Researcher's Profile

  • Associate Professor
  • Sadao OTA
  • Networked Biophotonics and Microfluidics
E-mail
sadaotasolab.rcast.u-tokyo.ac.jp
URL

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URL

Biography

March 2007 BS, Program for social innovation, Department of Engineering, The University of Tokyo (UTokyo)
October 2009 incomplete MS, Department of Life Sciences, Graduate School of Arts and Sciences, UTokyo
December 2013 Ph.D. from Mechanical Engineering Department at University of California Berkeley
February 2014 Assistant Professor, Chemistry Department, UTokyo(-2015.4)
October 2014 Sakigake Scholar, JST(-2015.4)
May 2015 Sakigake Scholar, JST(-2017.3)
April 2018 Associate Professor, RCAST, UTokyo
 

Research Interests

Trans-disciplinary science by networking biological measurements
With strong and widely spread expertise in optics, microfluidics, material synthesis, genomics, and engineering, we develop physical tools to probe biological structures and realize ways to network biological measurements for interrogating complex life systems. By fusing our strength with the power of information science, we tackle fundamental problems in biophysical and biological science, and explore the potential of such studies in healthcare industry. Ultimately, we aim at creating a machine that thinks by itself to discover something crazy with biology, physics and medicine outlooks.

Develop bioimaging/sensing, micro/nanofluidics, and information technologies
To these grand challenges and independently, we actively work on development of novel optical imaging, functional micro/nanofluidics, and information techniques, and their integrated modalities. Along such scientific explorations, new technologies continually emerge and may spin out to create industrial activities with further excitement.  

Welcome applicants who are interested to study experimental optics, microfluidics, biophysics, information- and bio-technologies, and/or to create values by combining these disconnected technologies.

Keywords

Optical Imaging, Microfluidics, Network Engineering, Biomolecular sensing, genetics, machine learning

Edudational Systems

  • Department of Advanced Interdisciplinary Studies, Graduate School of Engineering

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