MF Researcher Database

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Masato Ohkubo

    Department of Business Administration　Associate Professor
Last Updated :2025/06/06

Researcher Information

Degree

  • Doctor of Engineering（Waseda University）

Research funding number

  • 40777976

J-Global ID

Research Areas

  • Social infrastructure (civil Engineering, architecture, disaster prevention) / Social systems engineering / Quality statistics
  • Social infrastructure (civil Engineering, architecture, disaster prevention) / Social systems engineering / Industrial and Management Systems Engineering

Academic & Professional Experience

  • 2019/04 - Today  Waseda UniversityInstitute of Data ScienceAdjunct Researcher
  • 2019/04 - Today  Toyo UniversityFaculty of Business Administration, Department of Business AdministrationLecturer
  • 2018/04 - 2019/03  Waseda UniversityDepartment of Industrial and Management Systems Engineering, School of Creative Science and EngineeringAssistant Professor
  • 2016/04 - 2018/03  Waseda UniversityDepartment of Industrial and Management Systems Engineering, School of Creative Science and EngineeringResearch Associate
  • 2013/04 - 2016/03  Asahi Kasei CorporationInformation Systems Department

Education

  • 2016/04 - 2018/03  Waseda University  Graduate School of Creative Science and Engineering  Doctoral Program in Department of Industrial and Management Systems Engineering
  • 2011/04 - 2013/03  Waseda University  Graduate School of Creative Science and Engineering  Department of Industrial and Management Systems Engineering
  • 2007/04 - 2011/03  Waseda University  School of Creative Science and Engineering  Department of Industrial and Management Systems Engineering

Association Memberships

  • Japan Industrial Management Association (JIMA)   Japanese Society of Applied Statistics (JSAS)   Japanese Society for Quality Control (JSQC)   

Published Papers

Conference Activities & Talks

  • Taguchi’s RT method with sparse principal component analysis  [Not invited]
    Riku Ohta; Masato Ohkubo; Hiroki Iwamoto; Yasushi Nagata
    Asian Network for Quality (ANQ) Congress 2023, Ho Chi Minh city  2023/10  Oral presentation
  • The T-method with the application of sparse modeling  [Not invited]
    Ryo Asano; Masato Ohkubo; Shinto Eguchi; Yasushi Nagata
    Asian Network for Quality (ANQ) Congress 2022, Beijing  2022/10  Oral presentation
  • A Consideration of the Recognition Taguchi Method Using High-Dimensional Principal Component Analysis
    Ryo ASANO; Masato OHKUBO; Yasushi NAGATA
    Asian Network for Quality (ANQ) Congress 2021, Singapore  2021/10  Oral presentation
  • Mahalanobis-Taguchi Method for Anomaly Detection and Classification  [Not invited]
    Kentaro HONMA; Masato OHKUBO; Yasushi NAGATA
    Asian Network for Quality (ANQ) Congress 2021  2021/10  Oral presentation
  • Anomaly detection for noisy data with the Mahalanobis–Taguchi system  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    22th QMOD conference on Quality and Service Sciences ICQSS  2019/10  Oral presentation
  • Anomaly detection with Mahalanobis-Taguchi method based on robust sparse graphical modeling  [Not invited]
    Masato OHKUBO; Hironori FUJISAWA; Yasushi NAGATA
    119th Research meeting of the Japanese Society for Quality Control  2019/05  Oral presentation
  • The Mahalanobis-Taguchi Method using Bayesian principal component analysis  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    48th Annual Research meeting of the Japanese Society for Quality Control  2018/11  Oral presentation  大阪
  • Conditional anomaly detection based on a latent class model  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    21th QMOD conference on Quality and Service Sciences ICQSS  2018/08  Oral presentation  Wales
  • QUALITY DESIGN BASED ON TAGUCHI’S LOSS FUNCTION  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    International Academy of Business and Economics (IABE)-2018 MunichConference  2018/06  Oral presentation  Munich
  • The Mahalanobis-Taguchi Method based on a latent class model  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    116th Research meeting of the Japanese Society for Quality Control  2018/05  Oral presentation  東京
  • Analysis procedure for high dimensional data with the Mahalanobis-Taguchi system  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    115th Research meeting of the Japanese Society for Quality Control (Kansai Branch)  2017/09  Oral presentation  大阪
  • Mahalanobis-Taguchi method for contaminated unit space  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    Japanese Joint Statistical Meeting 2017  2017/09  Oral presentation  愛知
  • Anomaly detection in high-dimensional data with the Mahalanobis-Taguchi system  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    20th QMOD conference on Quality and Service Sciences ICQSS  2017/08  Oral presentation  Copenhagen / Elsinore, Denmark and Helsingborg, Sweden
  • The Mahalanobis-Taguchi Method based on gamma-divergence  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    113th Research meeting of the Japanese Society for Quality Control  2017/05  Oral presentation  東京
  • Anomaly detection by Mahalanobis-Taguchi method applying sparse modeling  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    the 79th National Convention of Information Processing Society of Japan  2017/03  Oral presentation  愛知
  • The Mahalanobis-Taguchi Method based on Graphical Modeling  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    46th Annual Research meeting of the Japanese Society for Quality Control  2016/11  Oral presentation  愛知
  • Applying Graphical Modeling to the Mahalanobis-Taguchi Method  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    Asian Network for Quality (ANQ) Congress 2016  2016/09  Oral presentation  Vladivostok
  • Consideration to apply MT system to small sample size data  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    101th Research meeting of the Japanese Society for Quality Control  2013/05  Oral presentation  東京
  • Consideration to Apply Q statistics to Mahalanobis Taguchi System using PCA  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    42th Annual Research meeting of the Japanese Society for Quality Control  2012/10  Oral presentation  石川
  • Taguchi's RT method using Ensemble learning and its application  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    98th Research meeting of the Japanese Society for Quality Control  2012/05  Oral presentation  東京
  • Consideration to apply Taguchi’s RT method to co-ntinuous type data that is not the same dimension  [Not invited]
    Masato OHKUBO; Yasushi NAGATA
    95th Research meeting of the Japanese Society for Quality Control  2011/05  Oral presentation  東京

MISC

Awards & Honors

  • 2023/10 ANQ Congress 2023 Best Paper Award
     
    受賞者: Riku Ohta;Masato Ohkubo;Hiroki Iwamoto;Yasushi Nagata
  • 2021/10 ANQ Congress 2021 Best Paper Award
     
    受賞者: Kentaro HONMA;Masato OHKUBO;Yasushi NAGATA
  • 2019/10 ANQ Congress 2019 Best Paper Award
     
    受賞者: Kosuke OYAMA;Masato OHKUBO;Yasushi NAGATA
  • 2018/11 Japanese Society for Quality Control JSQC Activity Acknowledgment
     
    受賞者: Masato OHKUBO
  • 2018/09 Japanese Society of Applied Statistics JSAS Best Paper Award for Young Researcher
     JPN official_journal 
    受賞者: Masato OHKUBO
  • 2017/09 ANQ Congress 2017 Best Paper Award
     
    受賞者: Masato OHKUBO;Yasushi NAGATA
  • 2017/09 Japanese Society for Quality Control (Kansai Branch) Best Presentation Award
     japan_society 
    受賞者: Masato OHKUBO
  • 2017/08 20th QMOD conference on Quality and Service Sciences ICQSS Best Paper Award Nomination
     international_society 
    受賞者: Masato OHKUBO;Yasushi NAGATA
  • 2017/05 Japanese Society for Quality Control Presentation Award
     JPN 
    受賞者: Masato OHKUBO
  • 2012/10 Japanese Society for Quality Control Award for Best Paper
     JPN 
    受賞者: Masato OHKUBO;Yasushi NAGATA

Research Grants & Projects

  • Japan Society for the Promotion of Science：Grants-in-Aid for Scientific Research
    Date (from‐to) : 2021/04 -2026/03 
    Author : 大久保 豪人
     
    本研究では，センサー・データを活用した設備機器等の状態監視システムの実現に向けて，タグチメソッドから着想を得た誤差因子にロバストな異常検出法を開発することを目的としている．2021年度は，国際会議にて3件の発表を行うことができた．なお，以下の研究の一部はJSPS科研費18K13953の助成を受けている． 【研究実績I】 運転状況等に応じた複数の正常モードをもつデータからの異常検出を可能とするプロシージャを開発した．この提案プロシージャを改善する形で誤差因子にロバストな異常検出法を目指す予定である．なお，この成果の一部を2021年度の国際会議にて発表し，Best Paper Awardを受賞した． 【研究実績II】Ohkubo & Nagata (2018)で提案した異常検出プロシージャ，すなわち高次元データからの異常検出をより適切に実行できる異常検出プロシージャを新たな観点から再評価した．この研究により，高次元データを対象とした異常検出プロシージャの拡張について一定の方向性を見出すことができた．次年度以降も引き続き，本プロシージャの改善を進めて行きたい．なお，この成果の一部を2021年度の国際会議にて発表している． 【研究実績III】異常検出プロシージャを統計的パターン認識の枠組みに則って実行する方法について議論を行った．その予備的な研究として，タグチのT法を分類問題に応用するプロシージャを開発した．次年度以降，この成果を分類問題ではなく異常検出問題に適用可能なプロシージャに発展させる予定である．なお，この成果の一部を2021年度の国際会議にて発表している．
  • Development of practical anomaly detection based on robust sparse modeling
    Japan Society for the Promotion of Science(JSPS)：KAKENHI (Early-Career Scientists)
    Date (from‐to) : 2018/04 -2021/03 
    Author : Masato OHKUBO
  • Development of robust sparse graphical modeling method for anomaly detection
    The Institute of Statistical Mathematics：Open-Type Professional Development Program (Intensive Training for Young Researchers)
    Date (from‐to) : 2018/04 -2019/03 
    Author : Masato OHKUBO
  • Establishment of statistical anomaly detection procedure based on sparse modeling
    Waseda University：Waseda University Grant for Special Research Projects
    Date (from‐to) : 2017/04 -2018/03 
    Author : Masato OHKUBO
  • Development and improvement of practical statistical anomaly detection method for small sample data
    Waseda University：Waseda University Grant for Special Research Projects
    Date (from‐to) : 2016/04 -2017/03 
    Author : Masato OHKUBO
  • Development of robust online anomaly detection method based on divergence type method
    The Institute of Statistical Mathematics：Cooperative Research Program (General Cooperative Research 2)
    Author : Masato OHKUBO

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