution Neural Networks
Kyungchul Park (M.S., 2019) is currently with Samsung Electronics.
Thesis: Systematically Trainable Conditional CNN for Fast yet Accurate Object Classification on Embedded Platforms
Taekhee Lee (M.S., 2018) is currently with NAVER.
Thesis: Accelerating Deep Learning Inference on CPU-GPU Heterogeneous Embedded Systems
Chang-Que Park (M.S., 2018) is currently with Kakao after Hyundai AutoEver.
Thesis: Spark Framework Supporting Efficient GPU Executions
Illo Yoon (M.S., 2017)
Thesis: Distributed Video Decoding and CPU-GPU Hybrid Scheduling in Hadoop for Video Processing Applications
Seulki Bae (M.S., 2017) is currently with LINE (in Japan).
Thesis: Acceleration of word2vec using GPUs
Saehanseul Yi (M.S., 2015) is currently with Intel after UC Irvine (PhD student).
Thesis: Real-time LBP-based Face Detection Using OpenCL on Embedded GPU
Youngsang Woo (M.S., 2014) is currently with Siemens Healthineers Korea.
Thesis: Fast and Energy-efficient Local Binary Pattern based Face Recognition Using OpenCL on Embedded GPUs
Cheongyong Yi (M.S., 2013) is currently with Melfas.
Thesis: Fast PCA-based Face Recognition on GPUs