Dongxiao Zhu is currently an Associate Professor at Department of Computer Science, Wayne State University. He received the B.S. degree from Shandong University (1996), the M.S. degree from Peking University (1999) and the Ph.D. degree from University of Michigan (2006).
Dongxiao Zhu's recent research interests are in machine learning and data
science with applications to health informatics, natural
language processing, medical imaging and recommender systems. Dr. Zhu is the Director of Machine
Learning and Predictive Analytics (MLPA) Lab and the Director of Computer Science
Graduate Program at Wayne State University. He has published over 70
peer-reviewed publications and numerous book chapters and he served on
several editorial boards of scientific journals. Dr. Zhu's research
has been supported by NIH, NSF and private agencies
and he has served on multiple NIH and NSF grant review panels. Dr. Zhu
has advised numerous students at undergraduate, graduate and
postdoctoral levels and his teaching interest lies in programming language, data
structures and algorithms, machine learning and data science.
Promoting a Healthier Urban Community: Prioritization of Risk Factors
for the Prevention and Treatment of Pediatric Obesity. 09/01/2016-08/31/2019. (co-Principal Investigator)
INT: Autonomous Battery Operating System (ABOS): An Adaptive and
Comprehensive Approach to Efficient, Safe, and Secure Battery System
Management. 09/01/2017-08/31/2021. (Senior Personnel)
NSF/CCF: EAGER: A novel algorithmic framework for discovering
subnetworks from big biological data. 08/15/2014-08/14/2017. (Principal
NIH/NLM: R21.A new informatics paradigm for reconstructing signaling
pathways in human disease. 09/2009 – 08/2012. (Principal Investigator)
NIH/NCI: R01. Analysis of Epstain-Barr virus type III latency on cellular miRNA gene expression. (co-Investigator)
NSF/CCF: CPATH: A verification based learning model that enriches CS and related undergraduate programs. (co-Principal Investigator)
Current Students Whose Research under My Supervision:
Lu Wang (CS Ph.D. candidate)
Xiangrui Li (CS Ph.D. candidate)
Deng Pan (CS Ph.D. candidate)
Xin Li (CS Ph.D. candidate)
Yao Qiang (CS Ph.D. pre-candidate)
Chengyin Li (CS Ph.D. pre-candidate)
Najibesadat Sadatijafarkalaei (CS Master thesis student, ISE Ph.D. student)
Bioinformatics, Briefings in Bioinformatics, Nucleic Acids Research, Genome
Biology, Genome Medicine, BMC Genomics, BMC Bioinformatics, BMC Systems
Biology, Biometrics, PLoS Genetics, PLoS ONE, Biology Direct, IEEE transaction on Fuzzy
Systems, IEEE transaction on Computational Biology and
Bioinformatics, IEEE Signal Processing Letters, IEEE
transaction on Computers, EURASIP
Computational Biology and Bioinformatics, EURASIP
Bioinformatics and Sysmtems Biology, IET Systems
Biology, Physics Review, Statistics in Medicine, Communications in Statistics,
Classroom Teaching (Computer Science Department at Wayne State University):
CSC 8860 Seminar Topics in Computer Vision and Pattern Recognition. Fall 2017
CSC 7825 Machine Learning. Fall 2014, Fall 2015, Fall 2016, Winter 2019
CSC 6580 Design and Analysis of Algorithms. Winter 2015, Winter 2016, Winter 2017
CSC 5825 Intro. to Machine Learning and Applications. Winter 2017, Fall 2017, Fall 2018, Fall 2019
CSC 5991 Special Topics in Comp. Sci. Fall 2012, Fall 2013, Winter 2014 , Winter 2015, Winter 2016
CSC 2110 Comp.
Sci. I (C++ Programming).
Fall 2011, Winter 2012, Winter 2013, Fall 2013
Classroom Teaching (Computer Science Department at University of New Orleans):
CSCI 6587 Adv.
Machine Learning in Bioinformatics. Fall 2009.
Principles of Image Processing. Fall
CSCI 1205 Intro.
Programming in C++. Spring 2009.
CSCI 2025 Data
Structure and Applications. Spring
2008, Spring 2009, Fall 2009, Spring 2010.
CSCI 6635 Pattern
Recognition. Fall 2008, Spring 2010,
Classroom Teaching (School of Science and Engineering at Chinese University of Hongkong, Shenzhen):
CSC 4008 Data Mining Techniques. Spring 2018.
CIE 6024 Selected Topics in Deep Learning. Spring 2018.