Tuesday
April 4, 2017
Opening
Remarks: 9:00AM
Keynote
Address: 9:30AM
Coffee
Break: 10:40AM
Speaker:
Dr. Armin R. Mikler, PhD
Department of Computer Science in Engineering
Center for Computational Epidemiology and
Response Analysis
University of North Texas
Title:
RE-PLAN:
A Computational Framework for Response
Plan Design and Analysis
Abstract:
Emergencies stemming from the accidental
or deliberate release of harmful biochemical
substances demand timely response to
minimize potential harm to affected
populations. Therefore, local governments
are required to maintain solid, functional
plans for receiving medical countermeasures
(MCMs) from the Strategic National Stockpile
(SNS) and providing them to populations
in need within short, federally-mandated
timeframes.
Determining
optimal placement of ad-hoc clinics
purposed for the distribution of MCMs
to target populations requires the
integration of data representing geographic,
demographic, and transportation characteristics.
Therefore, the design and analysis
of response plans represent a complex
task necessitating the availability
of computational tools. To this end,
the RE-PLAN Framework has been developed
to facilitate data driven response
plan design and analysis while streamlining
the planning process. This research
has been supported by the National
Institutes of Health (NIH 1R01LM011647-01
and NIH 1R15LM010804-01).
This
talk will provide the highlights of
RE-PLAN, a computational framework
for placing facilities based on different
optimization criteria. Further, computational
methods to address plan limitations
and access disparities resulting from
specific demographic characteristics
such as the distribution vulnerabilities
in the population will be explored.
Time permitting, the presentation
will conclude with a demonstration
of response plan development using
the RE-PLAN system.
Biography:
In 1997, Professor Mikler joined the Department
of Computer Science at the University of
North Texas with a PhD from Iowa State University.
With the help of four courageous undergraduate
students, he established the Network Research
Laboratory (NRL), and with it, UNT's first
Beowulf Cluster to facilitate complex simulations
in support of the group's research on Computer
Network Protocols and Distributed Systems.
In addition to the inaugural group of students,
who completed their MS theses under Dr.
Mikler's guidance, the laboratory attracted
many graduate students with interest in
experimental design of protocols and algorithms
for large distributed computing infrastructures.
In 2004, Dr. Mikler started to gradually
move into a new field of research, which
was motivated by the need to facilitate
advances in the field of Public Health and
Epidemiology through computational methods.
He established the Computational Epidemiology
Research Laboratory (CERL) with focus on
the development of computational methodology
to model and simulate the spread of diseases
and the design and analysis of bio-emergency
response plans. Together with colleagues
in Biology and Geography, Dr. Mikler established
the truly interdisciplinary Center for Computational
Epidemiology and Response Analysis (CeCERA)
after receiving federal funds from the US
Department of Health and Human Services.
Today, CeCERA is the home of over 15 PhD
students who are conducting research in
a variety of areas related to Computational
Epidemiology, Ecology, Social Network Analysis,
and High Performance Computing under Dr.
Mikler's mentorship. Recent graduates of
his research group are using their expertise
in Computational Epidemiology as faculty
members at different universities and as
researchers at National Laboratories. Dr.
Mikler's research on response plan design
and analysis is supported by the Texas Department
of State Health Services (DSHS), the National
Science Foundation (NSF), and the National
Institutes of Health (NIH). He has supervised
over 30 PhD and MS theses and has published
over 70 research articles related to a range
of topics, including distributed systems,
networking, computational epidemiology,
and response plan design and analysis.
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