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Kensaku MatsunamiPostdoctoral researcher, Purdue University

Email: kmatsun (at) purdue.edu

SNS: LinkedIn, Researchgate, Google Scholar, ORCID

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Job experience

2024–
Postdoctoral researcher, Purdue University (CryPTSys)
2021–2024
Postdoctoral researcher, Ghent University (BIOMATH & LPPAT & PharmaEng)
2021Postdoctoral researcher, The University of Tokyo (Sugiyama Lab)
2018–2021Research Fellow (DC1), Japan Society for the Promotion of Science
2016Internship, F. Hoffmann-La Roche, Ltd., Kaiseraugst, Switzerland

Education

2021Completion of Global Leader Program for Social Design and Management (GSDM)
2021Ph.D., Department of Chemical System Engineering, The University of Tokyo
2020–2021
Exchange student, Ghent University, Belgium
2018
Master of Engineering, Department of Chemical System Engineering, The University of Tokyo
2017Visiting Scholar, Rutgers University, United States
2016
Bachelor of Engineering, Department of Chemical System Engineering, The University of Tokyo

Awards


Grants

  • Kensaku Matsunami, "Development of design framework for solid drug product manufacturing processes" JSPS Grant-in-Aid for JSPS Fellows (DC1) JP18J22793 (FY2018–2020, JPY2,200,000)
  • Kensaku Matsunami, "Economic evaluation of continuous solid drug product manufacturing considering material properties" Research Abroad Grant Award, The New Pharmaceutical Technology and Engineering Foundation (2019, JPY500,000)
  • Kensaku Matsunami, Study Abroad Musha Shugyo Program, Graduate School of Engineering, The University of Tokyo (2016, JPY400,000)

Interests

Domains

  • Pharmaceutical manufacturing: e.g., solid drug products, continuous manufacturing, and granulation
  • Healthcare system: e.g., precision medicine, drug price reduction, and countermeasures for a pandemic
  • Others: e.g., sustainability and policy-making

Skills

  • Process systems engineering: e.g., process synthesis, economic assessment, optimization, surrogate modeling, and hybrid modeling
  • Powder engineering: e.g., population balance models (PBM)
  • Statistics and data science: e.g., design of experiments (DoE), multivariant analysis, and machine learning
  • Programming: e.g., MATLAB and Python

Others

  • Education: e.g., education in chemical engineering and educational system within a lab
  • Career planning: e.g., Ph.D. promotion, networking, and global cooperation
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