Hee Suk Yoon

Ph.D. Candidate @ KAIST EE
Georgia Institute of Technology ECE
(Georgia Tech)

About Me

I graduated from the Georgia Institute of Technology with a B.S. in Computer Engineering in 2021. After completing my undergraduate studies, I decided to continue my education and pursue a Ph.D. in the field of Artificial Intelligence/Deep Learning at the Korea Advanced Institute of Science and Technology (KAIST). I am currently working under the guidance of Professor Chang D. Yoo, whose expertise and leadership have been invaluable to my research.

My research focuses on the reliability of Artificial Intelligence/Deep Learning technologies for various modalities, including images, videos, and natural language. I am passionate about exploring the potential of these technologies and finding ways to improve their performance and reliability in real-world applications.

In my free time, I enjoy staying up-to-date with the latest developments in the field of AI/DL, as well as reading and learning about other areas of computer science and engineering. I am excited to continue my studies at KAIST and to see where my research takes me in the future!


    • Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
      Ph.D. candidate (integrated) in Electrical Engineering (Artificial Intelligence/Deep Learning)
      Aug. 2021 - Present
      Advisor: Chang D. Yoo

    • Georgia Institute of Technology, Atlanta, GA, United States
      B.S. in Computer Engineering
      graduated May 2021
      Cumulative GPA: 3.92/4.0 (highest honors)


* denotes equal contribution
denotes selected publications
[C]: Conference Paper [W]: Workshop Paper

Academic Activities

Invited Talk

    • CAU-AI Core Technology Seminar (Navigating Uncertainty Challenges in Classification and Language Generation): 2024.03.22

Journal Reviewing

    • Transactions on Machine Learning Research (TMLR)

Conference Reviewing

    • European Conference on Computer Vision (ECCV): 2024

    • Conference on Computer Vision and Pattern Recognition (CVPR): 2024

    • Association for Computational Linguistics Rolling Review (ARR): 2024

    • Association for Computational Linguistics (ACL): 2023

    • International Conference on Acoustics, Speech & Signal Processing (ICASSP): 2023, 2024

    • Empirical Methods on Natural Language Processing (EMNLP): 2022, 2023

    • International Conference on Learning Representations Tiny Papers Track (ICLR TinyPapers): 2024

Teaching Assistance

    • Statistical Learning Theory 2024 Spring

    • Introduction to Machine Learning 2023 Fall

    • Introduction to Reinforcement Learning 2023 Spring

    • Signals and Systems 2022 Spring, 2022 Fall

    • Hwaseong City-KAIST Semiconductor Specialized Curriculum - Large Language Models 2023

    • Seongnam-KAIST Next Generation ICT Research Center EE Co-op+ Joint Research Program 2023 Fall

    • Seongnam-KAIST Next Generation ICT Research Center Machine Learning and Big Data Course: 2021, 2022, 2023

Funded Projects

    • Development of Uncertainty-Aware Agents Learning by Asking Questions
      2022-03-01 ~ 2027-03-01
      Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (Role: Operator)

    • Multi-modal Generative AI for Summarization
      2023-09-01 ~ 2024-09-01
      Samsung Speech Recognition & Natural Language Processing Lab (Role: Supporter)

    • Visual Dialogue System: Developing Visual and Language Capabilities for AI-Based Dialogue Systems
      Korea Telecom (KT) AI2XL Laboratory (Role: Operator)

    • Enhancing CD SEM Image Quality and Inter-Facility Image Transfer Technology using Deep Learning
      2021-06-01 ~ 2023-06-01
      Samsung Metrology & Inspection (Role: Operator)

    • Prediction of Relative Object Sizes in Images using Deep Learning
      2021-06-01 ~ 2021-12-31
      U-AIM (Role: Operator)