This web site is outdated. Please see Google Scholar for research projects ongoing in my group.

• (8/5/17) Awarded a $470,796 NSF grant to study the application of deep learning to genomics and other biomedical data.
• (7/31/17) Congratulations to Daniel Quang for successfully defending his PhD thesis!
• (7/17/17) Awarded an opportunity award from CCBS to develop computational methods for characterizing metastatic potential by single cell DNA sequencing.
• (7/11/17) My group ranked #1 in the AI Tianchi Competition organized by Alibaba and Intel. 2886 teams participated in this compettion, the goal of which is to automatically detect nodules in low-dose lung CT images. Congratulations to team members - Daniel Kim & Hao Tang! Our solution is based on 3D Convolutional Neural Nets.
• (7/5/17) My comments in Science on the impact of deep learning to genomics: AI is changing how we do science. Get a glimpse
• (2/1/17) My group is one of winning teams in the ENCODE-DREAM Challenge. Congratulations to Daniel Quang!

• Tang H et al. Clinically applicable deep learning framework for organs at risk delineation in CT images Nature Machine Intelligence, 2019
• Yu R, Wang X and Xie X VTNFP: An Image-based Virtual Try-on Network with Body and Clothing Feature Preservation ICCV, 2019
• Kong D et al. Adaptive Graphical Model Network BMVC, 2019
• Chen L et al. TAGAN: Tonality Aligned Generative Adversarial Networks for Realistic Hand Pose Synthesis BMVC, 2019
• Tang H. et al. NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation MICCAI, 2019
• Wang Z et al. Structed Triplets Learning with Pos-tag Guided Attention for Visual Question Answering IEEE Winter Conf. on Applications of Computer Vision 2018
• Tang H, Kim D, and Xie X Automated Pulmonary Nodule Detection Using 3D Deep Convolutional Neural Networks IEEE International Symposium on Biomedical Imaging
• Zhu W, Lou Q, Vang YS, and Xie X Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification MICCAI 2017
• Quang D and Xie X DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences Nucleic Acids Research 2016
• Zhu W, Lan C, Xing J, Zeng W, Li Y, Shen L, and Xie X Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks AAAI Conference on Artificial Intelligence 2016
• Chen Y, Li Y, Narayan R, Subramanian A, and Xie X Gene expression inference with deep learning Bioinformatics 2016
• Kim I and Xie X Handwritten Hangul recognition using deep convolutional neural networks International Journal on Document Analysis and Recognition, 2014
  preprint
• Ye G and Xie X Learning sparse gradients for variable selection and dimension reduction Machine Learning Journal, 87(3):303-355 2012
  Preprint
• Ye G, Chen Y, and Xie X Efficient variable selection in support vector machines via the alternating direction method of multipliers AI & STATS, 2011
• Ye G-B and Xie X Bregman method for large scale fused Lasso Computational Statistics and Data Analysis, 2011

• CS273P Machine Learning and Data Mining, Spring 2019
• CS175 Project in Artificial Intelligence, Spring 2018
• CS206 Principles of Scientific Computing, Spring 2017
• ICS6N Computational Linear Algebra, Winter 2017
• CS206 Principles of Scientific Computing, Spring, 2014
• Math 227C/CS 285 Stochastic differential equations, Spring, 2014
• CS295: Convex Optimization, Winter, 2011
• CS190/295: Programmng in Python for Life Sciences , Winter, 2012
• CS295: Stochastic Differential Equations in Systems Biology and Engineering, Spring, 2011
• CS284A: Representations & Algorithms for Molecular Biology , Fall, 2010