Miltiadis "Miltos" Alamaniotis is an assistant professor in the Department of Electrical and Computer
Engineering at the University of Texas at San Antonio (UTSA). Before joining UTSA, he worked as a
researcher at Purdue University in the US. He received his Diploma in Electrical and Computer
Engineering from the University of Thessaly, in 2005, and a master's and PhD Degree in Nuclear
Engineering with emphasis on Applied Artificial Intelligence from Purdue University in 2010 and 2012
respectively. His interdisciplinary research focuses on the development of intelligent systems and
machine learning approaches applied to intelligent energy systems, power grids, nuclear energy
systems, and nuclear safety to detect hidden radioactive materials. He has published over two hundred
(200) research papers in scientific journals, books and proceedings of international conferences, while
he is the author of 2 books. He has been invited to serve as an Associate Editor at the International
journal on Artificial Intelligence Tools and as a Program Chair at IEEE International Tools with Artificial
Intelligence 2018. He worked as an external researcher at Argonne National Laboratory (Illinois, USA)
from 2010 to 2012, and as a visiting researcher in the Energy and Power Systems team at Oak Ridge
National Laboratory (Tennessee, USA) in May 2016, and at the Nevada National Security Laboratory
(USA). He is a recipient of the Distinguished Graduate Award of the Department of Electrical
Engineering and Computer Engineering of the University of Thessaly in July 2017 and the Rector's Award
for Distinguished Research achievements at UTSA in April 2022.
"Preventing a new September 11: the role and solutions of Artificial Intelligence in Nuclear Security"
"The terrorist events of September 11 led to the redefinition of the
security architecture and its priorities for deterring terrorist acts.
Among the scenarios that emerged was the use of nuclear materials to carry out terrorist attacks with
wide-scale consequences. The recent developments in the field of Artificial Intelligence, among
many, find application in the treatment of challenges in the field of security of nuclear energy
systems and installations. Data generated by supervisory instruments - e.g. sensors – is
multiplying exponentially due to the increasing use of new information and
communication technologies, resulting from the sensitive nature of these systems.
The use of artificial intelligence techniques offers solutions for the development of high-definition and
high-speed data analysis related to the use, storage and transportation of nuclear materials. In this talk,
the role of artificial intelligence in upgrading the security architecture to prevent a new September 11
using radioactive and nuclear materials will be discussed. In addition, AI-based solutions and techniques
for the early detection and detection of nuclear threats will be presented, while societal concerns
arising from the improper use of artificial intelligence in the field of Nuclear Security will be analyzed."
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