Biography

I am a Postdoc Research Fellow at DeepMed/ZhangLab, supervised by Prof. Zhang Yang. Before that, I was a PhD student at NExT++, where I was supervised by Prof. Chua Tat-Seng and co-supervised by Prof. Kawaguchi Kenji. I am also fortunate to be mentored by Prof. Wang Xiang at the University of Science and Technology of China (USTC). My research primarily focuses on AI for Science, particularly Multi-modal Generative Modeling for emerging scientific modalities such as proteins, RNAs, and small molecules. Additionally, I have a keen interest in Diffusion Models, Natural Language Processing, and Graph Neural Networks.

I am always looking for passionate and motivated graduate and undergraduate students to collaborate with me on AI for Science. Feel free to shoot me an Email if you’re interested in having a chat over coffee at the Coffee Bean & Tea Leaf at the School of Computing of NUS.

News

[New!] 2025/01: One paper is accepted by ICLR 2025! Many thanks to Yanchen and other co-authors!
     NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation.

[New!] 2025/01: I have joined DeepMed/ZhangLab as a Postdoc Research Fellow!

[New!] 2024/10: Three co-authored papers are accepted by iScience, EMNLP and TKDD respectively! Congrats to Yanchen Luo, He Cao and Yongduo Sui!
     Text-guided Diffusion Model for 3D Molecule Generation.
     PRESTO: Progressive Pretraining Enhances Synthetic Chemistry Outcomes.
     A Simple Data Augmentation for Graph Classification: A Perspective of Equivariance and Invariance.

[New!] 2024/08: I am invited to speak as a panelist for the AI for Science BoF sesion at the ACL 2024 conference.

[New!] 2024/01: Three papers are accepted by ACL 2024! Many thanks to Yaorui, Junfeng and other collaborators!
     ReactXT: Understanding Molecular “Reaction-ship” via Reaction-Contextualized Molecule-Text Pretraining.
     ProtT3: Protein-to-Text Generation for Text-based Protein Understanding.
     MolTC: Towards Molecular Relational Modeling In Language Models.

[New!] 2024/01: One paper is accepted by ICLR 2024!
     Towards 3D Molecule-Text Interpretation in Language Models.

[New!] 2023/10: Two papers are accepted by EMNLP 2023, one for the EMNLP main conference and one for the EMNLP Findings!
     MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter.
     ReLM: Leveraging Language Models for Enhanced Chemical Reaction Prediction.

[New!] 2023/09: One paper is accepted by NeurIPS'23!
     Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules.

Selected Publications (Google Scholar)

ICLR'25	NExT-Mol: 3D Diffusion Meets 1D Language Modeling for 3D Molecule Generation. [Paper; Code] Zhiyuan Liu*, Yanchen Luo*, Han Huang, Enzhi Zhang, Sihang Li, Junfeng Fang, Yaorui Shi, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua.
ACL'24	ProtT3: Protein-to-Text Generation for Text-based Protein Understanding. [Paper; Code] Zhiyuan Liu, An Zhang, Hao Fei, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua.
ACL Findings'24	ReactXT: Understanding Molecular “Reaction-ship” via Reaction-Contextualized Molecule-Text Pretraining. [Paper; Code; Demo; Website] Zhiyuan Liu*, Yaorui Shi*, An Zhang, Sihang Li, Enzhi Zhang, Xiang Wang, Kenji Kawaguchi, Tat-Seng Chua.
ICLR'24	Towards 3D Molecule-Text Interpretation in Language Models. [Paper; Code] Sihang Li*, Zhiyuan Liu*, Yanchen Luo, Xiang Wang, Xiangnan He, Kenji Kawaguchi, Tat-Seng Chua, Qi Tian.
EMNLP'23	MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter. [Paper; Code; Website] Zhiyuan Liu, Sihang Li, Yanchen Luo, Hao Fei, Yixin Cao, Kenji Kawaguchi, Xiang Wang, and Tat-Seng Chua.
NeurIPS'23	Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules. [Paper; Code] Zhiyuan Liu, Yaorui Shi, An Zhang, Enzhi Zhang, Kenji Kawaguchi, Xiang Wang, and Tat-Seng Chua
EMNLP'20	Exploring and Evaluating Attributes, Values, and Structures for Entity Alignment. [Paper; Code] Zhiyuan Liu, Yixin Cao, Liangming Pan, Juanzi Li, Zhiyuan Liu, and Tat-Seng Chua.
ACL'19	Multi-Channel Graph Neural Network for Entity Alignment. [Paper; Code] Yixin Cao, Zhiyuan Liu, Chengjiang Li, Zhiyuan Liu, Juanzi Li, and Tat-Seng Chua.
* denotes equal contribution.

Academic Service

I am serving as an Action Editor (Area Chair) for ACL2024 (ARR Feburary 2024), EMNLP 2024 (ARR June 2024), and NAACL2024 (ARR December 2023). I have also served as a Reviewer for ICLR 2025, ICLR2024, NeurIPS 2024, NeurIPS2023, NeurIPS2022, NeurIPS2021, ICML2024, ICML2023, ICML2022, COLM 2024 etc. I am also reviewing top journals like TPAMI and TKDE.

Guest Lecturer

CS6222, Advanced Topics in Computational Biology, Spring 2024 – 2025

Teaching Assistant

IT1244, Artificial Intelligence: Technology and Impact, Spring 2021 – 2022

CS3244, Machine Learning, Fall 2021 – 2022

CS3245, Information Retrieval, Spring 2020 – 2021

Honors and Awards

Dean's Graduate Research Excellence Award, National University of Singapore 2023

Student Research Award, Institue of Data Science at NUS 2023

Research Achievement Award, National University of Singapore 2021

National Group First Prize, the 7th China Undergraduate Physics Tournament 2016

Background

Postdoc Research Fellow, DeepMed/ZhangLab, National University of Singapore, 2025-Present
     Supervisor: Prof. Zhang Yang

PhD in Computer Science, NExT++, National University of Singapore, 2020-2024
     Supervisor: Prof. Chua Tat-Seng; Co-supervisor: Prof. Kawaguchi Kenji; Mentor: Prof. Wang Xiang

Bachelor in Physics, Xi'an Jiaotong University, 2015-2019