[ugrads] Wed 3/29 12:45pm Undergraduate Lunch Seminar: Aaron Luttman, National Nuclear Security Administration; plus 1:50pm research talk

Robert Ellis ellisr at iit.edu
Fri Mar 24 11:40:50 CDT 2017


Dear Undergraduates,

Next Wednesday is a valuable opportunity for undergraduates in Applied
Math, Physics, and Engineering -- especially Materials Engineering but not
excluding others -- to hear from Dr. Aaron Luttman about research
activities and opportunities (internships, graduate studies) at the
National Nuclear Security Administration.

Please complete the Google Form RSVP linked below.  All who RSVP will
receive a follow-up email with the room reservation for the 12:45pm
undergraduate lunch seminar.  The research talk following at 1:50pm in RE
104 is also below.

Thank you,
Robert Ellis

Google Form Lunch RSVP here
<https://docs.google.com/a/iit.edu/forms/d/e/1FAIpQLSdCXe7rSsDZilSfpkMimpTW23_OQ_TICMWD82MaSp-LGRvCtw/viewform?usp=sf_link#responses>

*Speaker:* Dr. Aaron Luttman, Manager, Diagnostic Research and Materials
Studies, Nevada National Security Site
*Title:*    Mathematical Methods and Modeling in the National Security
Sciences
*When:*  Mar 29, 2017 - 12:45pm to 1:45pm
*Where: *TBA (to be emailed to all who RSVP "Yes")

*Abstract*
While most people are familiar with many of the military aspects of
national security, the scientific enterprise in support of national
security is less well known. The National Nuclear Security Administration
(NNSA) is a semi-autonomous agency within the U.S. Department of Energy
that oversees the nation’s nuclear security science, from nuclear non- and
counter-proliferation technologies to nuclear emergency response (like the
Fukushima disaster in Japan) to the science of maintaining the U.S. nuclear
weapons stockpile. The NNSA supports a scientific enterprise of more than
50,000 scientists, technicians, and engineers, and, in this presentation,
the speaker will introduce some of the latest scientific developments that
are underway in support of U.S. nuclear security, including current
mathematical research associated with the chemistry and physics of dynamic
material studies, which involves explosively-driven experimentation in
material science. In addition to some actual mathematical case studies at
the cutting edge of nuclear security science, the speaker will discuss some
of the national policies that drive the science as well as how new
graduates in science, technology, engineering, and mathematics can get
involved in this research through internships and support for graduate
studies.

This work was authored by National Security Technologies, LLC, under
Contract No. DE-AC52-06NA25946 with the U.S. Department of Energy and
supported by the Site-Directed Research and Development Program.

*Speaker Bio*
Dr. Aaron Luttman began his professional career at a “dot-com” startup in
Minnesota, after receiving degrees in mathematics from Purdue University
and the University of Minnesota. After a detour to Belgium, Aaron returned
to the U.S. and earned his Ph.D. in Mathematics from the University of
Montana, where his research focused on using image processing techniques
for studying plant physiology. After 2 years as an assistant professor at
Bethany Lutheran College in Mankato, MN, and almost 4 years at Clarkson
University in Potsdam, NY, Aaron joined the Nevada National Security Site
(NNSS) in 2011 as a Senior Scientist. Since then, he has served as the
leader for the Signal Processing and Applied Mathematics team, as the North
Las Vegas representative to the NNSS Research & Development program, and as
a technical advisor to the NNSA Office of Defense Programs R&D (NA-113) at
DOE headquarters in Washington, D.C. He is now the manager of the
Diagnostic Research and Materials Studies group, a team of over 30
scientists and engineers developing next-generation diagnostic systems for
stockpile stewardship.


*Dr. Aaron Luttman Research talk*
Wed Mar 29th, 1:50pm-2:55pm, RE 104

*Title:* Quantifying Uncertainties in Inverse Problems: Meaning and
Usefulness of Error Bars in Large-Scale Inversion
*Abstract*
While the U.S. Department of Energy has moved to a scientific paradigm
driven by modeling and simulation – and in which experimentation is
motivated primarily by code validation – there is still much to be learned
by analyzing data directly and extracting information from experimental
data by solving inverse problems. In order to quantify the uncertainties
associated with the solutions, however, it is necessary to use statistical
approaches to formulating the inverse problems and to understand the nature
of the uncertainties for which such formulations can correctly account. In
this work we will present data from National Nuclear Security
Administration X-ray imaging experiments related to the stockpile
stewardship program, some inverse problems whose solutions inform the
evolution of our experiments and diagnostics systems, and the challenges
associated with the Bayesian formalisms used to assign error bars to the
information extracted. The discussion will include details of the
experiments themselves, where mathematical data analysts fit into the
experimental programs, the role of mathematical theory in development of
analysis techniques, and results demonstrating the efficacy of solving
statistical inverse problems to drive stockpile stewardship.

-- 
Robert B. Ellis, PhD
Assoc. Prof., IIT Applied Mathematics
10 W 32nd St, E1 208, Chicago, IL 60637
ellisr at iit.edu
http://math.iit.edu/~rellis
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