Seiichi OZAWA, Dr. Eng.    [Japanese] [Curriculum Vitae]

Affiliation Center for Mathematical and Data Sciences, Kobe University
Graduate School of Engineering, Kobe University
Position Professor
Address 1-1 Rokko-Dai, Nada-ku, Kobe 657-8501, JAPAN
TEL/FAX +81 78 803 6466
Research Fields Neural Networks,  Machine Learning, Pattern Recognition,
Big Data Analytics, Cyber-Security, SNS Security, Smart Agriculture

Short Biography [Curriculum Vitae]

Seiichi Ozawa received the B.E. and M.E. degrees in instrumentation engineering from Kobe University in 1987 and 1989, respectively. In 1998, he received his Dr. Eng. in computer science from Kobe University. He is currently the deputy director of Center for Mathematical and Data Sciences and a full professor with the Department of Electrical and Electronic Engineering, Graduate School of Engineering, Kobe University, Japan. He was a visiting researcher at Arizona State University in 2005. His current research interests are neural networks, machine learning, online learning, pattern recognition, big data analytics especially in cybersecurity, SNS and smart agriculture. He published 141 journal and refereed conference papers, and 9 book chapters/monographs. He is currently an associate editor of IEEE Trans. on Cybernetics, Evolving Systems Journal, Pattern Analysis and Applications Journal, and he was an associated IEEE Trans. on Neural Networks and Learning Systems for 6 years. Currently, he is a Pro Tempore Vice-President for Public Relations of International Neural Network Society (INNS), a vice-president for finance of Asia Pacific Neural Network Society (APNNS), and a special board of governor of Japan Neural Network Society (JNNS). He is a member of Neural Networks TC, Data Mining and Big Data Analytics TC, and Smart World TC of IEEE CI Society. He is serving as a general chair of INNS Conference on Big Data and Deep Learning 2018, Program Committee Chair of International Conference on Neural Information Processing 2018, Workshop Chair of 2018 IEEE Smart World Congress, and Program Committee Members of IJCNN 2018, INNS 2018, EAIS 2018, etc.

Recent Research Projects

  1. Machine Learning over Encrypted Data for Privacy-Preserving Data Mining
  2. Cyber-Security Using Machine Learning (Darknet Analysis, Deep/Dark Web AI Crawler)
  3. Sentiment Analysis for SNS Comments and Its Application to Flaming Detection
  4. Image Sensing Methods to Capture Growth Status of Agricultural Plants
  5. Visualization of High-Dimensional Data Using Machine Learning

Publication List

Activities of International Committee
International Neural Network Society (INNS) - Vice-President for PR, Governing Board Member
Asia Pacific Neural Network Society (APNNS) - Vice-President for Finance, Governing Board Member
Japan Neural Network Society - Special Goeverning Board Member
IEEE Trans. on Cybernetics - Associate Editor
IEEE Trans. on Neural Networks - Associate Editor (Past)
Evolving Systems (Springer) - Editorial Board Member
Pattern Analysis and Applications Journal (Springer) - Associate Editor
IEEE CIS, Neural Networks Technical Committee (NNTC) - Member
INNS SIG Autonomous Machine Learning - Member
INNS BDDL 2018 - General Co-Chair
IJCNN2017, ICONIP2017, INNS-BigData 2016, IScIDE2015, ICIST2015, ICIC2015, DMC2015 - Program Committee Member

International Research Collaborators

  1. Large-Scale Cyber Attacks Monitoring using Evolving Cauchy Possibilistic Clustering
    Prof. Igor Skrjanc
    Faculty of Electrical Engineering, University of Ljubljana, Slovenia
  2. Learning from SNS Big Data and Its Application to Flaming Detection
    Dr. Nistor Grozavu (Paris 13, France) and Dr. Nicoleta Rogovschi (Paris 5, France)
  3. Online Feature Extraction and Incremental Learning for Spiking Neural Networks
    Prof. Nikola Kasabov
    Knowledge Engineering and Discovery Research Institute (KEDRI), Auckland University of Technology, New Zealand
  4. Autonomous Learning for Neural Networks
    Prof. Asim Roy
    Dept. of Information Systems, Arizona State University, USA
  5. Ensemble Classifier Model Using Multimodal Features for Multitask Pattern Recognition Problems
    Prof. Minho Lee
    School of Electrical Engineering and Computer Science, Kyungpook National University, Korea