René's URL Explorer Experiment


Title: Gang Liu - PhD Candidate

Mail addresses
gliu7@nd.edu

direct link

Domain: liugangcode.github.io

Links:

Gang Liuhttps://liugangcode.github.io/
Homehttps://liugangcode.github.io/
Publicationshttps://liugangcode.github.io/publications.html
Softwarehttps://liugangcode.github.io/software.html
Abouthttps://liugangcode.github.io/#intro
Newshttps://liugangcode.github.io/#news
Researchhttps://liugangcode.github.io/#publications
Softwarehttps://liugangcode.github.io/#software
Awardshttps://liugangcode.github.io/#awards
Servicehttps://liugangcode.github.io/#service
Experiencehttps://liugangcode.github.io/#experience
GitHubhttps://github.com/liugangcode
Google Scholarhttps://scholar.google.com/citations?user=YOUR_ID&user=zdF3vTYAAAAJ
🤗 Hugging Facehttps://huggingface.co/liuganghuggingface
LinkedInhttps://www.linkedin.com/in/gang-liu-3879a0248/
https://x.com/gliu0329
Prof. Meng Jianghttp://www.meng-jiang.com/
torch-moleculehttps://github.com/liugangcode/torch-molecule
Tinker Research Granthttps://thinkingmachines.ai/blog/tinker-research-and-teaching-grants/
Learning Repetition-Invariant Representations for Polymer Informaticshttps://neurips.cc/virtual/2025/loc/san-diego/poster/115504
Open Polymer Challenge: Leveraging Machine Learning for Polymer Informaticshttps://neurips.cc/virtual/2025/loc/san-diego/competition/127721
Learning Repetition-Invariant Representations for Polymer Informaticshttps://neurips.cc/virtual/2025/poster/115504
[ACS InFocus]https://pubs.acs.org/doi/book/10.1021/acsinfocus.7e9014
[Springer Link]https://link.springer.com/book/10.1007/978-3-031-84732-5
[Challenge Page]https://open-polymer-challenge.github.io/
[Kaggle]https://www.kaggle.com/competitions/neurips-open-polymer-prediction-2025/overview
[GitHub]https://github.com/liugangcode/torch-molecule
MIT Newshttps://news.mit.edu/2025/could-llms-help-design-our-next-medicines-and-materials-0409
Learning Molecular Representation in a Cellhttps://openreview.net/forum?id=BbZy8nI1si
Multimodal Large Language Models for Inverse Molecular Design with Retrosynthetic Planninghttps://openreview.net/forum?id=rQ7fz9NO7f
Learning Attribute as Explicit Relation for Sequential Recommendationhttps://liugangcode.github.io/
Graph Diffusion Transformer (Graph DiT)https://arxiv.org/abs/2401.13858
LLM on Graph Surveyhttps://arxiv.org/abs/2312.02783
Data-Centric Learning from Unlabeled Graphs with Diffusion Modelhttps://arxiv.org/abs/2303.10108
Semi-Supervised Graph Imbalanced Regressionhttps://dl.acm.org/doi/10.1145/3580305.3599497
Network Immunization Strategy by Eliminating Fringe Nodes: A Percolation Perspectivehttps://ieeexplore.ieee.org/abstract/document/9914022
Graph Rationalization with Environment-based Augmentationshttps://arxiv.org/abs/2206.02886
Learning from Counterfactual Links for Link Predictionhttps://arxiv.org/abs/2106.02172
View All Publications →https://liugangcode.github.io/publications.html
[paper]https://arxiv.org/abs/2410.04223
[code]https://github.com/liugangcode/Llamole
[models]https://huggingface.co/collections/liuganghuggingface/llamole-collection-67073a2e76b47d5fea909434
[MIT News]https://news.mit.edu/2025/could-llms-help-design-our-next-medicines-and-materials-0409
[paper]https://arxiv.org/abs/2401.13858
[code]https://github.com/liugangcode/Graph-DiT
[paper]https://arxiv.org/abs/2303.10108
[code]https://github.com/liugangcode/data_centric_transfer
[paper]https://dl.acm.org/doi/10.1145/3580305.3599497
[code]https://github.com/liugangcode/SGIR
[video]https://www.youtube.com/watch?v=vx3Xj24eLvM&t=7s
[Snap Research Blog]https://research.snap.com/news/news-one.html#kdd-sgir-2023
[中文]https://mp.weixin.qq.com/s/LtAWveJYhq27bDojAz6Riw
[paper]https://dl.acm.org/doi/abs/10.1145/3534678.3539347
[code]https://github.com/liugangcode/GREA
[online tool]https://huggingface.co/spaces/liuganghuggingface/Polymer-Property-Prediction-For-Gas-Separation
[paper]https://www.sciencedirect.com/science/article/pii/S2666386424003369
[patent]https://patents.google.com/patent/US20240316492A1/en
SGIR (KDD'23)https://dl.acm.org/doi/10.1145/3580305.3599497
GREA (KDD'22)https://dl.acm.org/doi/10.1145/3534678.3539347
[Notre Dame News]https://mse.nd.edu/news-and-events/news/machine-learning-discovers-hidden-gem-materials-for-heat-free-gas-separation/
[website]https://open-polymer-challenge.github.io/
[Kaggle]https://www.kaggle.com/competitions/neurips-open-polymer-prediction-2025/overview
View All Software/Code →https://liugangcode.github.io/software.html
"Could LLMs help design our next medicines and materials?"https://news.mit.edu/2025/could-llms-help-design-our-next-medicines-and-materials-0409
"Gang Liu receives IBM Fellowship"https://engineering.nd.edu/news/gang-liu-receives-ibm-fellowship/
"Machine learning discovers 'hidden-gem' materials for heat-free gas separation"https://engineering.nd.edu/news/machine-learning-discovers-hidden-gem-materials-for-heat-free-gas-separation/
"Semi-Supervised Graph Imbalanced Regression"https://research.snap.com/news/kdd-sgir-2023.html
Eric Inaehttps://scholar.google.com/citations?user=RKiV3FAAAAAJ&hl=zh-CN&oi=sra
Motif-aware Attribute Masking for Molecular Graph Pre-training (LoG'24)https://arxiv.org/abs/2309.04589
Yihan Zhuhttps://yihan226.github.io/
Learning Repetition-Invariant Representations for Polymer Informatics (NeurIPS'25)https://neurips.cc/virtual/2025/poster/115504
MolTextNet: A Two Million Molecule-Text Datasethttps://arxiv.org/abs/2506.00009
Prof. Meng Jianghttp://www.meng-jiang.com/
Prof. Tengfei Luohttps://engineering.nd.edu/faculty/tengfei-luo/
Prof. Yong Denghttps://scholar.google.com/citations?user=Zuhod6sAAAAJ&hl=zh-CN
Prof. Fuyuan Xiaohttps://scholar.google.com/citations?user=__pybiIAAAAJ&hl=en
Dr. Jie Chenhttps://jiechenjiechen.github.io/
Dr. Anne E. Carpenterhttps://scholar.google.com/citations?user=pj6Bz0gAAAAJ&hl=zh-CN
Dr. Shantanu Singhhttps://scholar.google.com/citations?user=2sEDTFIAAAAJ&hl=zh-CN

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URLs of crawlers that visited me.