IEEE Awards Booklet - 2020 - 25


IEEE Robotics and Automation Award

IEEE Frank Rosenblatt Award

Sponsored by the IEEE Robotics and Automation Society

Sponsored by the IEEE Computational Intelligence Society

Vijay Kumar

Xin Yao

For contributions to cooperative robotics;
networked mobile manipulation systems,
particularly unmanned aerial vehicles;
and leadership in robotics research,
policy, and education

For contributions to the advancement of
the theory and applications of computational intelligence

Considered one of the top roboticists of his generation, Vijay
Kumar's vision and technical accomplishments have shaped the
fields of cooperative and networked robotics and autonomous micro
aerial vehicles. He developed several novel capabilities for swarms of
ground and aerial vehicles ranging in size from micro to macro that
can move in formation, transport objects, and operate both indoors
and outdoors. Central to his work is the synthesis of decentralized
controllers that allow a group of robots to produce a desired global
behavior by coordinating only with their immediate neighbors. Kumar has also served as an advisor in the White House Office of Science and Technology Policy, which was instrumental in increasing
federal funding for robotics and cyber physical systems.
An IEEE Fellow and a member of the National Academy of
Engineering, Kumar is the Nemirovsky Family Dean with the
School of Engineering and Applied Science at University of
Pennsylvania, Philadelphia, PA, USA.

Impacting both the foundational and practical aspects of computational intelligence, Xin Yao's accomplishments in advancing
evolutionary computation and machine learning are making it
easier to solve complex optimization problems. His approaches
to fast evolutionary programming, in which he proposed a widely known mutation operator and an entirely new methodology
for theoretical analysis of evolutionary operators/algorithms,
have been applied to neural network structure learning, digital
filter design, and design of new materials. His work on stochastic ranking, where he introduced a novel approach to deal with
constraints in evolutionary optimization by balancing objectives
and penalty functions based on a new ranking method, has had
a major impact on solving constraint optimization problems in
electrical, chemical, mechanical, and aeronautical engineering.
An IEEE Fellow,Yao is a Chair Professor of Computer Science at
the Southern University of Science and Technology, Shenzhen, China.

IEEE Marie Sklodowska-Curie Award

IEEE Innovation in Societal Infrastructure Award

Sponsored by the IEEE Nuclear and Plasma Sciences Society

Sponsored by Hitachi, Ltd. and the IEEE Computer Society

Michael A. Lieberman

Masaru Kitsuregawa

For groundbreaking research and
sustained intellectual leadership in the
physics of low-temperature plasmas and
their application

For contributions to big data collection
and analytics of real-world problems
with advanced data engineering technologies

Michael A. Lieberman's advances in low-temperature plasma science have impacted integrated circuit fabrication, materials processing, and biomedicine. He developed and popularized global
model conservation laws, which are used to predict plasma density and floating potential and electron temperature of plasmas.This
was critical to the rapidly developing microelectronics industry
being able to meet the challenges of continuing to shrink device
size (Moore's Law). His work on pulsed plasmas is vital to the
semiconductor industry, where pulsing the plasma is a powerful
means of reducing surface charging damage during etching and
deposition. His series of field-defining papers on the dynamics
of radiofrequency-excited atmospheric pressure plasmas has had
important implications in plasma medicine applications.
An IEEE Fellow, Lieberman is a professor with the graduate
school in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley, CA, USA.

Masaru Kitsuregawa has led the development and deployment of
big data platforms on the environment and healthcare. Since the
early 1980s he has accumulated earth environmental data from
many real-time sensors. In 2019, his DIAS system grew to 35
petabytes, used by scientists and government agencies around
the world for applications such as weather modeling and disaster
management. DIAS provides satellite imagery, radar, and river water gauge data for real-time flood prediction and proactive dam
discharging. He is building the SFINCS big data platform, with
200 billion medical claims records from Japan. SFINCS enables
new discoveries on nationwide statistics for drug usage and timeseries analysis after operation. These discoveries are being used to
improve medical treatments and healthcare system efficiency.
An IEEE Fellow, Kitsuregawa is director general of the National Institute of Informatics and professor with the Institute of
Industrial Science at the University of Tokyo, Tokyo, Japan.



IEEE Awards Booklet - 2020

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