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Name MASUDA Satoshi
Official Title Professor
Affiliation Information Systems, Informatics
E-mail smasuda@tcu.ac.jp
Web
  1. https://www.risys.gl.tcu.ac.jp/Main.php?action=profile&type=detail&selected_lang=E&tchCd=7000232000
  2. https://researchmap.jp/satoshi.masuda?lang=en
Profile Masuda had been working in an IT company and experienced developing information systems for clients. He has also been researching for software engineering, especially software testing and published papers and patents. Based on his background, we, Prof. Masuda laboratory, are working for software engineering to contribute for developing high quality software efficiently to solve social challenges. Many new technologies and methodologies for software have been developed, however, they are required contribution in real cases. We are tackling problems in wide area, such as testing autonomous-driving car, using natural language processing for requirement engineering and data science in enterprise systems.
Research Field(Keyword & Summary)
  1. Software Engineering and Data Science

    This research aims for efficiency and quality in processing tasks of data science.

  2. Software Testing

    Software testing has been always required to verify and validate the software, even if we bring any new technologies and methodologies. We are working for efficient software testing for every software.
Representative Papers
  1. (1) Guidelines for Quality Assurance of Machine Learning-Based Artificial Intelligence, International Journal of Software Engineering and Knowledge Engineering, Oct. 2020, pp1-18
  2. (2) Rule-based searching for collision test cases of autonomous vehicles simulation, IET Intelligent Transport Systems, 2018, 12, (9), p. 1088-1095
  3. (3) Semantic role labeling for automatic software test cases generation, Compter software, Vol.34, No.2(2017), pp.16-27 (in Japanese)
  4. (4) Detecting Logical Inconsistencies by Clustering Technique in Natural Language Requirements, Institute of Electronics Information and Communication Engineers, IEICE Transactions on Information and Systems, Volume E99.D (2016) Issue 9, Sep. 2016, pp. 2210-2218
  5. (5) Automatic Generation of UTP Models from Requirements in Natural Language, Ninth IEEE International Conference on Software Testing, Verification and Validation Workshops, ICST Workshops 2016, Chicago, IL, USA, April 11-15, 2016, 1-6, 2016
  6. (6) Syntactic Rules of Extracting Test Cases from Software Requirements, Proceedings of the 8th International Conference on Information Management and Engineering, ICIME 2016, Istanbul, Turkey, November 2-5, 2016, 12-17, 2016
  7. (7) Online Adaptation of Parameters using GRU-based Neural Network with BO for Accurate Driving Model SIGSPATIAL '21: 29th International Conference on Advances in Geographic Information Systems, Virtual Event / Beijing, China, November 2-5, 2021, 33-36, 2021
  8. (8) Spatially and semantically diverse points extraction using hierarchical clustering, LocalRec '21: Proceedings of the 5th ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising, Virtual Event / Beijing, China, 2 November 2021, 1:01-1:08, 2021
  9. (9) Data Quality for Machine Learning Tasks, KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, Singapore, August 14-18, 2021, 4040-4041, 2021
  10. (10) Obtaining Exhaustive Answer Set for Q&A-based Inquiry System using Customer Behavior and Service Function Modeling, Knowledge-Based and Intelligent Information & Engineering Systems: Proceedings of the 22nd International Conference KES-2018, Belgrade, Serbia, 3-5 September 2018, 126 986-995, 2018
Patent
  1. (1) Metric learning prediction of simulation parameters, US 20200393840A1
  2. (2) Verifying and correcting training data for text classification, US 20200034482A1
  3. (3) Training and testing automated driving models, US 20200225668A1
  4. (4) Approach to recommending mashups, US10606658B2, 2020
  5. (5) Verifying and correcting training data for text classification, US20200034482A1, 2020
Award (1) Best Paper Award: Second Place, "Guidelines for Quality Assurance of Machine Learning-based Artificial Intelligence,," The 32nd International Conference on Software Engineering & Knowledge Engineering, KSIR Virtual Conference Cener, Pittsburgh, USA, July 9-19, 2020
(2) International Standard Contribution Award, Information Technology Standards Comiison of Japan, Information Processing Society of Japan, 2018.
(3) International Standard Development Award, Information Technology Standards Comiison of Japan, Information Processing Society of Japan, 2017.
Grant-in-Aid for Scientific Research Support: Japan Society for Promotion of Science (JSPS) https://nrid.nii.ac.jp/en/nrid/1000060947927/
Research Grants/Projects including subsidies, donations, grants, etc. https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-22K21288
Recruitment of research assistant(s) No
Affiliated academic society (Membership type) (1) Information Processing Society of Japan (Senior Member)
(2) IEEE (Member)
(3) The Japanese Society for Artificial Intelligence (Member)
Education Field (Undergraduate level) Enterprise Information Systems, Electric Commerce
Education Field (Graduate level) Software Engineering

Affiliation