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Visiting researchers

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Tokyo Tech Emeritus Prof. Koichi MIKAMI

Research area

  • Asymmetric Synthesis 
  • Drug Design
  • Organofluorine
  • Organometalic
  • Material Design
  • Hydrogen Permeation
  • Fuel Cell

Research technology

  • Asymmetric Catalysis
  • Fluorinated Drug Design
  • Asymmetric Organofluorine
  • Asymmetric Reaction Design
  • Organometalic and/or Fluorinated Material
  • Ionic Liquids
  • AI-based Design

Chinnathan Areeprasert, D.Eng.
Visiting Associate Professor at Tokyo Tech

Associate Professor of Mechanical Engineering

Department of Mechanical Engineering,

Faculty of Engineering, Kasetsart University.

50 Ngam Wong Wan Rd., Chatuchak, Bangkok 10900, Thailand.

https://wbc-lab.com/

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Education:

  • Doctor of Engineering (2015)

    • Department of Environmental Science and Technology, Tokyo Institute of Technology

    • Dissertation: Solid Fuel Production from Paper Sludge Employing Hydrothermal Treatment and Its Co-combustion Performance with Coal

  • Master of Engineering (2013)

    • Department of Environmental Science and Technology, Tokyo Institute of Technology

  • Bachelor of Engineering (2011)

    • Department of Mechanical Engineering, Kasetsart University, Thailand

 

Research interests:

Hydrothermal Processing of Biomass; Thermochemical Conversion of Waste/Biomass; Waste Management; Hydrogen Production from Biomass Gasification

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Dr. Nopphon Keerativaoranan

Dr. Nopphon is a postdoctoral researcher and visiting researcher. His expertise lies in the research fields of machine learning and signal processing for educational technology, as well as his experience in developing MOOCs courses on the edX platform. His current research at Cross Lab focuses on learner style profiling in MOOCs for the development of personalized learning paths within specific disciplines. Additionally, he provides research support for graduate and undergraduate students in the education technology group at Cross Lab.

Previously, he served as a research assistant at the Intelligent Transportation Systems Laboratory (ITS Lab) at the National Electronics and Computer Technology (NECTEC), where he conducted research in data science and data visualization for real-time tracking of public transport in Bangkok, Thailand. He also worked at the Online Content Research and Development Section (OCRD) at the Tokyo Institute of Technology as a research and teaching assistant within OCRD's analytic team. His research and development activities there included data analysis of learners and course content using natural language processing (NLP) to assess the quality of edX MOOCs, and the development of automatic tools to support the Tokyo Tech MOOCs course development teams

Education:

  • D.E. in Global Engineering and Development, Environment and Society (Wireless Communication Engieeering), Tokyo Institute of Technology, 2020

  • M.S. in Computer Science and Engineering, Seoul National University, Korea, 2015

  • B.E. in Electrical and Computer Engineering, Thammasat University, Thailand, 2012

Dr. May Kristine Jonson CARLON (May)

Dr. Sasipa Boonyubol received a Dr. Eng degree in Chemical Science and Engineering at the Tokyo Institute of Technology (Tokyo Tech) in 2020. Her research was mainly focused on biofuel processing and biomass conversion and upgrading since her Bachelor’s degree. After her doctoral graduation, she worked in the Online Content Research and Development Section, Center for Innovative Teaching and Learning, Tokyo Tech. She was involved in not only creating various Tokyo Tech online courses, teaching assistant training but also conducted data analytics research on online education.

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Personalized Online Adaptive Learning System (POALS)

POALS is a web-based system designed to help learners succeed in online learning environments. To succeed in online learning environments where instructor support might be less compared to face-to-face instruction, learners must be trained to be autonomous by equipping them with metacognitive skills. However, teaching metacognition inevitably introduces cognitive strain, which can vary among individuals. Thus, we introduce adaptive learning to personalize each learning experience. We tap into the teachers as learning facilitators by creating an analytics dashboard to give implicit feedback to teachers that they can use to provide interventions if necessary. This research is supported by the Japan Society for the Promotion of Science (JSPS) via Grant-in-Aid for Scientific Research (B) grant (Kakenhi 20H01719) from April 2020 to March 2025. This serves as the bulk of May’s doctoral dissertation and postdoctoral research.

Research

  • Personalized Online Adaptive Learning System (POALS)

Education 

  • 2018 – 2021, Doctor of Philosophy, Global Engineering for Development, Environment and Society, Tokyo Institute of Technology (Tokyo, Japan)
    • Tokyo Tech Tsubame Scholarship for Doctoral Students (Special Scholarship)
  • 2016 – 2017, Master of Science in Computer Science, Georgia Institute of Technology (Atlanta, Georgia, USA - Online)
    • Specialization: Computational Perception and Robotics
  • 2002 – 2006, Bachelor of Science in Mathematics, University of the Philippines (Quezon City, Philippines)
    • Department of Science and Technology – Science Education Institute Merit Scholarship

Career

  • From May 2023, Technical Staff I, Social Value and Decision Making Lab, Center for Brain Science, RIKEN
  • April 2022 to present, Part-time Lecturer, Global Interdisciplinary Studies, Hosei University
  • February 2015 – May 2023, Software Engineer, Wisdom Incorporated
  • October 2022 – March 2023, Educational Specialist, Online Content Research and Development Section, Center for Innovative Teaching and Learning, Tokyo Institute of Technology
  • October 2021 – March 2023, Postdoctoral Researcher, Cross Laboratory, Department of Transdisciplinary Science and Engineering, School of Environment and Society, Tokyo Institute of Technology
  • December 2006 – June 2014, Quality Assurance, Canon Information Technologies Philippines, Inc.
    • ​April 2012 – June 2014, Principal Engineer
    • February 2012 – January 2013, Intracompany Assignee
    • April 2010 – March 2012, Senior Engineer
    • October 2008 – March 2010, Engineer
    • December 2006 – September 2008, Associate Engineer

Awards

  • Best Student Paper Award, IEEE Teaching, Assessment, and Learning in Engineering (TALE) Conference 2021
  • Excellent Presentation Award, Tokyo Tech Multidisciplinary International Student Workshop (MISW) 2019
  • Grace Hopper Celebration (GHC) for Women in Computing Student Scholarship 2019
  • Google Women Techmakers (WTM) Scholarship for Asia-Pacific Region 2019

Cross Laboratory Access

东京工业大学 Jeffrey Cross 教授
📮152-8550

日本东京都目黑区大冈山 2-12-1 I4-19 

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