145th AES CONVENTION Presenters: Bozena Kostek

AES New York 2018 Presenter or Author

Bozena Kostek

Bozena Kostek

Primary Affiliation: Gdansk University of Technology - Gdansk, Poland
Secondary Affiliation: Audio Acoustics Lab.
AES Member Type: Fellow
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BOZENA KOSTEK holds professorship at the Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology (GUT), Poland. She is Head of the Audio Acoustics Laboratory. In 2013 Prof. Kostek has been elected as a member of the Polish Academy of Sciences. She received her M.Sc. degrees in Sound Engineering (1983) and Organization and Management (1986) from GUT. She also received postgraduate DEA degree (1988) from Toulouse University, France. In 1992 she supported her Ph.D. thesis with honors at GUT, and in 2000 her D.Sc. degree at the Research Systems Institute, Polish Academy of Sciences. In 2005 President of Poland granted her the title of Professor. She published over 500 scientific papers in journals and at international conferences. Under her guidance, 14 Ph.D. students supported their doctoral theses and she supervised over 240 M.Sc. and Eng. theses. She serves as the Editor-in-Chief of the Journal of the Audio Eng. Soc. since 2011. She was also the Editor-in-Chief of Archives of Acoustics (2007-2012). She was the recipient of many prestigious awards for research, including those of the Prime Minister of Poland (2000, 2014) for outstanding research achievements, prizes of the Polish Academy of Sciences and Ministry of Science and the Bachelor Cross of the Polonia Restituta Order (2011). She also received the Audio Eng. Soc. Fellowship Award in 2010, and the AES Citation Award in 2013. Her research activities are interdisciplinary, however the main research interests focus on music informatics, audio signal processing, human-computer interaction, cognitive bases of sound and vision processing, as well as psychophysiology of hearing and vision.

More Info: http://www.audioakustyka.org/

Session List

Oct 18: P08: Acoustics and Signal Processing
Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification–An Approach Based on Audio “Fingerprinting” (Author)

Oct 20: EB07: Posters: Applications in Audio
A Device for Measuring Auditory Brainstem Responses to Audio (Author)

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