About Me

I am a research scientist at Facebook. I received Ph.D. in the Department of Computer Science at the University of Illinois at Chicago. During the doctoral study, I worked as a research assistant in the BDSC Lab advised by Prof. Philip S. Yu and the CoNECt Lab advised by Prof. Alex D. Leow. Prior to 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 modeling feature interactions [slides] and broad learning for healthcare [slides].

Publications

Private Model Compression via Knowledge Distillation

Ji Wang, Weidong Bao, Lichao Sun, Xiaomin Zhu, Bokai Cao and Philip S. Yu
AAAI Conference on Artificial Intelligence (AAAI), Honolulu, USA, January 27 - February 1, 2019
[bib]

Broad Learning for Healthcare

Bokai Cao
PhD Thesis, 2018
[paper] [slides] [bib]

Joint Embedding of Meta-Path and Meta-Graph for Heterogeneous Information Networks

Lichao Sun, Lifang He, Zhipeng Huang, Bokai Cao, Congying Xia, Xiaokai Wei and Philip S. Yu
IEEE International Conference on Big Knowledge (ICBK), Singapore, November 17-18, 2018
[paper] [bib]

dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction

He Huang, Bokai Cao, Philip S. Yu, Chang-Dong Wang and Alex D. Leow
IEEE International Conference on Data Mining (ICDM), Singapore, November 17-20, 2018
[paper] [bib]

Not Just Privacy: Improving Performance of Private Deep Learning in Mobile Cloud

Ji Wang*, Jianguo Zhang*, Weidong Bao, Xiaomin Zhu, Bokai Cao and Philip S. Yu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), London, UK, August 19-23, 2018
[paper] [bib]

Deep Learning Towards Mobile Applications

Ji Wang, Bokai Cao, Philip S. Yu, Lichao Sun, Weidong Bao and Xiaomin Zhu
IEEE International Conference on Distributed Computing Systems (ICDCS), Vienna, Austria, July 2–5, 2018
[paper] [bib]

Learning from Multi-View Multi-Way Data via Structural Factorization Machines

Chun-Ta Lu, Lifang He, Hao Ding, Bokai Cao and Philip S. Yu
International World Wide Web Conference (WWW), Lyon, France, April 23-27, 2018
[paper] [bib]

Multi-View Multi-Graph Embedding for Brain Network Clustering Analysis

Ye Liu, Lifang He, Bokai Cao, Philip S. Yu, Ann B. Ragin and Alex D. Leow
AAAI Conference on Artificial Intelligence (AAAI), New Orleans, USA, February 2-7, 2018
[paper] [bib]

Connecting Emerging Relationships from News via Tensor Factorization

Jingyuan Zhang, Chun-Ta Lu, Bokai Cao, Yi Chang and Philip S. Yu
IEEE International Conference on Big Data, Boston, USA, December 11-14, 2017
[paper] [bib]

Hierarchical Collaborative Embedding for Context-Aware Recommendations

Lei Zheng, Bokai Cao, Nianzu Ma, Vahid Noroozi and Philip S. Yu
IEEE International Conference on Big Data, Boston, USA, December 11-14, 2017
[paper] [bib]

HitFraud: A Broad Learning Approach for Collective Fraud Detection in Heterogeneous Information Networks

Bokai Cao, Mia Mao, Siim Viidu and Philip S. Yu
IEEE International Conference on Data Mining (ICDM), New Orleans, USA, November 18-21, 2017
[paper] [slides] [bib]

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
[paper] [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
[paper] [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
[paper] [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, 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, Canada, August 13-17, 2017
[paper] [video] [bib]

Collective Fraud Detection Capturing Inter-Transaction Dependency

Bokai Cao, Mia Mao, Siim Viidu and Philip S. Yu
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) Workshop on Anomaly Detection in Finance, Halifax, Canada, August 13-17, 2017
[paper] [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, 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, 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
[paper] [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
[paper] [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
[paper] [slides] [poster] [code] [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
[paper] [slides] [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
[paper] [bib]

Nonlinear Joint Unsupervised Feature Selection

Xiaokai Wei, Bokai Cao and Philip S. Yu
SIAM International Conference on Data Mining (SDM), Miami, USA, May 5-7, 2016
[paper] [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, USA, May 5-7, 2016
[paper] [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, 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, 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, USA, November 14-17, 2015
[paper] [slides] [code] [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, 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] [code] [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] [code] [bib]

Meta Path-Based Collective Classification in Heterogeneous Information Networks

Xiangnan Kong, Bokai Cao, Philip S. Yu, Ying Ding and David J. Wild
arXiv 2013
[paper] [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, 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