@inproceedings{imre2020graphvisual,
  title={GraphVisual: Design and Evaluation of a Web-Based Visualization Tool for Teaching and Learning Graph Visualization},
  author={Imre, Martin and Chang, Wenqing and Wang, Shuzhan and Trinter, Christine and Wang, Chaoli},
  booktitle={Proceedings of American Society for Engineering Education Annual Conference},
  volume={28},
  pages={1--28},
  year={2020}
}

@article{imre2020spectrum,
  title={Spectrum-preserving sparsification for visualization of big graphs},
  author={Imre, Martin and Tao, Jun and Wang, Yongyu and Zhao, Zhiqiang and Feng, Zhuo and Wang, Chaoli},
  journal={Computers \& Graphics},
  volume={87},
  pages={89--102},
  year={2020},
  publisher={Elsevier}
}

@inproceedings{imre2019contournet,
  title={ContourNet: Salient Local Contour Identification for Blob Detection in Plasma Fusion Simulation Data},
  author={Imre, Martin and Han, Jun and Dominski, Julien and Churchill, Michael and Kube, Ralph and Chang, Choong-Seock and Peterka, Tom and Guo, Hanqi and Wang, Chaoli},
  booktitle={International Symposium on Visual Computing},
  pages={289--301},
  year={2019},
  organization={Springer}
}

@article{tao2018exploring,
  title={Exploring time-varying multivariate volume data using matrix of isosurface similarity maps},
  author={Tao, Jun and Imre, Martin and Wang, Chaoli and Chawla, Nitesh V and Guo, Hanqi and Sever, G{\"o}khan and Kim, Seung Hyun},
  journal={IEEE transactions on visualization and computer graphics},
  volume={25},
  number={1},
  pages={1236--1245},
  year={2018},
  publisher={IEEE}
}

@article{imre2018identifying,
  title={Identifying nearly equally spaced isosurfaces for volumetric data sets},
  author={Imre, Martin and Tao, Jun and Wang, Chaoli},
  journal={Computers \& Graphics},
  volume={72},
  pages={82--97},
  year={2018},
  publisher={Elsevier}
}

@inproceedings{imre2017efficient,
  title={Efficient GPU-accelerated computation of isosurface similarity maps},
  author={Imre, Martin and Tao, Jun and Wang, Chaoli},
  booktitle={2017 IEEE Pacific Visualization Symposium (PacificVis)},
  pages={180--184},
  year={2017},
  organization={IEEE}
}