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Tutorial Sessions/Invited Talks
All tutorials and invited talks are free to registered
conference attendees of all conferences held at
WOLDCOMP'15. Those who are interested in attending one
or more of the tutorials are to sign up on site at the
conference registration desk in Las Vegas. A complete &
current list of WORLDCOMP Tutorials
can be found
here.
In addition to tutorials at other conferences,
DMIN'15 aims at providing a set of tutorials dedicated
to Data Mining topics. The 2007 key tutorial was given
by Prof. Eamonn Keogh on Time Series Clustering. The
2008 key tutorial was presented by Mikhail Golovnya
(Senior Scientist, Salford Systems, USA) on Advanced
Data Mining Methodologies. DMIN'09 provided four
tutorials presented by Prof. Nitesh V. Chawla on Data
Mining with Sensitivity to Rare Events and Class
Imbalance, Prof. Asim Roy on Autonomous Machine Learning,
Dan Steinberg (CEO of Salford Systems) on Advanced Data
Mining Methodologies, and Peter Geczy on Emerging
Human-Web Interaction Research. DMIN'10 hosted a
tutorial presented by Prof. Vladimir Cherkassky on
Advanced Methodologies for Learning with Sparse Data. He
was a keynote speaker as well (Predictive Data Modeling
and the Nature of Scientific Discovery). In 2011, Gary
M. Weiss (Fordham University, USA) presented a tutorial
on Smart Phone-Based Sensor Data Mining. Michael Mahoney
(Stanford University, USA) gave a tutorial on Geometric
Tools for Identifying Structure in Large Social and
Information Networks. DMIN'12 hosted a talk given by
Sofus A. Macskassy
(Univ. of Southern California, USA) on Mining
Social Media: The Importance of Combining Network and
Content as well as a talk given by Haym Hirsh (Rutgers
University, USA): Getting the Most Bang for Your Buck:
The Efficient Use of Crowdsourced Labor for Data
Annotation. Professor Hirsh was a WORLDCOMP keynote
speaker, too.
In addition, we hosted tutorials
and invited talks held by Peter Geczy on Web Mining,
Data Mining and Privacy: Water and Fire?,
and Data Mining in Organizations. DMIN'13 hosted the
following tutorials:
EXTENSIONS
and APPLICATIONS of UNIVERSUM LEARNING
presented by
Vladimir
Cherkassky (Dept. Electrical & Computer Eng.,
University of Minnesota,
Minneapolis, USA),
Visualization
& Data Mining for High Dimensional Datasets
presented by Alfred
Inselberg, (School of Mathematical Sciences, Tel
Aviv University, Tel
Aviv,
Israel)
as well as invited talks: Big Data = Big Challenges?
given by Peter Geczy (National Institute of Advanced Industrial
Science and Technology (AIST), Japan)
and The Problem
of Induction: When Karl Popper meets Big Data
given by Vladimir Cherkassky.
DMIN' 15 will host the following
tutorials/invited talks (as of July 1, 2015):
Invited Talks
|
Invited Talk A |
|
Speaker |
Peter Geczy
National Institute of Advanced Industrial
Science and Technology (AIST), Japan |
 |
|
Topic/Title |
Data Science: The
Road Ahead |
|
Date & Time |
Wednesday, July
29, 08:20 - 09:20 am |
|
Location |
Ballroom
1 |
|
Description |
Rise of data, its
diversity and complexity over the past several
years has been unprecedented. Data grows at an
estimated exponential rate with no deceleration
expected in the mid-term future. The current
trend in data increase is already significantly
affecting numerous areas of commercial, social
and scientific domains. Expansion of data
notably outpaces our contemporary technological
capacities to suitably process and manage it.
The rising discrepancy between the data
expansion and our technological means to cope
with it highlights the pressing need for
development of coordinated scientific approaches.
Data Science represents a novel
interdisciplinary endeavor to address these
issues. In order to succeed, however, it must
successfully encompass three core domains:
research, education and commercial applications.
We shall explore the essential interplays
between these core domains and promising avenues
ahead. |
|
Short Bio |
Dr. Peter Geczy
holds a senior position at the National
Institute of Advanced Industrial Science and
Technology (AIST). His recent research interests
are in information technology intelligence. This
multidisciplinary research encompasses
development and exploration of future and
cutting-edge information technologies. It also
examines their impacts on societies,
organizations and individuals. Such
interdisciplinary scientific interests have led
him across domains of technology management and
innovation, data science, service science,
knowledge management, business intelligence,
computational intelligence, and social
intelligence. Dr. Geczy received several awards
in recognition of his accomplishments. He has
been serving on various professional boards and
committees, and has been a distinguished speaker
in academia and industry. He is a senior member
of IEEE and has been an active member of INFORMS
and INNS. |
|
Invited Talk B |
|
Speaker |
Diego Galar,
Division of Operation and Maintenance
Engineering,
Luleå University of Technology, 971 87 Lulea,
Sweden |
 |
|
Topic/Title |
Data Mining for RUL estimation of
complex assets |
|
Date & Time |
Monday, July 27, 3:20 - 04:00pm
|
|
Location |
Ballroom 1 |
|
Description |
Assets necessarily suffer
wear and tear during operation. Prognostics
can assess the current health of a system
and predict its remaining useful life (RUL)
based on features captureing the gradual
degradation of its operational capabilities.
As there are many prognostic techniques,
usage must be attuned to particular
applications. Indeed the estimation of RUL
for complex systems like aircrafts is a real
challenge due to the huge amount of data
involved in the process. This information is
increasing exponentially collected from
disparate data sources and with different
nature and granularity, therefore there is a
real need of context engines to establish
meaningful data links for further
explotation and exploration. The
talk addresses the process of data
aggregation and mining into a contextual
awareness model to get RUL values within
logical confidence intervals so that the
life cycle of assets can be managed and
optimised.
|
|
Short Bio |
Prof. Diego Galar holds a M.Sc. in
Telecommunications and a PhD degree in Design
and Manufacturing from the University of
Saragossa. He has been Professor in several
universities, including the University of
Saragossa or the European University of Madrid,
researcher in the Department of Design and
Manufacturing Engineering in the University of
Saragossa, researcher also in I3A, Institute for
engineering research in Aragon, director of
academic innovation and subsequently
pro-vice-chancellor. He has authored more than
hundred journal and conference papers, books and
technical reports in the field of maintenance,
working also as member of editorial boards,
scientific committees and chairing international
journals and conferences. In industry, he has
been technological director and CBM manager of
international companies, and actively
participated in national and international
committees for standardization and R&D in the
topics of reliability and maintenance.
Currently, he is Professor of Condition
Monitoring in the Division of Operation and
Maintenance Engineering at LTU, Luleå University
of Technology, where he is coordinating several
EU-FP7 projects related to different maintenance
aspects and is also involved in the SKF UTC
centre located in Lulea focused in SMART
bearings. In the international arena, he has
been visiting Professor in the Polytechnic of
Braganza (Portugal) and NIU (USA), currently
University of Valencia, University of Sunderland
(UK), University of Maryland (USA).
|
Tutorials
|
Tutorial A |
|
Speaker |
Diego Galar,
Division of Operation and Maintenance
Engineering,
Luleå University of Technology, 971 87 Lulea,
Sweden |
|
|
Topic/Title |
eMaintenance: Knowledge Discovery in asset data
by the means of data mining |
|
Date & Time |
Tuesday July 28,
2015 (06:00pm - estimated duration: about 2+
hours) |
|
Location |
Ballroom 1 |
|
Description |
Assets are
composed by multiple complex systems. Each
system is built with components which, over
time, may fail. When a component does fail, it
is difficult to identify it because the effects
or problems that the failure has on the system
are often neither obvious in terms of their
source nor unique. These problems have been
historically solved by experienced personnel
with in-depth training and experience. Typically,
these experts used available information
recorded in a log. Looking through the log, they
used their accumulated expertise to link
incidents to the problems that may be causing
them. Indeed the complexity of the assets as
systems of systems has shifted the diagnosis,
prognosis and other maintenance services from
physics based to data driven. Moreover, the data
collected are often dispersed across independent
systems that are difficult to access, fuse and
mine due to disparate nature and granularity. If
the data from these independent systems are
combined into a common correlated data source,
this new set of information could add value to
the individual data sources by the means of data
mining.
The tutorial is recommended for researchers and
practitioners who are interested in knowledge
extraction from asset data, no matter the
nature, the size or other properties. During the
tutorial the attendees will have the opportunity
to see the different data types with disparate
nature and granularity present in asset
management with examples of systems which
collect and record this data. Integration of the
asset data with common taxonomies will be also
presented in a simple way to show the
possibilities offered by properly prepared data
in the needful data mining process.
The way of presenting the state of the art of
eMaintenance will be as a case oriented tutorial
where success stories from different sectors
like transportation (aircraft or railway) and
process industry will be presented. |
|
Short Bio |
Prof. Diego Galar holds a M.Sc. in
Telecommunications and a PhD degree in Design
and Manufacturing from the University of
Saragossa. He has been Professor in several
universities, including the University of
Saragossa or the European University of Madrid,
researcher in the Department of Design and
Manufacturing Engineering in the University of
Saragossa, researcher also in I3A, Institute for
engineering research in Aragon, director of
academic innovation and subsequently
pro-vice-chancellor. He has authored more than
hundred journal and conference papers, books and
technical reports in the field of maintenance,
working also as member of editorial boards,
scientific committees and chairing international
journals and conferences. In industry, he has
been technological director and CBM manager of
international companies, and actively
participated in national and international
committees for standardization and R&D in the
topics of reliability and maintenance.
Currently, he is Professor of Condition
Monitoring in the Division of Operation and
Maintenance Engineering at LTU, Luleå University
of Technology, where he is coordinating several
EU-FP7 projects related to different maintenance
aspects and is also involved in the SKF UTC
centre located in Lulea focused in SMART
bearings. In the international arena, he has
been visiting Professor in the Polytechnic of
Braganza (Portugal) and NIU (USA), currently
University of Valencia, University of Sunderland
(UK), University of Maryland (USA).
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