- Short Bio
Xiaohui Xie is a full profesor in the Department of Computer Science
at UC Irvine, where he has
been since 2007. He received his PhD from MIT, and completed his postdoctoral
training at the Broad Institute of MIT and Harvard. He is interested
in machine learning, neural networks, deep learning, and genomics. He lives in Irvine, California.
- Recent News
-
(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!
- Research Interests
AI/Machine Learning, Neural Networks, Deep Learning, Geonomics
Search for my publications at
Google Scholar
- Selected
Recent Publications
See all publications
-
Tang H et al.
Clinically applicable deep learning framework for organs at risk delineation in CT images
Nature Machine Intelligence, 2019
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Yu R, Wang X and Xie X
VTNFP: An Image-based Virtual Try-on Network with Body and Clothing Feature Preservation
ICCV, 2019
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Kong D et al.
Adaptive Graphical Model Network
BMVC, 2019
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Chen L et al.
TAGAN: Tonality Aligned Generative Adversarial Networks for Realistic Hand Pose Synthesis
BMVC, 2019
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Tang H. et al.
NoduleNet: Decoupled False Positive Reduction for Pulmonary Nodule Detection and Segmentation
MICCAI, 2019
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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
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Tang H, Kim D, and Xie X
Automated Pulmonary Nodule Detection Using 3D Deep Convolutional Neural Networks
IEEE International Symposium on Biomedical Imaging
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Zhu W, Lou Q, Vang YS, and Xie X
Deep Multi-instance Networks with
Sparse Label Assignment for Whole Mammogram Classification
MICCAI 2017
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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
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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
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Chen Y, Li Y, Narayan R, Subramanian A, and Xie X
Gene
expression inference with deep learning
Bioinformatics
2016
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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
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Ye G, Chen Y, and Xie X
Efficient
variable selection in support vector machines via the alternating
direction method of multipliers
AI & STATS,
2011
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Ye G-B and Xie X
Bregman method for large scale fused Lasso
Computational Statistics and Data Analysis,
2011
- Teaching
- 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
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CS206
Principles of Scientific Computing, Spring, 2014
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Math
227C/CS 285 Stochastic differential equations, Spring, 2014
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CS295: Convex Optimization, Winter, 2011
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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
