Introduction

I am passionate about modeling real-world business problems using advanced machine learning methods. I have a strong track record in successfully leading numerous customer engagements to deliver first-of-a-kind AI solutions across different industries. Most of the core algorithms I developed in those projects have been published in top AI/data mining conferences such as AAAI, IJCAI, ICDM, SDM, etc., which makes me one of the leading experts in AI-powered industry solution development in IBM.

In particular, I am known as an expert in anomaly and change detection, as evidenced by two textbooks I authored. I am particularly interested in extracting actionable insights from AI algorithms. See my LinkedIn article for my thoughts on eXplainable AI (XAI) research, specifically in the context of anomaly explanation (AAAI 2021) and its probabilistic extension (KDD 23). Other recent research interests include causal discovery from stochastic event data for AIOps (see, e.g., NeurIPS 21) and graph neural networks (AAAI 22, ICASSP 23).

Currently, I am serving as the head of data science, IBM Semiconductors. My almost two decades of experience in delivering AI-powered business solutions covers industries such as:

  • Semiconductor manufacturing
    • Fault detection and classification
    • stochastic WIP simulation and optimization
    • Statistical process control
  • Condition-based monitoring:
    • Automotive (sensor analytics, experimental design, failure diagnosis, EV fleet management, etc.)
    • Oil and petroleum
    • AIOps (event causal analysis)
    • Financial (Stock price monitoring, blockchains, collaborative learning, etc.)
    • Mining
    • etc.
  • Healthcare (diabetes data analytics)
  • Transportation
    • Railway
    • Maritime
    • Traffic simulation
    • Travel time prediction
  • LCD optics design
  • Statistical project management
  • Power grid failure analysis

In addition to broad industry knowledge, I have years’ of people and project management experience both in Japan and the US. I have done much work also in intellectual property management, handling many non-disclosure agreements, technology license agreements, and service contracts.

Back in Japan, I was known as a collector of antique computer keyboards. You can check some of my collection of mechanical keyboards on my YouTube channel. I also run a website on the history of modern computer keyboards (in Japanese). Enjoy!

Education

  • Ph.D. in Physics, The University of Tokyo, Japan, 2000.
    • Thesis: “Theoretical Study on Nonlocal Effects in Resonant X-Ray Emission Spectra of Strongly-Correlated Systems”
    • Supervisor: Prof. Kotani Akio
  • M.Sc. in Physics, University of Tokyo, Japan, 1997.
  • B.Eng. in Mechanical Engineering, Tohoku University, Japan, 1993.

Employment

I am a Japanese citizen and U.S. permanent resident.

  • Current-04/01/2023: Head of Data Science, IBM Semiconductors at IBM Research
    • Formulate R&D roadmap for technical differentiation of IBM’s Manufacturing Execution System (MES) using AI/ML technologies.
    • Lead technology development with data scientists for Fab-wide optimization in semiconductor manufacturing.
    • Provide consulting based on deep AI/ML expertise to address clients’ pain points in semiconductor manufacturing.
  • 03/31/2023-07/12/2016: IBM Thomas J. Watson Research Center
    • Senior Technical Staff Member
      • Perform basic and applied research in AI to publish research outcomes in world premier conferences and journals as well as patents.
      • Lead customer engagements and provide the team with technical guidance.
      • Play the role of technical evangelist to influence IBM’s technical roadmap based on a broad range of experiences on real business.
  •  07/11/2016-09/04/2013: IBM Thomas J. Watson Research Center (on international assignment from IBM Japan)
    • Senior Technical Staff Member (09/2014-07/2016).
      • Led a variety of customer engagements to success as the technical leader.
      • Developed innovative machine learning methods for industrial sensor data and published six lead-authored papers in top AI/data mining conference and journals.
    • Manager, Service Delivery & Risk Analytics (09/2013-09/2014).
      • Engaged in people, projects, and research strategy management of the team.
      • Proposed novel AI-based approaches to IT (information technology) system development.
      • Awarded two Outstanding Technical Achievement Awards by IBM Corporation for that work.
  • 09/03/2013-04/01/2000: IBM Research – Tokyo
    • Manager, Analytics & Optimization (09/2010-09/2013).
      • Directed AI research at IBM Research – Tokyo (except for teams dedicated to speech and text analytics).
      • Successfully established an organizational management model that strikes an optimal balance business contributions and academic reputation.
      • Proposed a new AI-driven business strategy and led numerous customer engagements. Major successful projects include the development of an intelligent transportation system in Kenya and a health monitoring system for ocean-going vessels. The latter won the General Manager Award of IBM Japan.
    • Senior Researcher (2010-2013), Advisory Researcher (2008-2010), Staff Researcher (2005-2008)
      • Led basic and applied research in AI as a technical leader.
      • Launched the project of Sensor Data Analytics as a promising area of AI applications.
      • Major research achievements include the establishment of a dependency-based anomaly detection method, which was awarded the Outstanding Technical Achievement Award later.
    • Researcher (2000-2005)
      • Engaged in improving existing IBM products using mathematical science technologies.
      • Major contributions include a significant improvement of luminance uniformity of IBM ThinkPad displays and the development anomaly detection solution of computer systems.

Honors & Awards

  • 2023
    • Outstanding Technical Achievement Award, IBM Corporation (for Scientific Contribution to AI for Combinatorial Sparsity)
  • 2022
    • High Value Patent Award, IBM Corporation (for the invention titled “Learning pattern dictionary from noisy numerical data in distributed networks”)
  • 2019
    • Research Division Award, IBM Corporation (for SROM: Smarter Resources and Operations Management Framework)
  • 2018
    • Outstanding Technical Achievement Award, IBM Corporation (for Business and Technical Leadership in IBM Anomaly Analyzer for Correlational Data)
  • 2017
    • Best Author Award, The Japan Society for Industrial and Applied Mathematics (For his article titled “Predicting project risks using latent trait model”)
  • 2016
    • Outstanding Technical Achievement Award, IBM Corporation, (for End-to-end Contract Profitability Analytics for ITS)
    • Outstanding Technical Achievement Award, IBM Corporation (for Financial Risk Analytics for Strategic Outsourcing)
  • 2015
    • Outstanding Technical Achievement Award, IBM Corporation (for Fundamental Contributions to Anomaly Detection)
    • Research Division Award, IBM Corporation (for SO T&T Repeatable Model Release 11: Cost Analysis and Optimization)
  • 2013
    • General Manager Award, IBM Japan (for successful delivery of vessel monitoring system to ClassNK)
  • 2007
    • Winner, ICDM Data Mining Contest, The 2007 Seventh IEEE International Conference on Data Mining
  • 2006
    • JSAI Annual Conference Award, The 20th Annual Conference of the Japanese Society for Artificial Intelligence
  • 2004
    • JSAI Annual Conference Award, The 18th Annual Conference of the Japanese Society for Artificial Intelligence

Executive/Board Membership

  • Today-2013: IBM Academy of Technology.
  • 2015-2011: Secretary, Machine Learning Activity Group of the Japan Society for Industrial and Applied Mathematics (JSIAM-ML).
  • 2014-2012: Board of Directors, The Japanese Society for Artificial Intelligence.
  • 2010-2008: Vice Chair, Technical Committee on Information-Based Induction Sciences (IBIS), IEICE.

Academic Community Services

Government grant reviewer

  • Council for the Humanities, Netherlands Organisation for Scientific Research, 2013.

Journal editor

Chair / Senior committee member

  • Senior Program Committee Member, 2023 SIAM International Conference on Data Mining (SDM 2023).
  • Senior Program Committee Member, The 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2024).
  • Area Chair, The 23rd IEEE International Conference on Data Mining (ICDM 2023).
  • Program Co-Chair, The 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023).
  • Senior Program Committee Member, 36th AAAI Conference on Artificial Intelligence (AAAI-22)
  • Senior Program Committee Member, 30th International Joint Conference on Artificial Intelligence (IJCAI-21), 2021.
  • Publicity Chair, The 9th IEEE International Conference on Big Knowledge (IEEE ICBK 2018), 2018.
  • Senior Program Committee Member, 24th International Joint Conference on Artificial Intelligence (IJCAI-15), 2015.
  • Program Chair, The 12th Workshop on Information-Based Induction Sciences (IBIS 2009), 2009.

Technical program committee member

  • 2024
    • The 38th AAAI Conference on Artificial Intelligence (AAAI 24).
    • The 2024 SIAM International Conference on Data Mining (SDM 24)
    • The 37th IEEE/IFIP Network Operations and Management Symposium (NOMS 2024).
  • 2023
    • The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’23).
    • The 32nd International Joint Conference on Artificial Intelligence (IJCAI-23).
    • The Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI-23).
    • 2023 IEEE/IFIP Network Operations and Management Symposium (NOMS 2023).
    • 2023 International Conference on Blockchain and Trustworthy Systems (BlockSys ’23).
    • 2023 IEEE International Conference on Big Data (BigData 23).
    • The 15th Asian Conference on Machine Learning (ACML 23).
  • 2022
    • The 22nd IEEE International Conference on Data Mining (IEEE ICDM 2022).
    • The 31st International Joint Conference on Artificial Intelligence and the 25th European Conference on Artificial Intelligence (IJCAI-ECAI 22) [certificate].
    • ACM SIGKDD International Conference on Data Mining (KDD 2022).
    • 2022 SIAM International Conference on Data Mining (SDM 2022).
    • 2022 IEEE/IFIP Network Operations and Management Symposium (NOMS 2022).
  • 2021
    • The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI-21).
    • 2021 SIAM International Conference on Data Mining (SDM 2021).
    • 2021 IEEE International Conference on Data Mining (IEEE ICDM 2021).
    • The 13th Asian Conference on Machine Learning (ACML 2021).
    • 2021 IFIP/IEEE International Symposium on Integrated Network Management (IM 2021).
  • 2020
    • 2020 IEEE International Conference on Data Mining (IEEE ICDM 2020).
    • The 29th International Joint Conference on Artificial Intelligence (IJCAI-20).
    • The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20).
    • The 12th Asian Conference on Machine Learning (ACML 2020).
    • 2020 International Conference on Blockchain and Trustworthy Systems (BlockSys 2020).
  • 2019
    • 2019 IEEE International Conference on Data Mining (IEEE ICDM 2019).
    • The 28th International Joint Conference on Artificial Intelligence (IJCAI-19; selected as Distinguished Program Committee Member).
    • The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 19).
    • The 28th ACM International Conference on Information and Knowledge Management (CIKM 2019).
    • 2019 International Conference on Blockchain and Trustworthy Systems (BlockSys 2019).
    • The 11th Asian Conference on Machine Learning (ACML 2019).
    • The 16th IFIP/IEEE International Symposium on Integrated Network Management (IM 2019).
  • 2018
    • 2018 IEEE International Conference on Data Mining (IEEE ICDM 2018).
    • The 10th Asian Conference on Machine Learning (ACML 2018).
    • The 27th International Joint Conference on Artificial Intelligence (IJCAI 2018).
    • The 2018 IEEE/IFIP Network Operations and Management Symposium (NOMS 2018).
  • 2017
    • The 9th Asian Conference on Machine Learning (ACML 2017).
    • The 15th IFIP/IEEE International Symposium on Integrated Network Management (IM 2017).
  • 2016
    • The IEEE/IFIP Network Operations and Management Symposium (NOMS 2016).
  • 2015
    • The 14th IFIP/IEEE International Symposium on Integrated Network Management (IM 2015).
  • 2013
    • The 30th International Conference on Machine Learning (ICML 2013).
    • The First International Workshop on Tera-Scale In-Core Data Mining (TIDM 2013).
  • 2012
    • The 4th Asian Conference on Machine Learning (ACML 2012).
  • 2011
    • 2011 SIAM International Conference on Data Mining (SDM 2011).
    • The 3rd Asian Conference on Machine Learning (ACML 2011).
    • IEEE International Workshop on Data Mining for Service (DMS2011).
  • 2010
    • IEEE International Workshop on Data Mining for Service (DMS2010).
    • International conference on IT and Business Intelligence (ITBI-10).
    • The 13th Workshop on Information-Based Induction Sciences (IBIS 2010).
  • 2009
    • JSAI 2009 Conference and Workshops, Japanese Society for Artificial Intelligence.
  • 2008
    • JSAI 2008 Conference and Workshops, Japanese Society for Artificial Intelligence.
    • The 11th Workshop on Information-Based Induction Sciences (IBIS 2008).
  • 2007
    • The 10th Workshop on Information-Based Induction Sciences (IBIS 2007).

Reviewer services

  • 2014
    • ICLR 2024
  • 2023
    • NeurIPS 2023
    • ICLR 2023
    • ICML 2023
  • 2022
    • NeurIPS 2022
    • ICML 2022
    • ICLR 2022
  • 2021
    • NeurIPS 2021
    • ICLR 2021
    • ICML 2021
  • 2020
    • NeurIPS 2020
    • Pattern Recognition,  IEEE Transactions on Industrial Informatics, Machine Learning, Frontiers in Big Data

+ Many others…