Joonhyung Park

Ph.D student at Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST)

I’m a Ph.D candidate at Machine Learning and Intelligence Lab (MLILAB) in KAIST, advised by Prof. Eunho Yang. Currently, I am working as an intern at Amazon AWS AI with Peng Tang. Please feel free to contact me if you are interested in potential collaborations.

My research interest falls into enhancing the understanding of unstructured/video data modalities through the guidance of large language models. With these goals in mind, my recent focus has been on linking diverse modalities into the core of large language model through the lens of graph-structured knowledge, e.g. object graphs (3D vision), knowledge graphs (natural language), and scene graphs (video). In this endeavor, I work on building algorithms that leverage relational information of data therein, revisiting real-world problems within a graph-based framework to provide a structured understanding of complex data modalities in large language models.

  • Multimodal Large language models: Generation and Comprehension
  • Compositional Generalization (Object-centric Learning)
  • Graph-driven Modal Understanding

Conference Publications

  • R-VLM: Region-Aware Vision Language Model for Precise GUI Grounding
    Joonhyung Park, Peng Tang, Sagnik Das, Srikar appalaraju, Kunwar Yashraj Singh, R. Manmatha, Shabnam Ghadar
    Under Review

  • PruNeRF: Segment-Centric Dataset Pruning via 3D Spatial Consistency
    Yeonsung Jung, Heecheol Yun, Joonhyung Park, Jin-Hwa Kim, Eunho Yang
    ICML 2024

  • PC-Adapter: Topology-Aware Adapter for Efficient Domain Adaption on Point Clouds with Rectified Pseudo Label [paper]
    Joonhyung Park, Hyujin Seo, Eunho Yang
    ICCV 2023

  • SGEM: Test-Time Adaptation for Automatic Speech Recognition via Sequential-Level Generalized Entropy Minimization [paper]
    Changhun Kim, Joonhyung Park, Hajin Shim, Eunho Yang
    INTERSPEECH 2023 (Congrats on my mentee’s paper! :tada:)

  • CALA: Connectivity- and Attribute-Aware Logit Adjustment for Class-Imbalanced Graphs
    Joonhyung Park*, Jaeyun Song*, Eunho Yang (* : equal contribution)
    TPAMI (Under Review)

  • WeavSpeech: Data Augmentation Strategy for Automatic Speech Recognition via Semantic-Aware Weaving [paper]
    Kyusung Seo, Joonhyung Park, Jaeyun Song, Eunho Yang
    ICASSP 2023 (Congrats on my mentee’s paper! :tada:)

  • TAM: Topology-Aware Margin Loss for Class-Imbalanced Node Classification [paper]
    Jaeyun Song*, Joonhyung Park*, Eunho Yang (*: equal contribution)
    ICML 2022

  • GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification [paper]
    Joonhyung Park*, Jaeyun Song*, Eunho Yang (*: equal contribution)
    ICLR 2022

  • Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing [paper]
    Joonhyung Park, June Yong Yang, Jinwoo Shin, Sung Ju Hwang, Eunho Yang
    AAAI 2022 (oral presentation, 380/9020=4.21%)

  • Graph Transplant: Node Saliency-Guided Graph mixup with Local Structure Preservation [paper]
    Joonhyung Park*, Hajin Shim*, Eunho Yang (*: equal contribution)
    AAAI 2022

Work Experiences

  • Applied Scientist II Intern, Amazon AWS AI, Pasadena, CA, Jun. 2024 -
    • Mentors: Peng Tang, Srikar Appalaraju, Yash Singh, and Sagnik Das
  • Research Intern, University of Virginia, Charlottesville, VA, Jun. 2018 - Aug. 2018
    • Advisor: Prof. Homa Alemzadeh
    • Medical concept extraction in text data for Cognitive Assistant System of emergency medical response (supported by the National Institute of Standards and Technology).
  • Research Intern, Collaborative Robots Research Center, DGIST, Daegu, Jun. 2017 - Aug. 2017
    • Development of treadmill for stroke hemiplegic patients

Education

  • Ph.D. (integrated) in Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Mar. 2021 - Present

  • M.S. in Graduate School of AI, Korea Advanced Institute of Science and Technology (KAIST), Mar. 2020 - Mar. 2021

  • B.E. in Computer Science Engineering, Daegu Gyeongbuk Institute of Science & Technology (DGIST), Mar. 2016 - Feb. 2020 - (Summa Cum Laude)

Projects

  • Sub-task generation based point/regional Out-Of-Distribution detection, Samsung Electronics, Sep. 2020 - Sep. 2025
  • Predicting graph properties with few labels using Graph Neural Networks, Samsung Electronics, Sep. 2020 - Sep. 2025
  • Machine learning model for the prediction of Hypoxaemia during Endoscopic Retrograde Cholangiopancreatography, Yonsei Severance Hospital, Mar. 2020 - Jun. 2020

Acamdeic Services

  • Conference Reviewer
    • International Conference on Machine Learning (ICML)
    • Neural Information Processing Systems (NeurIPS)
    • International Conference on Learning Representations (ICLR)
    • Computer Vision and Pattern Recognition (CVPR)
    • AAAI Conference on Artificial Intelligence (AAAI)
    • International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
    • Learning on Graphs (LoG)
  • Journal Reviewer
    • Transactions on Neural Networks and Learning Systems (TNNLS)