Jaehyeong Jo

Jaehyeong Jo

PhD student at KAIST AI

About me

Hi, I am Jaehyeong Jo.
Here is my CV (Curriculum Vitae) and Google Scholar.

Email: harryjo97 [at] kaist.ac.kr

Last updated: Sep 27, 2024

Introduction

I am a PhD student in Graduate school of AI at KAIST (MLAI lab), under the supervision of Prof. Sung Ju Hwang. Previously, I was a Research Intern at Meta Reality Labs.

My research interest lies in understanding the physical world through the lens of geometry. Previous works focus on diffusion models incorporating geometry for the generation of geometrical structures, including graphs and data on Riemannian manifolds, and their applications to real-world tasks, e.g., drug discovery, protein design, and neural architecture search. I am also interested in modeling discrete data (e.g., language) and temporal data (e.g., video, time series) with diffusion models.

Conference Publications

  • Conditional Synthesis of 3D Molecules with Time Correction Sampler

    ​Hojung Jung*, Youngrok Park*, Laura Schmid, Jaehyeong Jo, Dongkyu Lee, Bongsang Kim, Se-Young Yun, Jinwoo Shin
    NeurIPS 2024

  • Identity Decoupling for Multi-Subject Personalization of Text-to-Image Models

    [project page] [paper] [code]
    ​Sangwon Jang*, Jaehyeong Jo*, Kimin Lee^, Sung Ju Hwang^
    NeurIPS 2024

  • Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes

    [paper] [code]
    ​Jaehyeong Jo, Sung Ju Hwang
    ICML 2024

  • Graph Generation with Diffusion Mixture

    [paper] [code]
    ​Jaehyeong Jo*, Dongki Kim*, Sung Ju Hwang
    ICML 2024

  • DiffusionNAG: Task-guided Neural Architecture Generation with Diffusion Models

    [paper] [code]
    Sohyun An*, Hayeon Lee*, Jaehyeong Jo, Seanie Lee, Sung Ju Hwang
    ICLR 2024

  • Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models

    [project page] [paper]
    Jaewoong Lee*, Sangwon Jang*, Jaehyeong Jo, Jaehong Yoon, Yunji Kim, Jin-Hwa Kim, Jung-Woo Ha, Sung Ju Hwang
    ICCV 2023

  • Exploring Chemical Space with Score-based Out-of-distribution Generation

    [paper] [code]
    Seul Lee, Jaehyeong Jo, Sung Ju Hwang
    ICML 2023

  • Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations

    [paper] [code] [talk]
    ​Jaehyeong Jo*, Seul Lee*, Sung Ju Hwang
    ICML 2022

  • Edge Representation Learning with Hypergraphs

    [paper] [code]
    ​Jaehyeong Jo*, Jinheon Baek*, Seul Lee*, Dongki Kim, Minki Kang, Sung Ju Hwang
    NeurIPS 2021

*: Equal contribution, ^: Equal advising

Workshop Publications

  • Antibody-SGM: Antigen-Specific Joint Design of Antibody Sequence and Structure Using Diffusion Models

    [paper]
    Xuezhi Xie, Jin Sub Lee, Dongki Kim, ​Jaehyeong Jo, Jisun Kim, Philip M. Kim
    ICML 2023 Workshop on Computational Biology