Sangwoo Mo

About


I'm a 2nd year Ph.D. student at ALIN-LAB at KAIST, advised by Prof. Jinwoo Shin. I received a B.S. in Mathematics and Industrial Engineering (minor) at POSTECH. Before graduate school, I spent my time on various non-research experiences, e.g., start-ups and BCG.

contact: swmo at kaist dot ac dot kr / Google Scholar (40 citations) / Github (900 stars)


My research interest is to understand and design new deep learning algorithms and solve real-world problems.

In particular, I'm interested in

Publications

(C: conference / W: workshop / J: journal / A: arXiv) (* = equal contribution)


[A] Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs (paper, code)

Sangwoo Mo, Minsu Cho, Jinwoo Shin

arXiv 2020 (tech report)


[C4] Lookahead: A Far-sighted Alternative of Magnitude-based Pruning (paper, code)

Sejun Park*, Jaeho Lee*, Sangwoo Mo, Jinwoo Shin

International Conference on Learning Representations (ICLR) 2020


[C3] Mining GOLD Samples for Conditional GANs (paper, slide, poster, code)

Sangwoo Mo, Chiheon Kim, Sungwoong Kim, Minsu Cho, Jinwoo Shin

Advances in Neural Information Processing Systems (NeurIPS) 2019


[C2] Deep Neural Network Approach in Electrical Impedance Tomography-Based Real-Time Soft Tactile Sensor (paper)

Hyunkyu Park, Hyosang Lee, Kyungseo Park, Sangwoo Mo, Jung Kim

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2019


[C1] InstaGAN: Instance-aware Image-to-Image Translation (paper, slide, poster, code)

Sangwoo Mo, Minsu Cho, Jinwoo Shin

International Conference on Learning Representations (ICLR) 2019

Education


  • Ph.D. in Electrical Engineering, KAIST, Daejeon, Korea (advisor: Prof. Jinwoo Shin) (2018.09 - present)
  • M.S. in Electrical Engineering, KAIST, Daejeon, Korea (advisor: Prof. Jinwoo Shin) (2016.09 - 2018.08)
  • B.S. in Mathematics & Industrial Engineering (minor), POSTECH, Pohang, Korea (summa cum laude) (2011.03 - 2016.02)
  • Hansung Science High School, Seoul, Korea (2009.03 - 2011.02)

Work Experience


Research Experience


Non-research Experience

Honors & Awards


Research Honors & Awards


Non-research Honors & Awards

Services

  • Reviewer: ICLR 2020, ICML 2020, NeurIPS 2020