Qiaolin Lu

MaterialsPilot: An Execution-Feedback Framework for Generative Design of Complex Atomistic Architectures

Qiaolin Lu, Tongliang Liu, Qiang Qu, Bo Han, Yi Chang, Chengqi Zhang

Symmetry-Guaranteed Prediction of High-Order Tensor Properties for Crystalline Materials via Irreducible Decomposition

Qiaolin Lu, Qiang Qu, Hao Jiang, Aoni Xu, Fengwang Li, Bo Han, Tongliang Liu, Yi Chang, Chengqi Zhang

SeqDiCO: Sequence-oriented Diffusion for Scale-Generalizable Neural Combinatorial Optimization

Yu Wang, Qiaolin Lu, Yang Wu, Bohao Qu, Shirui Pan, Yi Chang, Chengqi Zhang

Graph contrastive learning of subcellular-resolution spatial transcriptomics improves cell type annotation and reveals critical molecular pathways

Qiaolin Lu^*, Jiayuan Ding^*, Lingxiao Li, Yi Chang

* Equal contribution.

Graph contrastive learning over subcellular RNA neighborhoods improves cell type annotation and highlights cell type-specific molecular pathways.

@article{lu2025focus,
  title = {{Graph contrastive learning of subcellular-resolution spatial transcriptomics improves cell type annotation and reveals critical molecular pathways}},
  author = {Lu, Qiaolin and Ding, Jiayuan and Li, Lingxiao and Chang, Yi},
  year = {2025},
  journal = {Briefings in Bioinformatics},
  volume = {26},
  number = {1},
  pages = {bbaf020},
  doi = {10.1093/bib/bbaf020}
}

SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology

Jiayuan Ding^*, Lingxiao Li^*, Qiaolin Lu^*, Julian Venegas, Yixin Wang, Lidan Wu, Wei Jin, Hongzhi Wen, Renming Liu, Wenzhuo Tang, Xinnan Dai, Zhaoheng Li, Wangyang Zuo, Yi Chang, Yu Leo Lei, Lulu Shang, Patrick Danaher, Yuying Xie, Jiliang Tang

* Equal contribution.

A human tumor microenvironment benchmark and graph neural network method for spatial cell type deconvolution.

@article{ding2024spatialctd,
  title = {{SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology}},
  author = {Ding, Jiayuan and Li, Lingxiao and Lu, Qiaolin and Venegas, Julian and Wang, Yixin and Wu, Lidan and Jin, Wei and Wen, Hongzhi and Liu, Renming and Tang, Wenzhuo and Dai, Xinnan and Li, Zhaoheng and Zuo, Wangyang and Chang, Yi and Lei, Yu Leo and Shang, Lulu and Danaher, Patrick and Xie, Yuying and Tang, Jiliang},
  year = {2024},
  journal = {Journal of Computational Biology},
  volume = {31},
  number = {9},
  pages = {871--885},
  doi = {10.1089/cmb.2024.0532}
}

DANCE: a deep learning library and benchmark platform for single-cell analysis

Jiayuan Ding, Renming Liu, Hongzhi Wen, Wenzhuo Tang, Zhaoheng Li, Julian Venegas, Runze Su, Dylan Molho, Wei Jin, Yixin Wang, Qiaolin Lu, Lingxiao Li, Wangyang Zuo, Yi Chang, Yuying Xie, Jiliang Tang

An extensible deep learning toolkit and benchmark platform for reproducible single-cell analysis.

@article{ding2024dance,
  title = {{DANCE: a deep learning library and benchmark platform for single-cell analysis}},
  author = {Ding, Jiayuan and Liu, Renming and Wen, Hongzhi and Tang, Wenzhuo and Li, Zhaoheng and Venegas, Julian and Su, Runze and Molho, Dylan and Jin, Wei and Wang, Yixin and Lu, Qiaolin and Li, Lingxiao and Zuo, Wangyang and Chang, Yi and Xie, Yuying and Tang, Jiliang},
  year = {2024},
  journal = {Genome Biology},
  volume = {25},
  pages = {72},
  doi = {10.1186/s13059-024-03211-z}
}

AI4Materials: A Survey of Chemistry-Aware Artificial Intelligence for Materials Science

Qiaolin Lu, Tongliang Liu, Qiang Qu, Hao Jiang, Jun Wang, Jiaqi Yao, Fengwang Li, Aoni Xu, Bo Han, Yi Chang, Chengqi Zhang

Leveraging Hyperbolic and Euclidean Representations in Tandem for Metal-Organic Framework Gas Adsorption Prediction

Hao Jiang, Qiaolin Lu, Qiang Qu, Yexiong Lin, Tongliang Liu

Thinking vs. NoThinking: Towards Interpreting Reasoning Mechanisms of Large Language Models via Sparse Autoencoders

Bo Cheng, Qiaolin Lu, Yi Chang, Yuan Wu

@misc{cheng2026thinking,
  title = {{Thinking vs. NoThinking: Towards Interpreting Reasoning Mechanisms of Large Language Models via Sparse Autoencoders}},
  author = {Cheng, Bo and Lu, Qiaolin and Chang, Yi and Wu, Yuan},
  year = {2026},
  eprint = {2608.08168},
  archivePrefix = {arXiv},
  primaryClass = {cs.CL},
  url = {https://arxiv.org/abs/2608.08168}
}

MEM-GAN: A Pseudo Membrane Generator for Single-cell Imaging in Fluorescent Microscopy

Y Wang, J Ding, L Wu, A Wardhani, P Danaher, Q Lu, H Wen, W Tang, ...