publications

2025

1. RA-L

   

   DOSE3: Diffusion-based Unified Out-Of-Distribution Detection on SE(3) Trajectories

   Hongzhe Cheng^*, Tianyou Zhang^*, Ziyong Ma^*, Tianyi Zhang, Matthew Johnson-Roberson, and Weiming Zhi

   IEEE Robotics and Automation Letters (RA-L), 2025

   Abs Bib

   A diffusion-based approach for unified out-of-distribution detection in robotic trajectory planning, improving safety and reliability in uncertain environments.

   @article{ma2024pose3,
     title = {DOSE3: Diffusion-based Unified Out-Of-Distribution Detection on SE(3) Trajectories},
     author = {Cheng, Hongzhe and Zhang, Tianyou and Ma, Ziyong and Zhang, Tianyi and Johnson-Roberson, Matthew and Zhi, Weiming},
     journal = {IEEE Robotics and Automation Letters (RA-L)},
     year = {2025},
     tags = {robotics}
   }

2. ML4H

   

   TempoQL: A Readable, Precise, and Portable Query System for Electronic Health Record Data

   Ziyong Ma, Venkatesh Sivaraman, Richard D Boyce, and Adam Perer

   In Proceedings of the Machine Learning for Healthcare (ML4H), 2025

   Also Presented at TS4H @ NeurIPS 2025

   Abs Bib Code

   A readable, precise, and portable query system designed for electronic health record data analysis, enabling healthcare professionals to perform complex temporal queries with ease.

   @inproceedings{ma2025tempoql,
     title = {TempoQL: A Readable, Precise, and Portable Query System for Electronic Health Record Data},
     author = {Ma, Ziyong and Sivaraman, Venkatesh and Boyce, Richard D and Perer, Adam},
     booktitle = {Proceedings of the Machine Learning for Healthcare (ML4H)},
     year = {2025},
     note = {Also Presented at TS4H @ NeurIPS 2025},
     tags = {healthcare}
   }

3. NeurIPS

   

   Building 3D Representations and Generating Motions From a Single Image via Video-Generation

   Weiming Zhi, Ziyong Ma, Tianyi Zhang, and Matthew Johnson-Roberson

   In Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS 2025), 2025

   Abs arXiv Bib

   This work explores environment representation through video generation from single images to enable motion policy learning for robotic systems.

   @inproceedings{ma2024single,
     title = {Building 3D Representations and Generating Motions From a Single Image via Video-Generation},
     author = {Zhi, Weiming and Ma, Ziyong and Zhang, Tianyi and Johnson-Roberson, Matthew},
     booktitle = {Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS 2025)},
     year = {2025},
     publisher = {NeurIPS,},
     tags = {robotics}
   }

4. arXiv

   

   OpenFLAME: A Federated Spatial Naming Infrastructure

   Sagar Bharadwaj, Ziyong Ma, Ivan Liang, Michael Farb, Anthony Rowe, and Srinivasan Seshan

   In arXiv, 2025

   Abs arXiv Bib Website

   A moderated heterogeneous federated learning framework that enables data scientists to collaboratively specify predictive modeling tasks while maintaining data privacy and security.

   @inproceedings{ma2025openflame,
     title = {OpenFLAME: A Federated Spatial Naming Infrastructure},
     author = {Bharadwaj, Sagar and Ma, Ziyong and Liang, Ivan and Farb, Michael and Rowe, Anthony and Seshan, Srinivasan},
     booktitle = {arXiv},
     year = {2025},
     publisher = {arXiv,},
     tags = {system}
   }

5. CHI

   

   Tempo: Helping Data Scientists and Domain Experts Collaboratively Specify Predictive Modeling Tasks

   Venkatesh Sivaraman, Anika Vaishampayan, Xiaotong Li, Brian R Buck, Ziyong Ma, Richard D Boyce, and Adam Perer

   In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI 2025), 2025

   Abs arXiv Bib Code

   We present Tempo, a system that facilitates collaboration between data scientists and domain experts for specifying predictive modeling tasks.

   @inproceedings{sivaraman2025tempo,
     title = {Tempo: Helping Data Scientists and Domain Experts Collaboratively Specify Predictive Modeling Tasks},
     author = {Sivaraman, Venkatesh and Vaishampayan, Anika and Li, Xiaotong and Buck, Brian R and Ma, Ziyong and Boyce, Richard D and Perer, Adam},
     booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI 2025)},
     year = {2025},
     publisher = {ACM},
     tags = {healthcare}
   }

2024

1. ASEE

   Introducing Students to Research and Reproducibility with Open Science Tools

   Chaaz Griego, Cheng Zhang, Wenchan Hu, Ziyong Ma, and Andy Ouyang

   In Proceedings of the 2024 ASEE Annual Conference & Exposition, 2024

   Abs Bib

   An educational framework for introducing undergraduate students to research methodologies and reproducibility through hands-on experience with modern open science tools and techniques.

   @inproceedings{ma2024introducing,
     title = {Introducing Students to Research and Reproducibility with Open Science Tools},
     author = {Griego, Chaaz and Zhang, Cheng and Hu, Wenchan and Ma, Ziyong and Ouyang, Andy},
     booktitle = {Proceedings of the 2024 ASEE Annual Conference & Exposition},
     year = {2024},
     publisher = {ASEE,}
   }