Hao-Wei Pang

According to our database, Hao-Wei Pang authored at least 7 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

MolWorld: Molecule World Models for Actionable Molecular Optimization.

Yang Qiao, Bo Pan, Hao-Wei Pang, Peter Zhiping Zhang, Liying Zhang, Liang Zhao

CoRR, May, 2026

Retrieval-Augmented Foundation Models for Matched Molecular Pair Transformations to Recapitulate Medicinal Chemistry Intuition.

Bo Pan, Peter Zhiping Zhang, Hao-Wei Pang, Alex Zhu, Xiang Yu, Liying Zhang, Liang Zhao

CoRR, February, 2026

Chemprop v2: An Efficient, Modular Machine Learning Package for Chemical Property Prediction.

David E. Graff, Nathan Morgan, Jackson W. Burns, Anna C. Doner, Brian Li, Shih-Cheng Li, Joel Manu, Angiras Menon, Hao-Wei Pang, Haoyang Wu, Akshat Shirish Zalte, Jonathan W. Zheng, Connor W. Coley, William H. Green Jr., Kevin P. Greenman

J. Chem. Inf. Model., 2026

2025

PepEVOLVE: Position-Aware Dynamic Peptide Optimization via Group-Relative Advantage.

Trieu Nguyen, Hao-Wei Pang, Shasha Feng

CoRR, November, 2025

PepThink-R1: LLM for Interpretable Cyclic Peptide Optimization with CoT SFT and Reinforcement Learning.

Ruheng Wang, Hang Zhang, Trieu Nguyen, Shasha Feng, Hao-Wei Pang, Xiang Yu, Li Xiao, Peter Zhiping Zhang

CoRR, August, 2025

RIGR: Resonance-Invariant Graph Representation for Molecular Property Prediction.

Akshat Shirish Zalte, Hao-Wei Pang, Anna C. Doner, William H. Green Jr.

J. Chem. Inf. Model., 2025

2022

RMG Database for Chemical Property Prediction.

Matthew S. Johnson, Xiaorui Dong, Alon Grinberg Dana, Yunsie Chung, David Farina, Ryan J. Gillis, Mengjie Liu, Nathan W. Yee, Katrin Blondal, Emily J. Mazeau, Colin A. Grambow, Allen Mark Payne, Kevin A. Spiekermann, Hao-Wei Pang, C. Franklin Goldsmith, Richard H. West, William H. Green Jr.

J. Chem. Inf. Model., 2022