Experts

岡田 龍太郎/Ryotaro Okada

Ryotaro Okada

  • RESEARCH FELLOW

Assistant Professor, Department of Data Science, Musashino University

Areas of Expertise

  • Data science
  • artificial intelligence
  • sensory information processing
  • natural language processing
  • semantic and contextual processing
  • automatic composition

Research Program

Nudge Analysis and Generation Mechanisms Based on Responsible AI and the Development of Data Scientists for Their Social Implementation

Bio

Became assistant professor in the Department of Data Science at Musashino University in Tokyo in 2020 and concurrently has been a research fellow at GLOCOM, International University of Japan, since 2020. Is also a part-time lecturer at the University of Tsukuba. Completed course requirements for a doctorate in computer science at the Graduate School of Systems and Information Engineering, University of Tsukuba, in 2014, and obtained his doctoral degree in engineering from the university in 2019. Participated in the 2018 CEO Program of the Circular Economy Promotion Organization—a data scientist human resource development program—and was certified as a CEO Leader.


Select Publications

  • Ryotaro Okada, Takafumi Nakanishi, Yuichi Tanaka, Yutaka Ogasawara, Kazuhiro Ohashi, “A Time Series Structure Analysis Method of a Meeting Using Text Data and a Visualization Method of State Transition,” New Generation Computing, 2018, DOI: 10.1007/s00354-018-0050-6.
  • Ryotaro Okada, Takafumi Nakanishi, Yuichi Tanaka, Yutaka Ogasawara, Kazuhiro Ohashi, “A Visualization Method of Relationships among Topics in a Series of Meetings,” Information Engineering Express, vol 3, no 4, pp. 115-124, 2017. 
  • Okada, T. Nakanishi, A. Kawagoe, H. Saito, H. Saito, M. Shinohara, “A Redefinition Method of Extracting Features for Media Content Utilization and Its Application to Kimono Obi Design,” 2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI 2020), pp. 116-121, 2020.
  • Nakanishi, R. Okada, R. Nakahodo, “Kansei Transition Analysis by Time-series Change of Media Content,” 2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI 2020), pp. 422-427, 2020.
  • Nitta, S. Hagimoto, A. Yanase, T. Nakanishi, R. Okada, V. Sornlertlamvanich, “Finger Character Recognition in Sign Language Using Finger Feature Knowledge Base for Similarity Measure,” in Proceedings of the 3rd IEEE/IIAI International Congress on Applied Information Technology (IEEE/IIAI AIT 2020), 2020 [Best Paper Award].
  • Hagimoto, T. Nitta, A. Yanase, T. Nakanishi, R. Okada, V. Sornlertlamvanich, “Knowledge Base Creation by Reliability of Coordinates Detected from Videos for Finger Character Recognition,” in Proceedings of 19th IADIS International Conference e-Society 2021, FSP 5.1-F144, pp. 169-176, 2021.
  • Ryotaro Okada, Takafumi Nakanishi, Yuichi Tanaka, Yutaka Ogasawara, Kazuhiro Ohashi, “A Topic Structuration Method on Time Series for a Meeting from Text Data,” ACIS International SNPD 2017, IEEE, published in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing: Studies in Computational Intelligence, Springer, pp. 45-59,2017.
  • Takafumi Nakanishi, Ryotaro Okada, Yuichi Tanaka, Yutaka Ogasawara, Kazuhiro Ohashi, “A Topic Extraction Method on the Flow of Conversation in Meetings,” 2017 6th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), IEEE, pp. 351-356, 2017.
  • Takafumi Nakanishi, Ryotaro Okada, Takashi Kitagawa, “Automatic media content creation system according to an impression by recognition-creation operators,” IEEE/ACIS 15th International Conference on Computer and Information Science (ICIS), pp. 175–180, 2016.
  • Kyohei Matsumoto, Ryotaro Okada, Takafumi Nakanishi, Takashi Kitagawa, “The Method of Image Feature Selection for Integration of Image Classification by Bag-of-Keypoints,” 2015 International Conference on Computational Science and Computational Intelligence (CSCI), IEEE, pp. 589-594, 2015.
  • Ryotaro Okada, Takafumi Nakanishi, Takashi Kitagawa, “A Method of Knowledge Creation and Knowledge Utilization by Generalized Inverse Operator,” 2014 IIAI 3rd International Conference on Advanced Applied Informatics, IEEE, pp. 253-258, 2014.