Research Interests

I am interested in AI4Science especially generative models for drug-like molecules and proteins.
Also interested in representation learning for graph-structured data and unsupervised learning.

Publications

• Equivariant Blurring Diffusion for Hierarchical Molecular Conformer Generation
  Jiwoong Park and Yang Shen
  Conference on Neural Information Processing Systems (NeurIPS), 2024
  Also accepted at NeurIPS 2024 Machine Learning in Structural Biology workshop

• Latent 3D Graph Diffusion
  Yuning You, Ruida Zhou, Jiwoong Park, Haotian Xu, Chao Tian, Zhangyang Wang and Yang Shen
  International Conference on Learning Representations (ICLR), 2024

• Confidence-Based Feature Imputation for Graphs with Partially Known Features
  Daeho Um, Jiwoong Park, Seulki Park and Jin Young Choi
  International Conference on Learning Representations (ICLR), 2023

• Meta-node: A Concise Approach to Effectively Learn Complex Relationsips in Heterogeneous Graphs
  Jiwoong Park, Jisu Jeong, Kyungmin Kim and Jin Young Choi
  Arxiv 2022

• Unsupervised Hyperbolic Representation Learning via Message Passing Auto-Encoders
  Jiwoong Park (*), Junho Cho (*), Hyung Jin Chang and Jin Young Choi (* equally contributed)
  IEEE/CVF Computer Vision and Pattern Recognition (CVPR), 2021

• Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning
  Jiwoong Park, Minsik Lee, Hyung Jin Chang, Kyuewang Lee and Jin Young Choi
  IEEE/CVF International Conference on Computer Vision (ICCV), 2019

• Learning Doubly Stochastic Affinity Matrix via Davis-Kahan Theorem
  Jiwoong Park and Taejeong Kim
  IEEE International Conference on Data Mining (ICDM), 2017 (Oral)

Educations

• Postdoc in Department of Electrical and Computer Engineering, Texas A&M University (Oct.2022 ~ Present)
  Advisor: Yang Shen

• PhD in Department of Electrical and Computer Engineering, Seoul National University (Mar.2018 ~ Aug.2022)
  Dissertation: “Unsupervised Representation Learning for Homogeneous, Heterogeneous, and Tree-like Graphs”
  Advisor: Jin Young Choi

• MSc in Department of Electrical and Computer Engineering, Seoul National University (Mar.2016 ~ Feb.2018)
  Thesis: “Learning Doubly Stochastic Affinity Matrix through Two Different Ways”
  Advisor: Taejeong Kim

• BSc in Department of Electrical and Electronics Engineering, Chung-Ang University (Mar.2010 ~ Feb.2016)

Work Experiences

• Research Intern (Aug.2021 ~ Feb.2022)
  Naver Corp.

• Research Intern (Jun.2020 ~ Aug.2020)
  Mitsubishi Electric Research Laboratories (MERL)

Awards and Honors

• Distinguished Dissertation Awards for Master (2018)
  Dept. of ECE, SNU

• Google Conference and Travel Scholarships (2017)
  Google Inc.

• ICDM 2017 Students Travel Awards (2017)
  ICDM 2017