"I wait for the lord, my soul waits, and in his word I put my hope. " Psalms 130.5
Shiyong Lu (吕世勇)
Big Data Research Laboratory
Wayne State University
Detroit, Michigan 48202, U.S.A.
Office: 3006 Maccabees
3105 Maccabees Bldg.
- CFP: IEEE Big Data Service 2017. Due 12/1/2017.
- CFP: IEEE Big Data Congress 2017. Due 1/19/2017.
- CFP: IEEE Big Data Conference 2016.
- Another paper is accepted by a workflow in Big Data Conference 2016, congratulations! Aravind Mohan, Mahdi Ebrahimi, Shiyong Lu, and Alexander Kotov, "Scheduling Big Data Workflows in the Cloud under Budget Constraints", in Proceedings of the IEEE Conference on Big Data, 2016, Washington DC, USA, 2016.
- A paper is accepted by Big Data Congress 2016, congratulations! Aravind Mohan, Mahdi Ebrahimi, Shiyong Lu, Alexander Kotov, "A NoSQL Data Model For Scalable Big Data Workflow Execution", IEEE International Congress on Big Data, San Francisco, USA, 2016.
- Congratulations to Andrey, who received a faculty position offer from Eastern Michigan University.
He will become an assisstat professor there from Fall 2016.
- Congratulations to Andrey, who got the Michigan Conrad Award in 2016. This award is given to only one student who published one best paper
in a previous year.
- Prospective Ph.D. students: we are always looking for excellent new PhD students. The best way to approach me is to look at http://www.dataview.org. You can sign up and then download the DATAVIEW code
and see if you can introduce some functionality to the system. I love to see a demo of your projects to demonstate your skills in Javascipt/AJAX, JAVA and SQL. System coding is critical in our lab.
The annual College of Enginnering magazine Exemplar publishes an article about
KDM (kdm.dataview.org) in Decembmer 2015.
- Milestone of KDM (> 600 users):
The KDM tool (http://kdm.dataview.org) is already being used by 600 registered users worldwide, representing over 200 universities and companies in more than 64 countries across 5 continents.
These users include professors, graduate and undergraduate students, entrepreneurs, big data architects, and engineers that have used KDM to generate hundreds of intelligent big data models in various domains, including healthcare, education, Internet of Things, stock market, retail and many others.
- We are looking for two excellent PhD students with full financial support to participate
Selected paper: A System Architecture for Running Big Data Workflows in the Cloud, IEEE SCC, 2014
Ian Foster, Yong Zhao, Ioan Raicu, and Shiyong Lu, "Cloud Computing and Grid Computing 360-Degree Compared", IEEE Grid Computing Environments, pp.1-10, in conjunction with IEEE/ACM Supercomputing, Austin, Texas, 2008. (2654 citations, one of the most cited articles in the area of cloud computing.)
Dr. Shiyong Lu is an
Associate Professor in the Department of Computer Science at Wayne State
Director of the Big Data Research Laboratory.
Our lab believes that mankind has entered the big data era, and with an extreme focus and deligence
we can produce high-impact research results or tools. Our lab has a rich and nurturing culture to cultivate
and train future professors - among graduates, six of them have joined other universities as professors.
Dr. Lu received his Ph.D. in computer science from State University of New York at
Stony Brook in 2002. Before that, he received his M.E. from the Institute of Computing Technology, Chinese Academy
of Sciences, Beijing
in 1996 and B.E. from the University
of Science and Technology of China at Hefei in 1993. Dr. Lu's
current research focuses on big data workflows and big data analytics. A big data workflow is the computerized modeling and automation of a process consisting of a set of computational tasks and their data interdependencies to process and analyze data of ever increasing in scale, complexity, and rate of acquisition.
He is an author of two books and over 120 articles published in various international conferences and journals, such as Data and Knowledge
Engineering (DKE), IEEE Transactions on Knowledge and Data Engineering (TKDE),
Transactions on Services Computing (TSC),
IEEE Transactions on Parallel and Distributed Systems (TPDS), IEEE Transactions
on Information Technology in Biomedicine (TITB), Theoretical Computer Science
(TCS), Information Systems (IS), etc. Dr. Lu's research is supported by NSF,
Department of Agriculture, Michigan
Tri-corridor, and Wayne
He is a Senior Member of the IEEE. Dr. Lu is an associate editor of International Journal of Big Data, and an editorial board member of International Journal of Big Data Intelligence (IJBDI).
Dr. Lu is currently involved in several big data workflow management projects, including NSF projects to
develop big data workflow technologies for bioinformatics, automobile industry, and civil engineering projects. Dr. Lu is the PI
of the DATAVIEW project, which focuses on the design and development of an online big data workflow system that supports
the modeling, execution, and monitoring of big data workflows in the cloud to support large-scale
big data analytics.
Located at midtown of Detroit, the Motor City,
Wayne State University is a
premier Carnegie Research Exensive University ranked
in the top 50 in R & D expenditures of all public universities by the
National Science Foundation. The university offered more than 350 academic
programs through 13 schools and colleges, to more than 32,000 students, ranked
as one of the top 3 universities in the state of Michigan. Department of
Obstetrics and Gynecology ranks #1 in the country in terms of total funding
from the National Institutes of Health. It is the home to the NIH Perinatology Research Branch, which is dedicated to
improving the quality of maternal-fetal health nationwide. The School of
Medicine at Wayne State University is the largest single-campus medical school,
and the third-largest overall, in the United States. The School of Library and
Information Science is ranked in the top 20 programs in the country. The
doctoral program of the College of Nursing was ranked 5th in the country.
Michigan has many attractive hot spots.
- Yue Opera
- Ping Pong
Datasets for Big Data
Slides for the class