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)

    • Fingers crossed to our Neurips 2023 paper!

    • Mitigating the Exposure Bias in Sentence-Level Grapheme-to-Phoneme (G2P) Transduction
      Eunseop Yoon*, Hee Suk Yoon*, Dhananjaya Gowda, SooHwan Eom, Daehyeok Kim, John Harvill, Heting Gao, Mark Hasegawa-Johnson, Chanwoo Kim, Chang D. Yoo
      INTERSPEECH 2023

    • One-Shot Exemplification Modeling via Latent Sense Representations
      John Harvill, Hee Suk Yoon, Eunseop Yoon, Mark Hasegawa-Johnson and Chang D. Yoo
      ACL 2023 Workshop on Representation Learning for NLP (RepL4NLP 2023)

    • INTapt: Information-Theoretic Adversarial Prompt Tuning for Enhanced Non-Native Speech Recognition
      Eunseop Yoon*, Hee Suk Yoon*, John Harvill, Mark Hasegawa-Johnson, Chang D. Yoo
      ACL 2023 (findings)

    • Counterfactual Two-stage Debiasing for Video Corpus Moment Retrieval
      Sunjae Yoon, Ji Woo Hong, SooHwan Eom, Hee Suk Yoon, Eunseop Yoon, Daehyeok Kim, Junyeong Kim, Chanwoo Kim, Chang D. Yoo
      ICASSP 2023

    • ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure
      Hee Suk Yoon*, Joshua Tian Jin Tee*, Eunseop Yoon, Sunjae Yoon, Gwangsu Kim, Yingzhen Li, Chang D. Yoo
      ICLR 2023
      [openreview] [arxiv]

    • SMSMix: Sense Maintained Sentence Mixup for Word Sense Disambiguation
      Hee Suk Yoon*, Eunseop Yoon*, John Harvill, Sunjae Yoon, Mark Hasegawa-Johnson, Chang D Yoo
      EMNLP 2022 (findings)
      [arxiv] [pdf]

    • Information-Theoretic Text Hallucination Reduction for Video-grounded Dialogue
      Sunjae Yoon, Eunseop Yoon, Hee Suk Yoon, Junyeong Kim, Chang D Yoo
      EMNLP 2022
      [arxiv] [pdf]

    • Selective Query-Guided Debiasing for Video Corpus Moment Retrieval
      Sunjae Yoon, Ji Woo Hong, Eunseop Yoon, Dahyun Kim, Junyeong Kim, Hee Suk Yoon, Chang D Yoo
      ECCV 2022
      [arxiv] [pdf]

Academic Activities

Reviwer Experience

    • Transactions on Machine Learning Research (TMLR): 2023

    • Association for Computational Linguistics (ACL): 2023

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

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

Teaching Assistance

    • Introduction to Machine Learning 2023 Fall

    • Introduction to Reinforcement Learning: 2023 Spring

    • Signals and Systems: 2022 Spring, 2022 Fall

    • 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


    • 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)

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

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

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