IEEE Signal Processing Society & EMBS
Meeting Date: August 29, 2019
Time: 6:00 PM Networking; 6:30 PM Presentation
Speaker: Distinguished Lecturer Dr. Tao Zhang
Location: San Diego
RSVP: requested, through website
Event Details: IEEE vTools
With resurgence of AI and machine learning, sensor miniaturization and increased wireless connectivity, ear-level devices are going through a major revolution transforming themselves from hearing devices into multipurpose hearing enhancement and health and wellness monitoring devices. In this talk, I will present examples of such transformation in the areas of hearing enhancement, health and wellness monitoring and hand-free user experience. In the process, I will highlight how AI and machine learning, miniaturized sensors and wireless connectivity are enabling and accelerating the transformation. In addition, I will discuss practical challenges for the transformation today. Finally, I will share an outlook on future directions and opportunities.
Dr. Tao Zhang received his B.S. degree in physics from Nanjing University, Nanjing, China in 1986, M.S. degree in electrical engineering from Peking University, Beijing, China in 1989, and Ph.D. degree in speech and hearing science from the Ohio-State University, Columbus, OH, USA in 1995. He joined the Advanced Research Department at Starkey Laboratories, Inc. as a Sr. Research Scientist in 2001, managed the DSP department from 2004 to 2008 and the Signal Processing Research Department from 2008 to 2019. Since 2019, he has been Director of the Algorithms (AI, ML and Signal Processing) Department at Starkey Hearing Technologies, a global leader in providing innovative hearing technologies. He has received many prestigious awards including Inventor of the Year Award, the Mount Rainier Best Research Team Award, the Most Valuable Idea Award, the Outstanding Technical Leadership Award and the Engineering Service Award at Starkey.
He is a senior member of IEEE and the Signal Processing Society and the Engineering in Medicine and Biology Society. He serves on the IEEE AASP Technical Committee, the industrial relationship committee and the IEEE ComSoc North America Region Board. He is an IEEE SPS Distinguished Industry Speaker and the Chair of IEEE Twin-cities Signal Processing and Communication Chapter.
His current research interests include audio, acoustic, speech signal processing and machine learning; multimodal signal processing and machine learning for hearing enhancement, health and wellness monitoring; psychoacoustics, room and ear canal acoustics; ultra-low power real-time embedded system design and device-phone-cloud ecosystem design. He has authored and coauthored 120+ presentations and publications, received 23 approved patents and had additional 30+ patents pending.