Keynote Speakers
Prof. Haizhou Li
IEEE Fellow
National University of Singapore, Singapore
Haizhou Li is a Presidential Chair Professor
and Associate Dean (Research) at the School of Data
Science, The Chinese University of Hong Kong,
Shenzhen, China. Dr. Li is also with the Department
of Electrical and Computer Engineering, National
University of Singapore (NUS), Singapore.
Dr. Li was the recipient of National Infocomm Awards
2002, Institution of Engineers Singapore (IES)
Prestigious Engineering Achievement Award 2013 and
2015, President's Technology Award 2013, and MTI
Innovation Activist Gold Award 2015 in Singapore. He
was named one of the two Nokia Visiting Professors
in 2009 by Nokia Foundation, IEEE Fellow in 2014 for
leadership in multilingual, speaker and language
recognition, ISCA Fellow in 2018 for contributions
to multilingual speech information processing, and
Bremen Excellence Chair Professor in 2019. Dr. Li is
a Fellow of Academy of Engineering Singapore.
Speech Title: Seeing to Hear Better
Abstract: Humans have a remarkable ability to
pay their auditory attention only to a sound source
of interest, that we call selective auditory
attention, in a multi-talker environment or a
Cocktail Party. However, signal processing approach
to speech separation and/or speaker extraction from
multi-talker speech remains a challenge for
machines. In this talk, we study the deep learning
solutions to monaural speech separation and speaker
extraction that enable selective auditory attention.
We review the findings from human audio-visual
speech perception to motivate the design of speech
perception algorithms. We introduce their
applications in speech enhancement, speaker
extraction, and speech recognition. We will also
discuss the computational auditory models, technical
challenges and the recent advances in the field.
Prof. De-Shuang Huang
IEEE Fellow
Tongji University, China
De-Shuang Huang is a Professor in Department
of Computer Science and Director of Institute of
Machine Learning and Systems Biology at Tongji
University, China. He is currently the Fellow of the
International Association of Pattern Recognition
(IAPR Fellow), Fellow of the IEEE (IEEE Fellow) and
Senior Member of the INNS, Bioinformatics and
Bioengineering Technical Committee Member of IEEE
CIS, Neural Networks Technical Committee Member of
IEEE CIS, the member of the INNS, Co-Chair of the
Big Data Analytics section within INNS, and
associated editors of IEEE/ACM Transactions on
Computational Biology & Bioinformatics, and Neural
Networks, etc. He founded the International
Conference on Intelligent Computing (ICIC) in 2005.
ICIC has since been successfully held annually with
him serving as General or Steering Committee Chair.
He also served as the 2015 International Joint
Conference on Neural Networks (IJCNN 2015) General
Chair, July 12-17, 2015, Killarney, Ireland, the
2014 11th IEEE Computational Intelligence in
Bioinformatics and Computational Biology Conference
(IEEE-CIBCBC) Program Committee Chair, May 21-24,
2014, Honolulu, USA. He has published over 470
papers in international journals, international
conferences proceedings, and book chapters.
Particularly, he has published over 230 SCI indexed
papers. His Google Scholar citation number is over
18300 times and H index 73. His main research
interest includes neural networks, pattern
recognition and bioinformatics.
Prof. Alexander Gammerman
Royal Holloway, University of London, UK
Professor Gammerman's current research
interest lies in machine learning and, in
particular, in the development of conformal
predictors -- a set of novel machine learning
techniques that guarantee the validity of
prediction. Areas in which these techniques have
been applied include medical diagnosis, drug design,
forensic science, proteomics, genomics, environment,
and information security. He has published about two
hundred research papers and several books on
computational learning and probabilistic inference.
Professor Gammerman is a Fellow of the Royal
Statistical Society and a Fellow of the Royal
Society of Arts. He chaired and participated in
organizing committees of many international
conferences and workshops on Machine Learning and
Bayesian methods in Europe, Russia and in the United
States. He was also a member of the editorial boards
of the Law, Probability and Risk journal (2002-2009)
and the Computer Journal (2003-2008). He has held
visiting and honorary professorships from several
universities in Europe and USA. Further details can
be found at
http://cml.rhul.ac.uk
