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SHORT BIO

Zenas Chao has a deep fascination with the human mind and the development of machines that mimic human intelligence. He earned B.S. degrees in Life Science and Chemistry in Taiwan before pursuing Biomedical Engineering at Georgia Institute of Technology, USA. During his Ph.D., he grew neurons in petri dishes and interfaced them with robots, demonstrating that machines equipped with an artificial organic brain can learn purposeful behaviors. Subsequently, he relocated to Japan, where he worked as a Research Scientist at the RIKEN Brain Science Institute, an Assistant Professor at the National Institute for Physiological Sciences, and a Junior Associate Professor at Kyoto University. His work in Japan focused on decoding brain signals from humans and monkeys to facilitate brain-controlled robots and computers. In 2019, Chao joined the International Research Center for Neurointelligence (IRCN) at the University of Tokyo. Here, he applies his research experience in silico, in vitro, and in vivo, to explore neural implementations of predictive coding, which is considered by many as a grand unified theory of cognition, and to investigate the neural mechanisms underlying creativity, a pivotal component of human intelligence.

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Brain

EDUCATION

PhD: Biomedical Engineering (2001-2007) 
Georgia Institute of Technology (joint program with Emory University), USA 

  • Thesis: “Toward the neurocomputer: goal-directed learning in embodied cultured networks” 

  • Advisor: Steve M. Potter

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Dual BS: Life Science / Chemistry (1994-1998)
National Tsing Hua University (NTHU), Taiwan

Brain

RESEARCH

EXPERIENCE

Associate Professor (2019-present)

International Research Center for Neurointelligence (IRCN), The University of Tokyo, Japan

  • Large-scale brain networks for predictive-coding signals

  • Predictive-coding signals in schizophrenic brain

  • Large-scale brain networks for creative problem solving

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Junior Associate Professor / Senior Lecturer (2016-2019)
Department of Neuroscience, Kyoto University, Japan
Center for Medical Education, Kyoto University, Japan

  • Large-scale brain networks for statistical learning 

  • Cortical network dynamics in major depressive disorder (MDD)

  • Corticomuscular network reorganization after neuronal injuries

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Assistant Professor (2016)
Department of Neuroscience, Kyoto University, Japan

  • Large-scale brain network reorganization after neuronal injuries

  • Nonhuman primate (NHP) model of Parkinson’s disease

  • Sensorimotor integration for muscle controls

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Assistant Professor (2015-2016)
Department of Developmental Physiology, National Institute for Physiological Sciences (NIPS), Japan 

  • Cortical network reorganization during functional recovery from spinal cord injuries

  • Big data analysis on simultaneous functional magnetic resonance imaging (fMRI) and electrocorticography (ECoG) signals 

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Research Scientist (2010-2015)
Laboratory for Adaptive Intelligence, RIKEN Brain Science Institute (RIKEN-BSI), Japan

  • Large-scale neurocognitive networks for perception, cognition, and consciousness in non-human primates

  • Data-mining for high-volume high-dimensional ECoG data

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Research Scientist (2008-2010)
Interactive Brain Communication Unit, RIKEN BSI-TOYOTA Collaboration Center (RIKEN-BTCC), Japan

  • ECoG-based brain-machine interfaces (BMIs) for non-human primates 

  • Decoding of high-level cognitive functions in human near-infrared spectroscopy (NIRS) 

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Graduate Research Assistant (2001-2007)
Laboratory for Neuroengineering, Department of Biomedical Engineering, Georgia Institute of Technology, USA

  • Network plasticity in cultured neurons with multi-electrode arrays (MEAs)

  • Embodied cultured networks for robot controls

  • Biologically-realistic network modeling 

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Research Assistant (2000-2001) 
Neuroscience Division, Institute of Biomedical Sciences (IBMS), Academia Sinica, Taiwan

  • fMRI and electrophysiology study of nociceptive responses in rats

  • Software development for clinical fMRI data analyses

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