About Me

I am a first year Ph.D. student in Computer Science and Engineering at University of California, Santa Cruz. I am a member of Computer Vision Lab advised by professor Roberto Manduchi. I have received my Master’s degree in Computer Science from Kookmin University, Seoul, South Korea. My master’s thesis was about Learning from time Series. I also have a Bachelor’s degree in Computer Science from Kookmin University, Seoul, South Korea. My research interests lie broadly in artificial intelligence, machine learning, deep learning, time series analysis, computer vision, multi-modals, IoT healthcare, assistive technology, and philosophy of science.

Education

Ph.D. in Computer Science and Engineering

University of California, Santa Cruz (2021 - )

Master's in Computer Science

Kookmin University (2019 - 2021)

Bachelor's in Computer Science

Kookmin University (2013 - 2017)

Experiences

Applied Scientist Intern

2022.6 - Present

Amazon, Seattle

Joining Natural Language Processing and Computer Vision team

Software Engineer Intern

2017.9 - 2018.3

KoreoGRFX, TX

Developed and tested a game based on C/C++ with Unity

Publications

  • Learning from Time Series
  • Seongsil Heo, In Kookmin University, Seoul, Korea, August 2021
  • Unsupervised Representation Learning for ECG-based Stress Detection (Best Paper Award)
  • Seongsil Heo, Jaekoo Lee, In IEMEK Symposium on Embedded Technology, May 2021
  • Stress Detection with Single Sensor PPG by Orchestrating Multiple Denoising and Peak Detection Method
  • Seongsil Heo, Sunyoung Kwon, and Jaekoo Lee, In IEEE Access, February 2021
  • PPG signal processing and comparison study with learning-based model for stress detection (Best Paper Award)
  • Seongsil Heo, Inkyung Kim, Sunyoung Kwon, Hyejin Lee and Jaekoo Lee, In Proceedings of Symposium of the Korean Institute of communications and Information Sciences, August 2020
  • A variation on Loss function of Deep Neural Networks for Facial Recognition
  • Seongsil Heo, Daehee Kim, Jaebin Lee and Jaekoo Lee, In Proceedings of Symposium of the Korean Institute of communications and Information Sciences, February 2020
  • Real-time Face De-identification in Visual Media using a Deep Neural Network for Object Detection
  • Seongsil Heo, Daehee Kim, Yonguk Kim and Jaekoo Lee, In Proceedings of Symposium of the Korean Institute of communications and Information Sciences, June 2019