Signal Processing - September 2017 - 195

the Signal Analysis and Interpretation
Laboratory. His research concerns developing engineering techniques and systems for societal applications in human
health and well-being, focusing on affective signal processing, speech and language processing, and machine learning.
He received the Alfred E. Mann "In no vation in Engineering" Doctoral
Fellowship (2014-2016) and the Achievement Rewards for College Scientists
Award (2012-2016), served as a USC
Ming Hsieh Institute Scholar (2015-
2016), and was on winning teams of two
Interspeech Challenges (2012 and 2015).
He is a Member of the IEEE.
Chi-Chun Lee (cclee@ee.nthu.edu
.tw) received his B.S. and Ph.D. degrees in
electrical engineering from the University
of Southern California in 2007 and 2012,
respectively. He is an assistant professor in
the Electrical Engineering Department of
the National Tsing Hua University,
Taiwan. His research interests are in
human-centered behavioral signal processing and multimodal affective computing. He led a team winning the
Emotion Challenge in Interspeech 2009.
He coauthored a paper that won the Best
Paper Award at Interspeech 2010. He is a
member of Tau Beta Pi, Phi Kappa Phi,
and Eta Kappa Nu. He is a Member of the
IEEE and the International Speech and
Communication Association.
Theodora Chaspari (chaspari@usc
.edu) received her diploma in electrical
and computer engineering from the
National Technical University of Athens,
Greece, in 2010 and her master's and
Ph.D. degrees from the University of
Southern California (USC) in 2012 and
2017, respectively. Since 2010 she has
been a member of the Signal Analysis and
Interpretation Laboratory at USC. Her
research interests lie in the area of biomedical signal processing, speech analysis, and
behavioral signal processing. She is a
Graduate Student Member of the IEEE.
James Gibson (jjgibson@usc.edu)
received his B.S. degree (magna cum
laude) in electrical engineering from the
University of Miami, Florida, in 2010,
and his M.S. degree in electrical engineering from the University of Southern
California (USC), in 2012. He is currently
pursuing the Ph.D. degree in the Signal

Analysis and Interpretation Laboratory at
USC. His research interests focus on
human-centered signal processing and
machine learning in the context of mental
health and well-being domains. He is a
member of the IEEE Signal Processing
Society and Eta Kappa Nu. He was a
recipient of the USC Annenberg Fellowship, 2010-2012. He is a Graduate Student
Member of the IEEE.
Shrikanth Narayanan (shri@sipi
.usc.edu) received his M.S., engineer, and
Ph.D. degrees all in electrical engineering,
from the University of California, Los Angeles, in 1990, 1992, and 1995, respectively. He is the Niki and Max Nikias Chair
in Engineering at the University of Southern California, where he is a professor of
electrical engineering, computer science,
linguistics, psychology, neuroscience,
and pediatrics and the director of the Ming
Hsieh Institute and the Signal Analysis and
Interpretation Laboratory. He is a fellow of
the National Academy of Inventors,
Acoustical Society of America, International Speech Communication Association, and American Association for the
Advancement of Science. His research focuses on human-centered signal and information processing and modeling with
applications of direct societal relevance in
intelligence, defense, health, education and
the media arts. He is a Fellow of the IEEE.

References

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https://www http://www.drugabuse.gov/publications/drugfacts/nationwide-trends http://www.usc.edu http://www.forbes.com/sites/tjmccue/ https://www.nimh.nih https://www.nimh.nih.gov/health/statistics/prevalence/
Table of Contents for the Digital Edition of Signal Processing - September 2017
