Tao Peng Ph.D. Student [CV] Center for Bioimage Informatics Department of Biomedical Engineering Carnegie Mellon University

Office: Hamerschlag Hall C119 Email: tpeng@cmu.edu Phone: (412)-268-8379

 

Short Bio

I received my B.E. degree from Biomedical Engineering Department, Tsinghua University in July 2006. Then I came to the United States and am now studying towards Ph.D. degree in Biomedical Engineering, Carnegie Mellon University. I am a member of Center for Bioimage Informatics and Murphy Lab. My academic advisor is Prof. Robert F. Murphy.

Research Interests

My research interest resides in microscopy image analysis, towards recognition, interpretation and modeling of protein subcellular location patterns. Specifically, the research projects that I have been involved with include automated unmixing of complex protein subcellular location patterns and building statistical generative model of 3D protein location images.

Research Experience

• Generative model of 3D protein subcellular location pattern images: use digital camera collected microscope images to learn a compact and statistical accurate model from which new instances of protein location images can be synthesized.
• Automated unmixing of complex subcellular location patterns: with multiple location patterns reside in single image, learn the information of basic patterns and estimate their fractions in complex pattern images.
• Diffeomorphism of cellular/subcellular shapes: perform deformation across shapes to synthesize shape instances not included in the training set.

Teaching Experience

Teaching Assistant, Carnegie Mellon University, Spring 2008/2007

• 03-510/42-434: Computational Biology
• Instructor: Prof. Robert F. Murphy

Teaching Assistant, Carnegie Mellon University, Fall 2007

• 42-101: Introduction To Biomedical Engineering
• Instructor: Prof. Robert D. Tilton

Graduate Mentor, Carnegie Mellon University, Summer 2007

• SUREBET Summer Undergraduate Research Program
• Student: Aimee Sanchez

Industrial Experience

Intern, Siemens Medical Solutions Inc., May-Aug. 2010

• Research/Development: Computed tomography images normalization and quality control.
• Mentor: Matthias Wolf

Graduate Courses

Carnegie Mellon University

• 15-826: Multimedia databases and data mining. Spring 2010.
• 15-853: Algorithms in the "Real World". Fall 2009.
• 10-708: Probabilistic graphical models. Fall 2008.
• 10-702: Statistical machine learning. Spring 2008.
• 42-707: Readings in bioimage informatics. Spring 2008.
• 36-705: Intermediate statistics. Fall 2007.
• 16-720: Computer vision. Fall 2007.
• 42-708: Registration in bioimaging. Fall 2007.
• 10-701: Machine learning. Spring 2007.
• 42-759: Cellular biomechanics. Spring 2007.
• 36-625: Probability & statistics. Fall 2006.
• 42-702: Advanced physiology. Fall 2006.
• 03-231: Biochemistry I. Fall 2006. (undergraduate level)

Publications

• T. Peng, R. F. Murphy. Image-derived, three-dimensional generative models of cellular organization. XXVI Congress of the International Society for Advancement of Cytometry. Accepted.
• X. Jiang, Q. Wu, T. Peng, and L. Sweeney. Structure preserving semantic coherent object segmentation. Proceedings of 17th IEEE International Conference on Image Processing. 2010.
• L. P. Coelho, T. Peng, and R.F. Murphy. Quantifying the distribution of probes between subcellular locations using unsupervised pattern unmixing. Bioinformatics. 26: i7-i12. 2010. [PDF] (co-first author)
• T. Peng, G. M. C. Bonamy, E. Glory, D. Rines, S. K. Chanda, and R. F. Murphy. Automated unmixing of subcellular patterns: determining the distribution of probes between different subcellular locations. Proceedings of the National Academy of Sciences. 107: 2944-2949. 2010. [PDF][SI][Software/Data]
• W. Wang, C. Chen, T. Peng, D. Slepcev, J. Ozolek, G. K. Rohde. A graph-based method for detecting characteristic phenotypes from biomedical images. Proceedings of 7^th IEEE International Symposium on Biomedical Imaging. pp. 129-132. 2010. [PDF]
• T. Peng, W. Wang, G. K. Rohde, R. F. Murphy. Instance-Based generative biological shape modeling. Proceedings of 6^th IEEE International Symposium on Biomedical Imaging. pp. 690-693. June 2009. [PDF]
• G. K. Rohde, W. Wang, T. Peng, and R. F. Murphy. Deformation-based non-linear dimension reduction: application to nuclear morphometry. Proceedings of 5th IEEE International Symposium on Biomedical Imaging. pp. 500-503. May 2008. [PDF]

Last Updated: Dec 06, 2010