Chao Chen   

Assistant Professor
Department of Computer Science
CUNY Queens College & CUNY Graduate Center
A118 Science Building
65-30 Kissena Boulevard, Flushing, NY 11367

I am an assistant professor of computer science at the City University of New York (CUNY) . I am affiliated with both CUNY Queens College and CUNY Graduate Center.

I am looking for motivated graduate students and postdocs. Please contact me directly or check out the graduate program at CUNY Graduate Center. Our graduate program is ranked 82nd according to US News and is ranked 81st according to NRC ranking .

Research Interests

I explore geometric and topological properties of data. These global and robust information can provide insight for modern data analytics. My research draws from the following different domains.

  • Biomedical imaging informatics: medical images, neuron images, functional MRI.
  • Machine learning: graphical models, structured learning.
  • Topology data analysis: persistent homology, computation of topological features.
Past Experience

Publications

Conferences
  • Xiuyan Ni, Novi Quadrianto, Yusu Wang, Chao Chen: "Composing Tree Graphical Models with Persistent Homology Features for Clustering Mixed-Type Data", in the 34rd International Conference on Machine Learning (ICML), 2017, (acceptance rate 25.46%) (pdf)
  • Pengxiang Wu, Chao Chen, Yusu Wang, Shaoting Zhang, Changhe Yuan, Zhen Qian, Dimitris Metaxas, Leon Axel: "Optimal Topological Cycles and Their Application in Cardiac Trabeculae Restoration", in the 25th biennial international conference on Information Processing in Medical Imaging (IPMI), 2017, (Oral presentation, acceptance rate 14.32%, pdf)
  • Chao Chen, Novi Quadrianto: "Clustering High Dimensional Categorical Data via Topographical Features", in the 33rd International Conference on Machine Learning (ICML), 2016, (acceptance rate 24.26%) (pdf)
  • Cong Chen, Changhe Yuan, Chao Chen: "Solving M-Modes Using Heuristic Search", in the 25th International Joint Conference on Artificial Intelligence (IJCAI), 2016 (pdf)
  • Scott Kulp, Chao Chen, Dimitris Metaxas, Leon Axel: "Ventricular blood flow analysis using topological methods", in International Symposium on Biomedical Imaging (ISBI), 2015 (pdf)
  • Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao: "Mode Estimation for High Dimensional Discrete Tree Graphical Models", in Advances in Neural Information Processing Systems (NIPS), 2014 (Spotlight oral, acceptance rate ~5%, pdf, technical report available soon)
  • Mustafa Uzunbas, Chao Chen, Dimitris Metaxas: "Optree: a Learning-Based Adaptive Watershed Algorithm for Neuron Segmentation", in the 17th Annual International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2014. (Early acceptance rate ~10%, pdf)
  • Mingchen Gao, Chao Chen, Shaoting Zhang, Zhen Qian, Mani Vannan, Sarah Rinehart, Dimitris Metaxas, Leon Axel: "Morphological analysis of the papillary muscles and the trabaculae", in International Symposium on Biomedical Imaging (ISBI), 2014 (pdf)
  • Mustafa Uzunbas, Chao Chen, Shaoting Zhang, Kilian Pohl, Kang Li, Dimitris Metaxas: "Collaborative multi organ segmentation by integrating deformable and graphical models", in International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2013 (pdf)
  • Mingchen Gao *, Chao Chen *, Shaoting Zhang, Zhen Qian, Dimitris Metaxas, Leon Axel: "Segmenting the papillary muscles and the trabeculae from high resolution cardiac CT through restoration of topological handles", in International Conference on Information Processing in Medical Imaging (IPMI), 2013 (pdf) (* contributed equally)
  • Chao Chen, Vladimir Kolmogorov, Yan Zhu, Dimitris Metaxas, Christoph Lampert: "Computing the M most probable modes of a graphical model", in International Conference on Artificial Intelligence and Statistics (AISTATS), 2013 (Oral presentation, acceptance rate ~11% pdf, supplemental material)
  • Novi Quadrianto, Chao Chen, Christoph Lampert: "The most persistent soft-clique in a set of sampled graphs", in International Conference on Machine Learning (ICML), 2012 (pdf)
  • Oleksiy Busaryev, Sergio Cabello, Chao Chen, Tamal K. Dey, Yusu Wang: "Annotating simplices with a homology basis and its applications", in Scandinavian Symposium and Workshops on Algorithm Theory (SWAT), 2012 (pdf)
  • Chao Chen, Herbert Edelsbrunner: "Diffusion runs low on persistence fast", in IEEE International Conference on Computer Vision (ICCV), 2011 (Acceptance rate 23.7%, pdf, poster, code)
  • Chao Chen, Daniel Freedman, Christoph H. Lampert: "Enforcing topological constraints in random field image segmentation", in IEEE Computer Vision and Pattern Recognition (CVPR), 2011 (pdf, technical report, poster, code)
  • Chao Chen, Michael Kerber: "An output-sensitive algorithm for persistent homology", in Annual Symposium on Computational Geometry (SoCG), 2011 (pdf)
  • Chao Chen, Daniel Freedman: "Hardness results for homology localization", in Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), 2010 (pdf)
  • Chao Chen, Daniel Freedman: "Quantifying homology classes", in Annual Symposium on Theoretical Aspects of Computer Science (STACS), 2008 (pdf)
    Note: Proofs of the NP-hardness results in this paper are available in "Quantifying homology classes II: localization and stability".
Journals and Book Chapters
  • Tingting Wu, Alexander J. Dufford, Laura J. Egan, Melissa-Ann Mackie, Cong Chen, Changhe Yuan, Chao Chen, Xiaobo Li, Xun Liu, Patrick R. Hof, Jin Fan: "Hick–Hyman Law is Mediated by the Cognitive Control Network in the Brain", in Cerebral Cortex pp. 1-16, May 2017 (pdf)
  • Jingjing Liu, Chao Chen, Yan Zhu, Wei Liu, Dimitris Metaxas: “Video Classification via Weakly Supervised Sequence Modeling”, in Computer Vision and Image Understanding (CVIU) 152 pp. 79-87, Nov. 2016 (pdf)
  • Mustafa Uzunbas, Chao Chen, Dimitris Metaxas: “ An efficient conditional random field approach for automatic and interactive neuron segmentation”, in Medical Image Analysis (MedIA) 27 pp. 31-44, Jan. 2016 (pdf)
  • Arjun Jain, Chao Chen, Thorsten Thormählen, Dimitris Metaxas, Hans-Peter Seidel: “Multi-layer stencil creation from images”, in Computer & Graphics (C&G) 48 pp. 11-22, 2015 (pdf, video, website)
  • Chao Chen, Michael Kerber: “An output-sensitive algorithm for persistent homology”, in Computational Geometry: Theory and Applications (CGTA) 46 (4) pp. 435-447 - Special Issue on the 27th Annual Symposium on Computational Geometry, 2013 (pdf)
  • Yu Sheng, Barbara Cutler, Chao Chen, Joshua Nasman: "Perceptual global illumination cancellation in complex projection environments", in Computer Graphics Forum (CGF), Volume 30, Issue 4, Eurographics Symposium on Rendering (EGSR), 2011 (pdf)
  • Daniel Freedman, Chao Chen: "Algebraic topology for computer vision", Chapter 5 of Computer Vision, 239-268, Ed. Sota R. Yoshida, Nova Science Pub. Inc., Hauppauge, New York, 2011 (pdf)
  • Chao Chen, Daniel Freedman: "Hardness results for homology localization", in Discrete & Computational Geometry (DCG) 45(3): 425-448, 2011 (pdf)
  • Chao Chen, Daniel Freedman: "Measuring and computing natural generators for homology groups", in Computational Geometry: Theory and Applications (CGTA) 43(2): 169-181, 2010 (pdf)
  • Chao Chen, Ho-Lun Cheng: "Superimposing voronoi complexes for shape deformation", in International Journal of Computational Geometry and Applications (IJCGA) 16(2-3): 159-174 2006
Workshops
  • Chao Chen, Han Liu, Dimitris Metaxas, Tianqi Zhao: "Identifying Sub-Networks of Functional Connectivity Using Modes of Distributions", in the 4th NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI), 2014 (pdf available soon)
  • Hubert Wagner, Chao Chen, Erald Vuçini: "Efficient computation of persistent homology for cubical data", in Proceedings of the 4th Workshop on Topology-based Methods in Data Analysis and Visualization (TopoInVis), 2011 (Best paper runner-up, pdf)
  • Chao Chen, Michael Kerber: "Persistent homology computation with a twist", in European Workshop on Computational Geometry (EuroCG), 2011 (pdf)
  • Chao Chen, Daniel Freedman: "Topology noise removal for curve and surface evolution", in Proceedings of the Medical Computer Vision Workshop (MCV) (in conjunction with MICCAI), 2010 (pdf)

 Last modified: June 2017