About Me

I am a Ph.D. candidate in the Department of Computer Science at the University of Illinois at Chicago. I am working as a research assistant in the BDSC Lab advised by Prof. Philip S. Yu and the CoNECt Lab advised by Prof. Alex D. Leow. Before joining UIC, I received B.Eng. in Computer Science and B.Sc. in Mathematics from the School of Information at Renmin University of China.

My research interests lie in the fields of data mining and machine learning. In particular, I focus on the development and analysis of algorithms for brain, social and information networks, as well as multi-view learning, feature selection, tensor factorization, deep learning and time series analysis.

Publications

Unsupervised Feature Selection with Heterogeneous Side Information

Xiaokai Wei, Bokai Cao and Philip S. Yu
ACM International Conference on Information and Knowledge Management (CIKM), Singapore, November 6–10, 2017
[bib]

Rethinking Unsupervised Feature Selection: From Pseudo Labels to Pseudo Must-links

Xiaokai Wei, Sihong Xie, Bokai Cao and Philip S. Yu
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), Skopje, Macedonia, September 18–22, 2017
[bib]

Sequential Keystroke Behavioral Biometrics for Mobile User Identification via Multi-view Deep Learning

Lichao Sun, Yuqi Wang, Bokai Cao, Philip S. Yu, Witawas Srisa-an and Alex D. Leow
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), Skopje, Macedonia, September 18–22, 2017
[bib]

DeepMood: Modeling Mobile Phone Typing Dynamics for Mood Detection

Bokai Cao, Lei Zheng, Chenwei Zhang, Philip S. Yu, Andrea Piscitello, John Zulueta, Olu Ajilore, Kelly Ryan and Alex D. Leow
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Halifax, Nova Scotia, Canada, August 13-17, 2017
BiAffect is the winner of the Mood Challenge for ResearchKit!
[paper] [video] [poster] [code] [app] [bib]

Structural Deep Brain Network Mining

Shen Wang, Lifang He, Bokai Cao, Chun-Ta Lu, Philip S. Yu and Ann B. Ragin
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Halifax, Nova Scotia, Canada, August 13-17, 2017
[video] [bib]

Multi-view Unsupervised Feature Selection by Cross-diffused Matrix Alignment

Xiaokai Wei, Bokai Cao and Philip S. Yu
International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska, USA, May 14–19, 2017
[paper] [bib]

t-BNE: Tensor-based Brain Network Embedding

Bokai Cao, Lifang He, Xiaokai Wei, Mengqi Xing, Philip S. Yu, Heide Klumpp and Alex D. Leow
SIAM International Conference on Data Mining (SDM), Houston, Texas, USA, April 27-29, 2017
[paper] [slides] [poster] [code] [bib]

Cross View Link Prediction by Learning Noise-resilient Representation Consensus

Xiaokai Wei, Linchuan Xu, Bokai Cao and Philip S. Yu
International World Wide Web Conference (WWW), Perth, Australia, April 3-7, 2017
[bib]

A Novel Ensemble Approach on Regionalized Neural Networks for Brain Disorder Prediction

Lei Zheng, Jingyuan Zhang, Bokai Cao, Philip S. Yu and Ann B. Ragin
ACM SIGAPP Symposium on Applied Computing (SAC), Marrakech, Morocco, April 4-6, 2017
[bib]

Multilinear Factorization Machines for Multi-Task Multi-View Learning

Chun-Ta Lu, Lifang He, Weixiang Shao, Bokai Cao and Philip S. Yu
ACM International Conference on Web Search and Data Mining (WSDM), Cambridge UK, February 6-10, 2017
[bib]

Community Detection with Partially Observable Links and Node Attributes

Xiaokai Wei, Bokai Cao, Weixiang Shao, Chun-Ta Lu and Philip S. Yu
IEEE International Conference on Big Data, Washington D.C., USA, December 5-8, 2016
[bib]

Semi-supervised Tensor Factorization for Brain Network Analysis

Bokai Cao, Chun-Ta Lu, Xiaokai Wei, Philip S. Yu and Alex D. Leow
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), Riva del Garda, Italy, September 19–23, 2016
[paper] [slides] [code] [bib]

Multi-Graph Clustering based on Interior-Node Topology with Applications to Brain Networks

Guixiang Ma, Lifang He, Bokai Cao, Jiawei Zhang and Philip S. Yu
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD), Riva del Garda, Italy, September 19–23, 2016
[bib]

Nonlinear Joint Unsupervised Feature Selection

Xiaokai Wei, Bokai Cao and Philip S. Yu
SIAM International Conference on Data Mining (SDM), Miami, Florida, USA, May 5-7, 2016
[bib]

Identifying Connectivity Patterns for Brain Diseases via Multi-side-view Guided Deep Architectures

Jingyuan Zhang, Bokai Cao, Sihong Xie, Chun-Ta Lu, Philip S. Yu and Ann B. Ragin
SIAM International Conference on Data Mining (SDM), Miami, Florida, USA, May 5-7, 2016
[bib]

Multi-view Machines

Bokai Cao, Hucheng Zhou, Guoqiang Li and Philip S. Yu
ACM International Conference on Web Search and Data Mining (WSDM), San Francisco, California, USA, February 22-25, 2016
[paper] [slides] [poster] [code] [bib]

Unsupervised Feature Selection on Networks: A Generative View

Xiaokai Wei, Bokai Cao and Philip S. Yu
AAAI Conference on Artificial Intelligence (AAAI), Phoenix, Arizona USA, February 12–17, 2016
[paper] [bib]

Identifying HIV-induced Subgraph Patterns in Brain Networks with Side Information

Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu and Ann B. Ragin
Brain Informatics 2015
[paper] [bib]

A Review of Heterogeneous Data Mining for Brain Disorder Identification

Bokai Cao, Xiangnan Kong and Philip S. Yu
Brain Informatics 2015
[paper] [slides] [bib]

Determinants of HIV-induced Brain Changes in Three Different Periods of the Early Clinical Course: A Data Mining Analysis

Bokai Cao, Xiangnan Kong, Casey Kettering, Philip S. Yu and Ann B. Ragin
NeuroImage: Clinical 2015
[paper] [bib]

Mining Brain Networks using Multiple Side Views for Neurological Disorder Identification

Bokai Cao, Xiangnan Kong, Jingyuan Zhang, Philip S. Yu and Ann B. Ragin
IEEE International Conference on Data Mining (ICDM), Atlantic City, New Jersey, USA, November 14-17, 2015
[paper] [slides] [bib]

Inferring Crowd-Sourced Venues for Tweets

Bokai Cao, Francine Chen, Dhiraj Joshi and Philip S. Yu
IEEE International Conference on Big Data, Santa Clara, California, USA, October 29 - November 1, 2015
[paper] [slides] [bib]

Identification of Discriminative Subgraph Patterns in fMRI Brain Networks in Bipolar Affective Disorder

Bokai Cao, Liang Zhan, Xiangnan Kong, Philip S. Yu, Nathalie Vizueta, Lori L. Altshuler and Alex D. Leow
International Conference on Brain Informatics and Health (BIH), London, UK, August 30 - September 2, 2015
[paper] [slides] [bib]

Tensor-based Multi-view Feature Selection with Applications to Brain Diseases

Bokai Cao, Lifang He, Xiangnan Kong, Philip S. Yu, Zhifeng Hao and Ann B. Ragin
IEEE International Conference on Data Mining (ICDM), Shenzhen, China, December 14-17, 2014
selected as one of the best papers for possible publication in Knowledge and Information Systems
[paper] [slides] [bib]

Collective Prediction of Multiple Types of Links in Heterogeneous Information Networks

Bokai Cao, Xiangnan Kong and Philip S. Yu
IEEE International Conference on Data Mining (ICDM), Shenzhen, China, December 14-17, 2014
[paper] [slides] [bib]

Multi-label Classification by Mining Label and Instance Correlations from Heterogeneous Information Networks

Xiangnan Kong, Bokai Cao and Philip S. Yu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Chicago, Illinois, USA, August 11-14, 2013
[paper] [poster] [bib]

Office

851 S. Morgan St., Rm 1336 SEO, Chicago, IL 60607

Email

caobokai at uic dot edu