Dongxiao Zhu is currently an Associate Professor at Department of Computer Science, Wayne State University. He received his Ph.D. from University of Michigan, Masters from Peking University and Bachelor from Shandong Univeristy.
His current primary research interests are machine leanring and data
science with applications to learning from big data in health
informatics, bioinformatics, natural language processing and multimedia. Dr. Zhu has published over 50
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.
Selected Peer-Reviewed Research Papers:
Li, X, Zhu, D, Dong, M, Nezhad, MZ and Levy, P (2017) SDT:
A Tree Method for Detecting Patient Subgroups with Personalized Risk
Factors. In the proceedings of 2017 American Medical Information
Association (AMIA) Summit on Clinical Research Informatics, San Francisco, March 2017.
a Bioconductor package to estimate correlation between two
variables with replicates
GeneNT: a R package to estimate
co-expression gene networks
a GUI system for transcriptoime assembly and quantification
using RNA-Seq (A popular sotware in its field: 4000+ downloads, used by researchers from all over the world and cited by papers published in Nature Genetics, PNAS, Genome Research etc.)
a GUI system for Topological Enrichment Analysis frameworK
dSpliceType: a Java-based tool to detect various types of differential splicing events using RNA-Seq
Selected Book Chapters (group members are in bold face):
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 7825 Machine Learning. Fall 2014, Fall 2015, Fall 2016
CSC 6580 Design and Analysis of Algorithms. Winter 2015, Winter 2016, Winter 2017
CSC 5825 Intro. to Machine Learning and Applications. Winter 2017
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,