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Zenas Chao has always been fascinated by the human mind, and curious about the development of machines with human-like intelligence, and the origins of free will, and consciousness. After graduating from college in Taiwan with a dual B.S. in Life Science and Chemistry, he attended Georgia Institute of Technology in the United States to study Biomedical Engineering. For his Ph.D., he grew neurons in petri dishes and connected them to robots demonstrating that a machine with an artificial organic brain can learn purposeful behavior. After graduation, he moved to Japan and held positions at the RIKEN Brain Science Institute (RIKEN-BSI) as a Research Scientist, the National Institute for Physiological Sciences (NIPS) as an Assistant Professor, and Kyoto University as a Junior Associate Professor, to study how to decode brain signals from behaving humans and monkeys and enable the control of robots and computers by the brain. In September 2019 he joined the International Research Center for Neurointelligence (IRCN) at the University of Tokyo as a Project Associate Professor, using his research experience in silico, in vitro, and in vivo, to search for evidence of predictive coding, a framework many consider a “grand unified theory of cognition”.



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

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




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

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

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

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 

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

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) 

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 

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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