Carnegie Mellon University

 Min Xu

Assistant Professor, Computational Biology Department, Co-Director, MS in Computational Biology Program


Gates Hillman Center 7709
Computational Biology Department, SCS
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213



Administrative Assistant: Ally Ricarte


Dr. Xu is currently developing computer vision and machine learning methods for the automatic structural analysis of cell systems at molecular resolution and in close-to-native states. In particular, his research focuses on information extraction and modelling of the structures and spatial organizations of macromolecules and their interactions with organelles in single cells captured by cryo electron-tomography 3D images. This emerging research field aims to address fundamental biological questions using a wide range of state-of-the-art computational and mathematical techniques.

 Titas Chakraborty 

Research Assistant (MLD, MSML)

 Ali Dabouei

 Abhinand Jha

Research Assistant (ECE)

 Shirley Kokane

Research Assistant (ECE)

 Mostofa Rafid Uddin

Ph.D. Student

Highlighted Publications

Gupta T, He X, Uddin M, Zeng X, Zhou A, Zhang J, Freyberg, Xu M. Self-supervised learning for macromolecular structure classification based on cryo-electron tomograms. Frontiers in Physiology. 

Zeng X, Lin Z, Uddin M, Zhou B, Cheng C, Zhang J, Freyberg, Xu M. Structure Detection in Three-Dimensional Cellular Cryoelectron Tomograms by Reconstructing Two-Dimensional Annotated Tilt Series. Journal of Computational Biology. 

Zhu H, Wang C, Wang Y, Fan Z, Uddin M, Gao X, Zhang J, Zeng X, Xu M. Unsupervised multi-task learning for 3d subtomogram image alignment, clustering and segmentation. 2022 IEEE International Conference on Image Processing (ICIP)

Uddin M, Howe G, Zeng X, Xu M. Harmony: A Generic Unsupervised Approach for Disentangling Semantic Content from Parameterized Transformations. IEEE conference on computer vision and pattern recognition (CVPR 2022). 

Wang T, Li X, Yang P, Hu G, Zeng X, Huang S, Xu C, Xu M. Boosting Active Learning via Improving Test Performance. AAAI Conference on Artificial Intelligence. (AAAI 2022) 

Cang Z, Ning X, Nie A, Xu M, Zhang J. Scan-IT: Domain segmentation of spatial transcriptomics images by graph neural network. British Machine Vision Conference (BMVC 2021). 

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