[Iefac.list] IISE QCRE and DAIS Joint Webinar -- Dr. Kaibo Liu -- Nov. 17, 12 pm -1 pm, EST.

[Xiaolei Fang]

*Institute of Industrial and Systems Engineers*

*Quality Control & Reliability Engineering (QCRE) Division*

*and *

*Data Analytics and Information Systems (DAIS) Division*

*2022-2023 Webinar Series*

IISE Quality Control & Reliability Engineering (QCRE) division and Data 
Analytics and Information Systems (DAIS) Division would like to invite 
you to attend our webinar on Thursday, November 17, 12 p.m.-1 p.m., 
Eastern Time.

*Webinar 
Registration:*https://us06web.zoom.us/webinar/register/WN_jsAD4nJpR_i2oD-fIS9yZQ 
<https://us06web.zoom.us/webinar/register/WN_jsAD4nJpR_i2oD-fIS9yZQ>

*Time:*Nov. 17, Thursday, 12-1 p.m., Eastern Time.

Click to add this event to your***Google calendar* 
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*Title: Online monitoring of big data streams --- roadmap and recent 
advances*

*Presenter:* Dr. Kaibo Liu, Associate Professor, Department of 
Industrial and Systems Engineering, UW-Madison

*Abstract**:*The rapid advancements of internet of things (IoT) 
technology and cyber-physical infrastructure have resulted in a 
temporally and spatially dense data-rich environment, which provides 
unprecedented opportunities for performance improvement in various 
complex systems. Meanwhile, it also raises new research challenges on 
process monitoring, such as heterogeneous data formats, high-dimensional 
and big data structures, inherent complexity of the target systems, and 
potential lack of complete a priori knowledge. In this talk, an overview 
of the research roadmap and recent advances in online monitoring of big 
data streams conducted by Prof. Liu’s group will be provided. Several 
research works will be discussed in detail to elaborate the needs and 
research evolution of developing data science and multidisciplinary 
analytics methods for effective process monitoring, dynamic sampling and 
quality improvement in industrial applications tailored to the 
characteristics of Big Data.

*Biography*: Dr. Kaibo Liu is an associate professor at the department 
of Industrial and Systems Engineering, University of Wisconsin-Madison, 
and is also the associate director of UW-Madison IoT systems research 
center. He received the B.S. degree in industrial engineering from the 
HKUST, the M.S. degree in statistics and the Ph.D. degree in industrial 
engineering from the Georgia Institute of Technology. Dr. Kaibo Liu’s 
research is system informatics and industrial big data analytics, with 
an emphasis on the data fusion approach for real-time system modeling, 
monitoring, diagnosis, prognostics, and decision making. His research 
has been successfully funded by NSF, ONR, AFOSR, DOE, US ARMY CORPS OF 
ENGINEERS, and Industry. He is the recipient of three prestigious early 
career awards, including 2019 Outstanding Young Manufacturing Engineer 
Award by SME, 2019 Feigenbaum Medal Award by ASQ, and 2019 Dr. Hamed K. 
Eldin Outstanding Early Career IE in Academia Award by IISE, and also 
the winner of the Innovations in Education Award from IISE in 2020 and 
the Award for Technical Innovation in Industrial Engineering from IISE 
in 2021. He is currently serving as an associate editor of IEEE T-ASE, 
and the department editor of IISE Transactions on Data Science, Quality 
and Reliability.

---------------------------------------------------------

QCRE and DAIS Webinar Committee Members

Dr. Xiaowei Yue, xwy at vt.edu <mailto:xwy at vt.edu>

Assistant Professor, Grado Department of Industrial and Systems 
Engineering, Virginia Tech (DAIS)

Dr. Xiao Liu, xl027 at uark.edu <mailto:xl027 at uark.edu>

Assistant Professor, Department of Industrial Engineering, University of 
Arkansas (DAIS)

Dr. Na Zou, nzou1 at tamu.edu <mailto:nzou1 at tamu.edu>

Assistant Professor, Department of Engineering Technology & Industrial 
Distribution, Texas A&M University (QCRE)

Dr. Xiaolei Fang, xfang8 at ncsu.edu <mailto:xfang8 at ncsu.edu>

Assistant Professor, Edward P. Fitts Department of Industrial and 
Systems Engineering, North Carolina State University (QCRE)

-- 

Assistant Professor
Edward P. Fitts Department of Industrial and Systems Engineering
North Carolina State University

/Member, IISE Quality Control and Reliability Engineering/
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