Abstract
線上會議連結如下: https://asmeet.webex.com/asmeet-en/j.php?MTID=m5c448d02031cb2e2042cee855aba9893
會議號: 2520 745 7132
密碼: H29WpmR3Da7
Over the past three decades, significant advancements have occurred in fundamental neuroscience research and the development of next-generation neurotechnology. Among the pioneering innovations is the Brain-Computer Interface (BCI), which facilitates a direct interface between the user's brain and external devices. Despite the success of BCI technologies, their use has largely been confined to well-controlled laboratories. Our research team has committed to surmounting existing barriers to translate laboratory demonstrations into tangible, real-world BCI applications. This presentation will explore using EEG and BCI for cognitive-state monitoring, the science of learning, and enhancing aesthetic experiences.
會議號: 2520 745 7132
密碼: H29WpmR3Da7
Over the past three decades, significant advancements have occurred in fundamental neuroscience research and the development of next-generation neurotechnology. Among the pioneering innovations is the Brain-Computer Interface (BCI), which facilitates a direct interface between the user's brain and external devices. Despite the success of BCI technologies, their use has largely been confined to well-controlled laboratories. Our research team has committed to surmounting existing barriers to translate laboratory demonstrations into tangible, real-world BCI applications. This presentation will explore using EEG and BCI for cognitive-state monitoring, the science of learning, and enhancing aesthetic experiences.
Bio
Tzyy-Ping Jung is the Co-Director of the Center for Advanced Neurological Engineering, an Associate Director of the Swartz Center for Computational Neuroscience, and an Adjunct Professor of the Department of Bioengineering at the University of California San Diego, CA, USA. He is also an Adjunct Professor of the College of Education at National Tsing Hua University, and the Department of Electrical Engineering at National Chiao Tung University in Taiwan. Dr. Jung established transformative techniques for applying blind source separation to decompose multichannel EEG/MEG/ERP and fMRI data and was elevated to an IEEE Fellow for his contributions to blind source separation for biomedical applications in 2015. He is also a Fellow of Asia-Pacific Artificial Intelligence Association (AAIA). Dr. Jung’s research emphasis has been placed on the integration of cognitive science, computer science and engineering, neuroscience, bioengineering, and electrical engineering. Dr. Jung’s work is truly interdisciplinary and well-cited by peers (>43,000 total citations and h-index = 88, according to Google Scholar). He has published many well-cited articles in prestigious scientific journals such as Science, PNAS, PLoS Biology, and J. Neurosciences, engineering journals such as Proceedings of the IEEE, IEEE Trans Biomedical Engineering, and clinical journals such as Gerontology and JAMA Ophthalmology.