Yonsoo Kim

 |  Education  |  Work Experience  |  Publications  |  Patent  |  Honors  |  Projects  | 

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I am an undergraduate student at Ewha Womans University, where I double-major in Computer Science & Engineering and Business Administration. I work with Prof.Joonseok Lee at the Visual Information Processing lab on video understanding.

Currently, I'm interested in deep learning, especially representation learning in computer vision, and real-world applications (e.g. unmanned vehicle, autonomous driving).

Feel free to check out my CV and drop me an e-mail if you want to chat with me!

 ~  Email  |  CV  |  Github  |  LinkedIn  |   ~ 

Ewha Womans University
Magna Cum Laude
Mar '17 — Feb '23

B.S in Computer Science and Engineering
B.A in Business Administraction

Major GPA (CS): 4.04/4.3, Cumulative GPA: 3.96/4.3
Certificated Big Data and Artificial Intelligence track, Opensource SW developer track

Research Intern | Seoul National University
July '21 — Present

Working under the supervision of Prof.Joonseok Lee at the Visual Information Processing Lab. We are researching the generic video summarization in a supervised manner.

Research Student | Electronics and Telecommunications Research Institute
Jan '21 — Feb '21

I worked at Defense & Safety ICT Research Department of Intelligent Convergence Research Laboratory. We built a deep learning model that predicts crime types through police reports.

Research Intern | Ewha Womans University
June '20 — Aug '20

Working under the supervision of Prof.Hyunseok Park at the Bioinformatics Laboratory. Finding insights from bioinformatics journals by using NLP methods.

(*) indicates equal contribution.

STAR-SUM: Structure-aware Video Summarization
Jinhwan Sul*, Yonsoo Kim*, Donghwa Kim, Joonseok Lee
Submitted to CVPR, 2023

An Empirical Study on the Korean Text Classification based on Active Learning with KorBERT
Wonjoo Park, Yonsoo Kim, Myungsun Baek, Yongtae Lee.
The 2nd Korea Artificial Intelligence Conference, 2021

Organizing an in-class hackathon to correct PDF-to-text conversion errors of Genomics & Informatics 1.0
Sunho Kim, Hyunseok Park, [and 43 others, including Yonsoo Kim]
Genomics & Informatics, 2020

Active Learning Apparatus, Apparatus and Method for Sampling Data used for Active Learning
Yonsoo Kim, Wonjoo Park, Yongtae Lee
Apr, 2021. Patent pending

  • Dean’s List, Ewha Womans University, 2018 — 2021
  • 2nd Place in SW Startup Competition, Ewha Womans University, 2021
  • 4th Place in Best Poster Awards of Graduation projects, Ewha Womans University, 2021
  • 3rd Place in Finance Data Contest, Financial Security Institute, 2021, (among 400+ teams)
  • Finalist in Animal Datathon Korea, Animal Tech Korea, 2021
  • LEAP Student Club Grants, Ewha Womans University, 2021
  • UROP Fellowship, Ewha Womans University, 2021
  • Academic Scholarship, Ewha Womans University, 2021
  • SW Leadership Scholarship, Ewha Womans University, 2021
  • Fostering Futures Scholarship, Ewha Womans University, 2021
  • Honorable Mention in Industrial Control System Threat Detection AI Competition, National Intelligence Service(NIS), 2020, (top 10 among 260+ teams)

STAR-SUM: Structure-aware Video Summarization

CVPR 2023 (Under submission)
Dates of Participation: Mar '22 — Present

In this paper, we proposed a structure-aware transformer, which hierarchically processes each semantic level composed by machine-generated semantic units. We also reset evaluation settings for fair comparison and suggested experiments related to video summarization subjectivity, and its positive results confirmed the model possessing generalizability.

Token Sampling for ViT

Dates of Participation: Sep '21 — Mar '22

We proposed a token sampling module for vision transformers to focus on core tokens rather than giving all tokens the same weight. We built a trainable kernel function that computes probabilities of tokens in the image. By doing this, the model could select the most important tokens of regions. This module can be attached to any vision transformer models, such as Vanilla ViT, Swin Transformers, TimeSFormer, MViT and etc.

Data Analysis Tool using Machine-Generated Visualization

Dates of Participation: Mar '21 — Dec '21

In this work, we developed a data analysis tool that recommends data plots generated by a deep learning model(Data2Vis), thereby providing data analysis reports in dashboard form. The project recognized as a high-quality UI/UX for broad accessibility from a user survey and resulted in 2nd place in the SW Startup Competition and 4th place in the Best Poster Awards of Graduation projects.

One Line A Day

Dates of Participation: July '21 — Dec '21

We created a mobile application with a function that summarizes in one line through a text summarization model after a user writes a diary. My role was a machine learning engineer and backend developer. I implemented abstractive summarization API using Pororo, a Korean text summarization model.
Active Learning on Crime Classification

The 2nd Korea Artificial Intelligence Conference, 2021
Dates of Participation: Jan '21 — Feb '21

In this work, we conducted a crime classification project based on crime reporting messages using KorBERT. I suggested a new active learning algorithm where the model is proportionally fed to learn high confidence data as well as low ones. The performance was improved macro F1 11.6% higher and weighted F1 4.9% higher for the same training time. We published a paper in Korea AI conference, got a patent pending, and further exhibited by KOREA AI EXPO 2021.

Sign Language Education Web Application

Dates of Participation: Sep '19 — Aug '20

We developed a sign language “education” web that could lower the entry barrier of sign-language for the public. My team designed it to recognize the user’s hand gestures using a real-time object detection model through a webcam, which would make the user practice each alphabet of sign-language ten times. For this, we trained a YOLO model from scratch, using our labeled data from over 20,000 images.

This template is a modification to Rishab Khincha's website.