Yin Jun Phua

Profile Information

Affiliation: Assistant Professor, School of Computing, Institute of Science Tokyo

Degree: PhD (Informatics)(Mar, 2022, The Graduate University for Advanced Studies)

Researcher number: 20963747
ORCID iD: https://orcid.org/0000-0003-1178-8238
J-GLOBAL ID: 202201016928842589
researchmap Member ID: R000036029

External link: https://yinjunphua.com/

Research Interests

Research Areas

Research History

Oct, 2024 - Present

Assistant Professor, School of Computing, Institute of Science Tokyo
Apr, 2022 - Sep, 2024

Assistant Professor, School of Computing, Tokyo Institute of Technology
Apr, 2021 - Mar, 2022

Research fellowship (DC2), Japan Society for the Promotion of Science
Apr, 2019 - Mar, 2021

Special RA, National Institute of Informatics

Education

Mar, 2019 - Apr, 2022

Department of Informatics, School of Multidisciplinary Sciences, The Graduate University for Advanced Studies
Apr, 2017 - Mar, 2019

Department of Informatics, School of Computing, Tokyo Institute of Technology
Apr, 2013 - Mar, 2017

Department of Computer Science, School of Engineering, Tokyo Institute of Technology

Committee Memberships

2024 - Present

Program Committee, International Conference on Neurosymbolic Learning and Reasoning

Awards

Nov, 2023

Tokyo Institute of Technology Best Teacher Award, Procedural Programming, Tokyo Institute of Technology

Masahito Ohue, Shio Miyafuji, Yin Jun Phua
Oct, 2023

Best Paper Award, Class-Incremental Learning using Diffusion Model for Distillation and Replay, 1st Workshop on Visual Continual Learning, ICCV2023

Quentin Jodele, Xin Liu, Yin Jun Phua, Tsuyoshi Murata
Nov, 2019

Best Student Paper Award, Learning Logic Programs from Noisy State Transition Data, ILP 2019: 29th International Conference on Inductive Logic Programming

Yin Jun Phua, Katsumi Inoue

Papers

Memory augmented using diffusion model for class-incremental learning.

Quentin Jodelet, Xin Liu 0020, Yin Jun Phua, Tsuyoshi Murata

Image Vis. Comput., 161 105600-105600, 2025
Future-proofing class-incremental learning.

Quentin Jodelet, Xin Liu 0020, Yin Jun Phua, Tsuyoshi Murata

Machine Vision and Applications, 36(1) 16-16, Jan, 2025
Variable Assignment Invariant Neural Networks for Learning Logic Programs.

Yin Jun Phua, Katsumi Inoue

NeSy (1), 47-61, 2024
DEGNN: Dual Experts Graph Neural Network Handling both Edge and Node Feature Noise.

Tai Hasegawa, Sukwon Yun, Xin Liu 0020, Yin Jun Phua, Tsuyoshi Murata

PAKDD (2), 376-389, 2024
Class-Incremental Learning using Diffusion Model for Distillation and Replay.

Quentin Jodelet, Xin Liu, Yin Jun Phua, Tsuyoshi Murata

ICCV (Workshops), 3417-3425, 2023
resVAE ensemble: Unsupervised identification of gene sets in multi-modal single-cell sequencing data using deep ensembles.

Foo Wei Ten, Dongsheng Yuan, Nabil Jabareen, Yin Jun Phua, Roland Eils, Sören Lukassen, Christian Conrad

Frontiers in cell and developmental biology, 11 1091047-1091047, 2023
Learning Logic Programs Using Neural Networks by Exploiting Symbolic Invariance.

Yin Jun Phua, Katsumi Inoue

ILP, 203-218, 2021
Learning Logic Programs from Noisy State Transition Data.

Yin Jun Phua, Katsumi Inoue

Inductive Logic Programming - 29th International Conference(ILP), 72-80, 2019
Learning Logic Programs from Noisy State Transition Data.

Yin Jun Phua, Katsumi Inoue

Inductive Logic Programming - 29th International Conference(ILP), JSAI2019 72-80, 2019
Learning Representation of Relational Dynamics with Delays and Refining with Prior Knowledge.

Yin Jun Phua, Tony Ribeiro, Katsumi Inoue

IfCoLog Journal of Logics and their Applications(FLAP), 6(4) 695-708, 2019
Learning Logic Program Representation for Delayed Systems With Limited Training Data.

Yin Jun Phua, Tony Ribeiro, Sophie Tourret, Katsumi Inoue

Late Breaking Papers of the 27th International Conference on Inductive Logic Programming, 27-37, 2017

Misc.

Learning dynamics from limited training data with multilayer perceptron initialized by weight prediction

PHUA Yin Jun, INOUE Katsumi

Proceedings of the Annual Conference of JSAI, JSAI2018 4A101-4A101, 2018
リカレントニューラルネットワークによる遅延を伴う解釈遷移からの論理プログラム表現学習

ポアインジュン, 井上克巳

人工知能学会全国大会論文集, JSAI2017 3O11-3O11, 2017

Presentations

A Foundation Model for Learning Propositional Logic Program

Yin Jun Phua

Ninth International Workshop on Symbolic-Neural Learning, Oct, 2025
Transformers Can Admit Mistakes and Backtrack

Tony Ribeiro, Yin Jun Phua, Tuan Nguyen, Katsumi Inoue

Sep, 2025
Leveraging Symbolic Invariance in Neuro-Symbolic AI

Yin Jun Phua

Aug 27, 2025 Invited
Variable Assignment Invariant Neural Network for Learning Logic Programs

Yin Jun Phua, Katsumi Inoue

Jun, 2024
Learning from Noisy Transition Data

Yin Jun Phua, Katsumi Inoue

Jul, 2019

Teaching Experience

Jun, 2023 - Present

Advanced Procedural Programming

Research Projects

Constraint Reasoning for Trustworthy AI

Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (B), Japan Society for the Promotion of Science, Apr, 2025 - Mar, 2029

Katsumi Inoue, Yuichi Sei, Hidetomo Nabeshima, Phua Yin Jun
背景知識と少量のデータから汎用的で解釈可能な知識をデータ駆動で学習するAIの開発

科学研究費助成事業, 若手研究, 日本学術振興会, Apr, 2025 - Mar, 2028

Phua Yin・Jun
Robust AI by Integration of Knowledge Representation and Machine Learning

Grants-in-Aid for Scientific Research, Grant-in-Aid for Scientific Research (A), Japan Society for the Promotion of Science, Apr, 2021 - Mar, 2025
Discovering New Knowledge by Combining Symbolic Logic and Deep Learning

Grants-in-Aid for Scientific Research Grant-in-Aid for Research Activity Start-up, Grant-in-Aid for Research Activity Start-up, Japan Society for the Promotion of Science, Aug, 2022 - Mar, 2024
Understandable Model by Combination of Symbolic Machine Learning and Deep Statistical Learning

Grants-in-Aid for Scientific Research Grant-in-Aid for JSPS Fellows, Grant-in-Aid for JSPS Fellows, Japan Society for the Promotion of Science, Apr, 2021 - Mar, 2023

Yin Jun Phua

Profile Information

Research Interests

Research Areas

Research History

Education

Committee Memberships

Awards

Papers

Misc.

Presentations

Teaching Experience

Research Projects

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