Cheng Wan

Hi there! I’m an ECE Ph.D. Student at Cornell University, and I’m honored to be advised by Mert Sabuncu and Qingyu Zhao, previously working on Computer Vision at CMU CS, also on AI for Healthcare at Georgia Tech and Emory.

Research Interests: AI for Medicine, 3D Vision Learning, and Multimodal Learning.

My research is now mainly focused on AI for Medicine especially in 3D vision learning and understanding. I’m passionate about developing intelligent systems that can make a meaningful impact in healthcare.

Publications

arXiv

Breaking the Pairing Shortcut in Medical Visual In-Context Learning

Cheng Wan, Chenjun Li, and Qingyu Zhao

arXiv preprint, 2026

Bib HTML

@article{wan2026pairing,
  title = {Breaking the Pairing Shortcut in Medical Visual In-Context Learning},
  author = {Wan, Cheng and Li, Chenjun and Zhao, Qingyu},
  journal = {arXiv preprint},
  year = {2026},
}

arXiv

Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling

Cheng Wan, Bahram Jafrasteh, Ehsan Adeli, Miaomiao Zhang, and Qingyu Zhao

arXiv preprint arXiv:2601.14584, 2026

Bib HTML PDF

@article{wan2026agldm,
  title = {Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling},
  author = {Wan, Cheng and Jafrasteh, Bahram and Adeli, Ehsan and Zhang, Miaomiao and Zhao, Qingyu},
  journal = {arXiv preprint arXiv:2601.14584},
  year = {2026},
}

MIDL

Synthetic Vasculature and Pathology Enhance Vision-Language Model Reasoning

Chenjun Li, Cheng Wan, Laurin Lux, Alexander Berger, Richard B. Rosen, Martin J. Menten, and Johannes C. Paetzold

Medical Imaging with Deep Learning (MIDL), 2026

Spotlight

Bib HTML

@inproceedings{li2026svr,
  title = {Synthetic Vasculature and Pathology Enhance Vision-Language Model Reasoning},
  author = {Li, Chenjun and Wan, Cheng and Lux, Laurin and Berger, Alexander and Rosen, Richard B. and Menten, Martin J. and Paetzold, Johannes C.},
  booktitle = {Medical Imaging with Deep Learning (MIDL)},
  year = {2026},
  note = {Spotlight},
}

Neurocomputing

HyCTAS: Multi-Objective Hybrid Convolution-Transformer Architecture Search for Real-Time Image Segmentation

Hongyuan Yu, Cheng Wan, Xiyang Dai, Mengchen Liu, Dongdong Chen, Bin Xiao, Yan Huang, Yuan Lu, and Liang Wang

Neurocomputing, 2025

Bib HTML PDF

@article{yu2025hyctas,
  title = {HyCTAS: Multi-Objective Hybrid Convolution-Transformer Architecture Search for Real-Time Image Segmentation},
  author = {Yu, Hongyuan and Wan, Cheng and Dai, Xiyang and Liu, Mengchen and Chen, Dongdong and Xiao, Bin and Huang, Yan and Lu, Yuan and Wang, Liang},
  journal = {Neurocomputing},
  year = {2025},
}

J-BHI

Advancing Sleep Disorder Diagnostics: A Transformer-based EEG Model for Sleep Stage Classification and OSA Prediction

Cheng Wan, Micky C. Nnamdi, Wenqi Shi, Benjamin Smith, Chad Purnell, and May Dongmei Wang

IEEE Journal of Biomedical and Health Informatics (J-BHI), 2024

BHI Oral, 8% acceptance rate

Bib HTML

@article{wan2024sleep,
  title = {Advancing Sleep Disorder Diagnostics: A Transformer-based EEG Model for Sleep Stage Classification and OSA Prediction},
  author = {Wan, Cheng and Nnamdi, Micky C. and Shi, Wenqi and Smith, Benjamin and Purnell, Chad and Wang, May Dongmei},
  journal = {IEEE Journal of Biomedical and Health Informatics (J-BHI)},
  year = {2024},
  note = {BHI Oral, 8% acceptance rate},
}

CVPR-W

Swift Parameter-free Attention Network for Efficient Super-Resolution

Cheng Wan^*, Hongyuan Yu^*, Zhiqi Li^*, Yihang Chen, Yajun Zou, Yuqing Liu, Xuanwu Yin, and Kunlong Zuo

IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W), 2024

Winner Award and Oral at NTIRE Workshop

Bib HTML

@inproceedings{wan2024swift,
  title = {Swift Parameter-free Attention Network for Efficient Super-Resolution},
  author = {Wan, Cheng and Yu, Hongyuan and Li, Zhiqi and Chen, Yihang and Zou, Yajun and Liu, Yuqing and Yin, Xuanwu and Zuo, Kunlong},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W)},
  year = {2024},
  note = {Winner Award and Oral at NTIRE Workshop},
}

arXiv

Breaking the Pairing Shortcut in Medical Visual In-Context Learning

Cheng Wan, Chenjun Li, and Qingyu Zhao

arXiv preprint, 2026

Bib HTML

@article{wan2026pairing,
  title = {Breaking the Pairing Shortcut in Medical Visual In-Context Learning},
  author = {Wan, Cheng and Li, Chenjun and Zhao, Qingyu},
  journal = {arXiv preprint},
  year = {2026},
}

arXiv

MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text

Chenjun Li, Cheng Wan, Haomiao Chen, and Johannes C. Paetzold

arXiv preprint, 2026

Bib HTML

@article{li2026meld,
  title = {MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text},
  author = {Li, Chenjun and Wan, Cheng and Chen, Haomiao and Paetzold, Johannes C.},
  journal = {arXiv preprint},
  year = {2026},
}

arXiv

Your Simulation Runs but Solves the Wrong Physics: PDE-Grounded Intent Verification for LLM-Generated Multiphysics Simulation Code

Zhenghan Song, Yulong Liu, Cheng Wan, Chenjun Li, Lingfu Liu, Yunyi Li, and Congcong Yuan

arXiv preprint, 2026

Bib HTML

@article{song2026pde,
  title = {Your Simulation Runs but Solves the Wrong Physics: PDE-Grounded Intent Verification for LLM-Generated Multiphysics Simulation Code},
  author = {Song, Zhenghan and Liu, Yulong and Wan, Cheng and Li, Chenjun and Liu, Lingfu and Li, Yunyi and Yuan, Congcong},
  journal = {arXiv preprint},
  year = {2026},
}

arXiv

Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling

Cheng Wan, Bahram Jafrasteh, Ehsan Adeli, Miaomiao Zhang, and Qingyu Zhao

arXiv preprint arXiv:2601.14584, 2026

Bib HTML PDF

@article{wan2026agldm,
  title = {Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling},
  author = {Wan, Cheng and Jafrasteh, Bahram and Adeli, Ehsan and Zhang, Miaomiao and Zhao, Qingyu},
  journal = {arXiv preprint arXiv:2601.14584},
  year = {2026},
}

MIDL

Synthetic Vasculature and Pathology Enhance Vision-Language Model Reasoning

Chenjun Li, Cheng Wan, Laurin Lux, Alexander Berger, Richard B. Rosen, Martin J. Menten, and Johannes C. Paetzold

Medical Imaging with Deep Learning (MIDL), 2026

Spotlight

Bib HTML

@inproceedings{li2026svr,
  title = {Synthetic Vasculature and Pathology Enhance Vision-Language Model Reasoning},
  author = {Li, Chenjun and Wan, Cheng and Lux, Laurin and Berger, Alexander and Rosen, Richard B. and Menten, Martin J. and Paetzold, Johannes C.},
  booktitle = {Medical Imaging with Deep Learning (MIDL)},
  year = {2026},
  note = {Spotlight},
}

MICCAI

WASABI: A Metric for Evaluating Morphometric Plausibility of Synthetic Brain MRIs

Bahram Jafrasteh^*, Wei Peng^*, Cheng Wan, Yimin Luo, Ehsan Adeli, and Qingyu Zhao

Medical Image Computing and Computer Assisted Intervention (MICCAI), 2025

Bib HTML PDF

@article{jafrasteh2025wasabi,
  title = {WASABI: A Metric for Evaluating Morphometric Plausibility of Synthetic Brain MRIs},
  author = {Jafrasteh, Bahram and Peng, Wei and Wan, Cheng and Luo, Yimin and Adeli, Ehsan and Zhao, Qingyu},
  journal = {Medical Image Computing and Computer Assisted Intervention (MICCAI)},
  year = {2025},
}

ICASSP

A Multi-scenario Attention-based Generative Model for Personalized Blood Pressure Time Series Forecasting

Cheng Wan, Chenjie Xie, Longfei Liu, Dan Wu, and Ye Li

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2025

Bib HTML PDF

@inproceedings{wan2025multi,
  title = {A Multi-scenario Attention-based Generative Model for Personalized Blood Pressure Time Series Forecasting},
  author = {Wan, Cheng and Xie, Chenjie and Liu, Longfei and Wu, Dan and Li, Ye},
  booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year = {2025},
}

Neurocomputing

HyCTAS: Multi-Objective Hybrid Convolution-Transformer Architecture Search for Real-Time Image Segmentation

Hongyuan Yu, Cheng Wan, Xiyang Dai, Mengchen Liu, Dongdong Chen, Bin Xiao, Yan Huang, Yuan Lu, and Liang Wang

Neurocomputing, 2025

Bib HTML PDF

@article{yu2025hyctas,
  title = {HyCTAS: Multi-Objective Hybrid Convolution-Transformer Architecture Search for Real-Time Image Segmentation},
  author = {Yu, Hongyuan and Wan, Cheng and Dai, Xiyang and Liu, Mengchen and Chen, Dongdong and Xiao, Bin and Huang, Yan and Lu, Yuan and Wang, Liang},
  journal = {Neurocomputing},
  year = {2025},
}

BCB

KindSleep: Knowledge-Informed Diagnosis of Obstructive Sleep Apnea from Oximetry

Micky C. Nnamdi, Wenqi Shi, Cheng Wan, J. Ben Tamo, Benjamin M. Smith, Chad A. Purnell, and May Dongmei Wang

ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB), 2025

Bib HTML

@inproceedings{nnamdi2025kindsleep,
  title = {KindSleep: Knowledge-Informed Diagnosis of Obstructive Sleep Apnea from Oximetry},
  author = {Nnamdi, Micky C. and Shi, Wenqi and Wan, Cheng and Tamo, J. Ben and Smith, Benjamin M. and Purnell, Chad A. and Wang, May Dongmei},
  booktitle = {ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (BCB)},
  year = {2025},
}

J-BHI

Advancing Sleep Disorder Diagnostics: A Transformer-based EEG Model for Sleep Stage Classification and OSA Prediction

Cheng Wan, Micky C. Nnamdi, Wenqi Shi, Benjamin Smith, Chad Purnell, and May Dongmei Wang

IEEE Journal of Biomedical and Health Informatics (J-BHI), 2024

BHI Oral, 8% acceptance rate

Bib HTML

@article{wan2024sleep,
  title = {Advancing Sleep Disorder Diagnostics: A Transformer-based EEG Model for Sleep Stage Classification and OSA Prediction},
  author = {Wan, Cheng and Nnamdi, Micky C. and Shi, Wenqi and Smith, Benjamin and Purnell, Chad and Wang, May Dongmei},
  journal = {IEEE Journal of Biomedical and Health Informatics (J-BHI)},
  year = {2024},
  note = {BHI Oral, 8% acceptance rate},
}

BIBM

ECG-LLM: Leveraging Large Language Models for Low-Quality ECG Signal Restoration

Longfei Liu, Guosheng Cui, Cheng Wan, Dan Wu, and Ye Li

IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2024

Bib HTML

@inproceedings{liu2024ecg,
  title = {ECG-LLM: Leveraging Large Language Models for Low-Quality ECG Signal Restoration},
  author = {Liu, Longfei and Cui, Guosheng and Wan, Cheng and Wu, Dan and Li, Ye},
  booktitle = {IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},
  year = {2024},
}

CVPR-W

Swift Parameter-free Attention Network for Efficient Super-Resolution

Cheng Wan^*, Hongyuan Yu^*, Zhiqi Li^*, Yihang Chen, Yajun Zou, Yuqing Liu, Xuanwu Yin, and Kunlong Zuo

IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W), 2024

Winner Award and Oral at NTIRE Workshop

Bib HTML

@inproceedings{wan2024swift,
  title = {Swift Parameter-free Attention Network for Efficient Super-Resolution},
  author = {Wan, Cheng and Yu, Hongyuan and Li, Zhiqi and Chen, Yihang and Zou, Yajun and Liu, Yuqing and Yin, Xuanwu and Zuo, Kunlong},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPR-W)},
  year = {2024},
  note = {Winner Award and Oral at NTIRE Workshop},
}

arXiv

Unveiling Linear Mode Connectivity of Re-basin from Neuron Distribution Perspective

Zhiqi Li^*, Zexi Li^*, Mian Wu^*, Cheng Wan^*, and Chao Wu

arXiv preprint, 2024

Bib HTML

@article{li2024nonconnectivity,
  title = {Unveiling Linear Mode Connectivity of Re-basin from Neuron Distribution Perspective},
  author = {Li, Zhiqi and Li, Zexi and Wu, Mian and Wan, Cheng and Wu, Chao},
  journal = {arXiv preprint},
  year = {2024},
}

arXiv

PRISM-Bench: A Benchmark of Puzzle-Based Visual Tasks with CoT Error Detection

Yusu Qian^*, Cheng Wan^*, Chao Jia, Yinfei Yang, Qingyu Zhao, and Zhe Gan

arXiv preprint arXiv:2510.23594, 2025

Bib HTML PDF

@article{qian2024prism,
  title = {PRISM-Bench: A Benchmark of Puzzle-Based Visual Tasks with CoT Error Detection},
  author = {Qian, Yusu and Wan, Cheng and Jia, Chao and Yang, Yinfei and Zhao, Qingyu and Gan, Zhe},
  journal = {arXiv preprint arXiv:2510.23594},
  year = {2025},
}

Experience

Research Intern Adobe (Firefly) May 2026 – Aug 2026

Pretraining @ Adobe Firefly. We research the pretraining efficiency of generative foundation models, and also work on RL and OPD.

Teaching

Teaching Assistant: Foundations Machine Learning (ECE 5200/3200)
Spring 2025 @ Cornell University