SAIGO HIROTO
Organization
Faculty of Information Science and Electrical Engineering Department of Informatics Associate Professor
School of Sciences Department of Physics（Concurrent）
Graduate School of Information Science and Electrical Engineering Department of Information Science and Technology（Concurrent）
Joint Graduate School of Mathematics for Innovation
（Concurrent）
Title
Associate Professor
Contact information
Tel
0928023783
Profile
His research interest is in developing methods for data mining and artificial intelligence, and applying them to problems in biology and chemistry. He also serves as a program committee member for international conferences in bioinformatics and machine learning.
External link
Degree
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Doctor of Informatics
Research History
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2010-2015 九州工業大学（准教授） 2008-2010 Max Planck Institute for Informatics, Germany (Research Scientist) 2006-2008 Max Planck Institute for Biological Cybernetics, Germany (Research Scientist)
Research Interests・Research Keywords
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Research theme：Machine Learning for High-Level Radioactive Waste Management: An Approach Based on Control of High-Temperature Multiphase Melts
Keyword：machine learning, high-level radioactive waste, high-temperature multiphase melts
Research period： 2023.4
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Research theme：A machine learning approach to automatic design of genes, proteins and chemical compounds
Keyword：machine learning, protein squence, chemical compound, design
Research period： 2022.9
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Research theme：Development of machine learning methods towards manufacturing informatics
Keyword：machine learning, data mining, statistics
Research period： 2018.4
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Research theme：Development of a GWAS method that considers interaction among genetic factors and environmental factors
Keyword：GWAS, interaction
Research period： 2013.3
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Research theme：Development and application of statistical learning methods to the problems associated with Human Immunodeficiency Virus (HIV).
Keyword：HIV, statistical learning, pattern mining
Research period： 2008.6
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Research theme：Integration of frequent pattern mining with machine learning algorithms
Keyword：頻出パターンマイニング、ブースティング、線形計画法、SVM
Research period： 2006.6
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Research theme：Development of kernel methods for detecting remote homology between protein sequences.
Keyword：kernel methods, protein homology detection, alignment, SVM
Research period： 2002.4 - 2006.3
Awards
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奨励賞
2007.6 人工知能学会 奨励賞
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Best Paper Award
2006.6 Mining and Learning with Graphs Committee
Papers
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Einstein-Roscoe regression for the slag viscosity prediction problem in steelmaking Reviewed International journal
@Saigo, H., Bahadur, K.C.D, @Saito, N.
Scientific Reports 12 2022.4
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Automatically mining relevant variable interactions via sparse Bayesian learning Reviewed International journal
#Yafune, R., #Sakuma, D., Tabei, Y., @Saito, N., @Saigo, H.
International Conference on Pattern Recognition 2021.1
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KDE: a Kernel-based approach to detecting high-order genetic Epistasis Reviewed International journal
Kodama, K., Saigo, H.
The 27th International Conference on Genome Informatics (GIW2016) 2016.10
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Protein Structure Comparison Based on 3D Molecular Visualization Images Reviewed International journal
Suryanto, C. H., Saigo, H., Fukui, K.
2016.8
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Extracting sets of chemical substructures and protein domains governing drug-target interactions Reviewed International journal
Yamanishi, Y., Pauwels, E., Saigo, H., Stoven, V.
51 ( 5 ) 1183 - 1194 2011.5
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Learnig from past treatments and their outcome improves prediction of in vivo response t anti-HIV therapy Reviewed International journal
Saigo, H., Altmann, A., Bogojeska, J., Mueller, F., Nowozin, S., and Lengauer, T.
10 ( 1 ) 2011.1
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Reaction graph kernels that predict EC numbers of unknown enzymatic reactions in the secondary metabolism of plant Reviewed International journal
Saigo, H., Hattori, M., Kashima, H., and Tsuda, K.
Asia Pacific Bioinformatics Conference (APBC2010) 2010.1
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gBoost: A mathematical programming approach to graph classification and regression Reviewed International journal
Saigo, H., Nowozin, S., Kadowaki, T., Kudo, T., and Tsuda, K.
75 ( 1 ) 69 - 89 2009.4
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Iterative Subgraph Mining for Principal Component Analysis Reviewed International journal
Saigo, H. and Tsuda, K.
IEEE International Conference on Data Mining (ICDM2008) 2008.12
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Partial Least Squares Regression for Graph Mining Reviewed International journal
Saigo, H., Kraemer, N. and Tsuda, K.
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2008) 2008.8
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Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism Reviewed International journal
Saigo, H., M. Hattori and K. Tsuda:
NIPS Workshop on Machine Learning in Computational Biology, 2007.12
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Graph boosting for molecular QSAR analysis Reviewed International journal
Saigo, H., Kadowaki, T., Kudo, T. and Tsuda, K.
NIPS Workshop on Machine Learning in Computational Biology, 2006.12
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A Linear Programming Approach for Molecular QSAR analysis Reviewed International journal
Saigo, H., Kadowaki, T. and Tsuda, K.
International Workshop on Mining and Learning with Graphs (MLG2006) 2006.9
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Optimizing amino acid substitution matrices with a local alignment kernel Reviewed International journal
Saigo, H., Vert J.-P. and Akutsu, T.
7 ( 246 ) 1 - 12 2006.5
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Functional census of mutation sequence spaces: The example of p53 cancer rescue mutants Reviewed International journal
Danziger, S. A., Swamidass, S. J., Zeng, J., Dearth, L. R., Lu, Q., Cheng, J. H., Cheng, J. L., Hoang, V. P., Saigo, H., Luo, R., Baldi, P., Brachmann, R. K. and Lathrop, R. H.
3 ( 2 ) 114 - 125 2006.4
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A novel representation of protein sequences for prediction of subcellular location using support vector machines Reviewed International journal
Matsuda, S., Vert, J.-P., Saigo, H., Ueda, N., Toh, H. and Akutsu, T.
14 2804 - 2813 2005.1
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Graph Kernels for Chemical Informatics Reviewed International journal
Ralaivola, L., Swamidass, J. S., Saigo, H. and Baldi, P.
18 ( 8 ) 1093 - 1110 2005.1
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Benchmarking a Wide Range of Unsupervised Learning Methods for Detecting Anomaly in Blast Furnace
Itakura K., Bahadur D., Saigo H.
International Conference on Pattern Recognition Applications and Methods 1 641 - 650 2024 （ ISBN:9789897586842 ）
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A Branch-and-Bound Approach to Efficient Classification and Retrieval of Documents
Ii K., Saigo H., Tabei Y.
International Conference on Pattern Recognition Applications and Methods 1 205 - 214 2024 （ ISBN:9789897586842 ）
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pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model Invited Reviewed International journal
Pratyush, P., Pokharel, S., @Saigo, H., KC.D.B.
BMC Bioinformatics 24 ( 1 ) 2023.2
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Sparse nonnegative interaction models Reviewed International journal
#Takayanagi, M., Tabei, Y., @Suzuki, E., @Saigo, H.
IEEE Access 2021.8
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Topic modeling for sequential documents based on hybrid inter-document topic dependency Reviewed International journal
#Li, W. and @Saigo, H. and Tong, E. and @Suzuki, E.
Journal of Intelligent Information Systems, 56 ( 3 ) 453 - 458 2021.6
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DeepRMethylSite: a deep learning based approach for prediction of arginine methylation sites in proteins Reviewed International journal
Chaudhari, M., Thapa, N., S., Roy, K., Newman, R.H., @Saigo, H., KC, D.B.
Molecular Omics 2020.10
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Context-Aware Latent Dirichlet Allocation for Topic SegmentationWenbo Li,?Tetsu Matsukawa,?Hiroto Saigo,?Einoshin Suzuki: Reviewed International journal
#Wenbo Li,?Tetsu Matsukawa,?Hiroto Saigo,?Einoshin Suzuki
PAKDD 2020.5
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DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction, Reviewed International journal
Thapa, N., Chaudhari, M., McManus, S., Roy, K., Newman, R.H., Saigo, H., KC, D.B.
BMC Bioinformatics 2020.4
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RF-MaloSite and DL-Malosite: Methods based on random forest and deep learning to identify malonylation sites Reviewed International journal
Al-barakati, H.J., Thapa, N., Saigo, H., Roy, K., Newman, R.H., Bahadur, K.C.D.
Computational and Structural Biotechnology Journal 2020.2
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SVM-GlutarySite: A support vector machine-based prediction of Glutarylation sites from protein sequences Reviewed International journal
Albarakati, H., Saigo, H., Newman, R.H., KC, D.B.
Joint GIW/ABACBS-2019 Bioinformatics Conference 2019.9
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RF-GlutarySite: a random forest predictor for glutarylation sites Reviewed International journal
Al-barakati, H.J., @Saigo, H., Newman, R.H., Bahadur, K.C.D.
Molecular Omics ( 15 ) 189 - 204 2019.4
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DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction Reviewed International journal
Thapa, N., Chaudhari, M., McManus, S., Roy, K., Newman, R.H., Saigo, H., KC, D.B.
MCBIOS 2019.3
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Entire regularization path for sparse nonnegative interaction model Reviewed International journal
#Takayanagi, M., Tabei, Y., Saigo, H.
ICDM 2018.11
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Structural Class Classification of 3D Protein Structure Based on Multi-View 2D Images Reviewed
Chendra Hadi Suryanto, Hiroto Saigo, Kazuhiro Fukui
IEEE/ACM Transactions on Computational Biology and Bioinformatics 15 ( 1 ) 286 - 299 2018.1
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CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes Reviewed International journal
2017.12
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RF-NR: Random forest based approach for improved classification of Nuclear Receptors Reviewed International journal
Ismail, H.D., Saigo, H., Bahadur, K.C.D.
IEEE Transactions on Computational Biology and Bioinformatics 2017.11
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CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes Reviewed International journal
2017.9
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KDSNP: A kernel-based approach to detecting high-order SNP interactions Reviewed
Kento Kodama, Hiroto Saigo
Journal of Bioinformatics and Computational Biology 14 ( 5 ) 1 - 16 2016.10
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Scalable Partial Least Squares Regression on Grammar- Compressed Data Matrices Reviewed International journal
Tabei, Y., Saigo, H., Yamanishi, Y., Puglisi, S.
The 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2016) 2016.8
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Mining Discriminative Patterns from Graph Data with Multiple Labels and Its Application to Quantitative Structure-Activity Relationship (QSAR) Models Reviewed
Zheng Shao, Yuya Hirayama, Yoshihiro Yamanishi, Hiroto Saigo
JOURNAL OF CHEMICAL INFORMATION AND MODELING 55 ( 12 ) 2519 - 2527 2015.12
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RF-NR: Random forest based approach for improved classification of Nuclear Receptors Reviewed
Ismail, H.D, Saigo, H, Bahadur, K.C, D
International Conference on Genome Informatics & International Conference on Bioinformatics (GIW/InCoB2015) 2015.9
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Fast Iterative Mining Using Sparsity-Inducing Loss Functions Reviewed
Hiroto Saigo, Hisashi Kashima, Koji Tsuda
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS E96D ( 8 ) 1766 - 1773 2013.8
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Protein Clustering on Grassman Manifold, Pattern Recognition in Bioinformatics Reviewed International journal
Suryanto, C.H., Saigo, H., Fukui, K.
Pattern Recognition in Bioinformatics (PRIB2012) 2012.11
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A Bayesian Approach to Graph Regression with Relevant Subgraph Selection Reviewed International journal
Chiappa, S., Saigo, H. and Tsuda, K.
Siam International Conference on Data Mining (SDM2009) 2009.4
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Regression with Interval Output Values Reviewed International journal
Kashima, H., Yamasaki, K., Saigo, H. and Inokuchi, A.
International Conference on Pattern Recognition (ICPR2008) 2008.1
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Regression with Intervals Reviewed International journal
Kashima, H., Yamazaki, K., Saigo, H. and Inokuchi, A.
International Workshop on Data-Mining and Statistical Science (DMSS2007) 2007.10
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Mining complex genotypic features for predicting HIV-1 drug resistance Reviewed
Hiroto Saigo, Takeaki Uno, Koji Tsuda
BIOINFORMATICS 23 ( 18 ) 2455 - 2462 2007.9
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Functional census of mutation sequence spaces: The example of p53 cancer rescue mutants
SA Danziger, SJ Swamidass, J Zeng, LR Dearth, Q Lu, JH Chen, JL Cheng, VP Hoang, H Saigo, R Luo, P Baldi, RK Brachmann, RH Lathrop
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 3 ( 2 ) 114 - 125 2006.4
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Large-scale prediction of disulphide bridges using kernel methods, two-dimensional recursive neural networks, and weighted graph matching
JL Cheng, H Saigo, P Baldi
PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS 62 ( 3 ) 617 - 629 2006.2
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Protein homology detection using string alignment kernels
H Saigo, JP Vert, N Ueda, T Akutsu
BIOINFORMATICS 20 ( 11 ) 1682 - 1689 2004.7
Books
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Matrix Decomposition-based Dimensionality Reduction on Graph Data In Sakr, S. and Pardede, E. editors Graph Data Management: Techniques and Applications
（ Role： Joint author）
2011.1
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Graph Mining for Chemoinformatics In Lodhi, H and Yamanishi, Y. editors Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Method and Collaborative Technique
（ Role： Joint author）
2010.1
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Graph Classification In Sakr, C.C.C. and Wang, H. editors Managing and Mining Graph Data
（ Role： Joint author）
2010.1
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Graph Kernels for Chemoinformatics In Lodhi, H and Yamanishi, Y. editors Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Method and Collaborative Techniques
（ Role： Joint author）
2010.1
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Subash C Pakhrin, Suresh Pokharel, @Hiroto Saigo, Dukka B Kc（ Role： Joint author）
Springer 2022.6 （ ISSN:10643745 ）
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Local Alignment Kernels for Biological Sequences, In Bernhard Scheolkopf, Koji Tsuda and Jean-Philippe Vert editors, Kernel Methods in Computational Biology
（ Role： Joint author）
2004.1
Presentations
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Automatically mining relevant variable interactions via sparse Bayesian learning International conference
#Yafune, R., #Sakuma, D., Tabei, Y., @Saito, N., @Saigo, H.
International Conference on Pattern Recognition 2021.1
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Entire regularization path for sparse nonnegative interaction model International conference
#Takayanagi, M., Tabei, Y., Saigo, H.
International Conference on Data Mining (ICDM) 2018.11
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Towards predicting the epistasis in genome wide association study International conference
Saigo, H.
BMIRC2015 2015.3
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Towards predicting the epistasis in genome wide association study International conference
Saigo, H.
BMIRC2015 2015.3
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Mining and learning with structured data International conference
Saigo, H.
BIT2016 2016.3
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Reaction graph kernels that predict EC numbers of unknown enzymatic reactions in the secondary metabolism of plant International conference
Saigo, H., Hattori, M., Kashima, H., and Tsuda, K.
Asia Pacific Bioinformatics Conference (APBC2010) 2010.1
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KDE: a Kernel-based approach to detecting high-order genetic Epistasis International conference
Kodama, K., Saigo, H.
The 27th International Conference on Genome Informatics (GIW2016) 2016.10
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Optimization of amino acid substitution matrices by Gaussian process and sequence alignment
2023.9
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Improving the Efficiency of Auditory Brainstem Response Testing Using k-means
2023.9
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Benchmarking a wide range of unsupervised learning methods for detecting anomaly in blast furnace International conference
# Kendai Itakura, Dukka Bahadur KC, Hiroto Saigo
International Conference of Pattern Recognition Applications and Methods (ICPRAM2024) 2024.2
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A branch-and-bound approach to efficient classification and retrieval of documents International conference
# Kotaro Ii, Yasuo Tabei, Hiroto Saigo
International Conference of Pattern Recognition Applications and Methods (ICPRAM2024) 2024.4
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機械学習・深層学習を用いた高炉の教師なし異常検知
#板倉, @西郷
情報学的学習理論ワークショップ(IBIS2022) 2022.11
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深層学習を利用した高炉内の異常検知 International conference
#木崎亮介, @西郷浩人
情報学的学習理論ワークショップ 2022.6
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深層学習を利用した高炉内の異常検知
#木崎 亮介, @西郷 浩人
人工知能基本問題研究会 2021.3
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Context-Aware Latent Dirichlet Allocation for Topic SegmentationWenbo Li, Tetsu Matsukawa, Hiroto Saigo, Einoshin Suzuki: International conference
#Wenbo Li, Tetsu Matsukawa, Hiroto Saigo, Einoshin Suzuki
2020.5
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Bayesian Optimization for Sequence Data International conference
#Kohei Oyamada and Hiroto Saigo
10th International Conference on Bioscience, Biochemistry and Bioinformatics 2020.1
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A Sparse Bayesian Approach to Combinatorial Feature Selection and Its Applications to Biological Data International conference
#Ryoichiro Yafune, #Daisuke Sakuma, Yasuo Tabei, Noritaka Saito, Einoshin Suzuki and Hiroto Saigo
10th International Conference on Bioscience, Biochemistry and Bioinformatics 2020.1
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SVM-GlutarySite: A support vector machine-based prediction of Glutarylation sites from protein sequences International conference
Albarakati, H., Saigo, H., Newman, R.H., KC, D.B.
Joint GIW/ABACBS-2019 Bioinformatics Conference 2019.9
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変数間作用を考慮した非負スパースモデルの正則化経路探索
#高柳 未来1、田部井 靖生、@西郷 浩人
人工知能学会全国大会（第３３回） 2019.6
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アイテムセットを用いたスパースベイズ学習
#矢船 僚一朗、@西郷 浩人
人工知能学会全国大会（第３３回） 2019.6
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DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction International conference
Thapa, N., Chaudhari, M., McManus, S., Roy, K., Newman, R.H., Saigo, H., KC, D.B.
MCBIOS 2019.3
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Mining and Learning with Structured Data International conference
Hiroto Saigo
Japan America Germany Frontiers of Science Symposium 2017.9
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CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes International conference
2017.9
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Learning from treatment history to predict response to anti-HIV therapy
Saigo, H.
BMIRC2013 2013.2
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Mining discriminative patterns from graph data with multiple labels
Saigo, H.
BMIRC2014 2014.1
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Mining and learning with structured data
Saigo, H.
2016.1
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Multiple response regression for graph mining International conference
Saigo, H.
Department of Computing Seminar, Imperial College London 2013.10
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Multiple response regression for graph mining International conference
Saigo, H.
Friedrich Miescher Lab. Seminar 2013.11
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Protein Clustering on Grassman Manifold, Pattern Recognition in Bioinformatics International conference
Suryanto, C.H., Saigo, H., Fukui, K.
Pattern Recognition in Bioinformatics (PRIB2012) 2012.11
-
A Bayesian Approach to Graph Regression with Relevant Subgraph Selection International conference
Chiappa, S., Saigo, H. and Tsuda, K.
Siam International Conference on Data Mining (SDM2009) 2009.4
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Iterative Subgraph Mining for Principal Component Analysis International conference
Saigo, H. and Tsuda, K.
IEEE International Conference on Data Mining (ICDM2008) 2008.12
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Regression with Interval Output Values International conference
Kashima, H., Yamasaki, K., Saigo, H. and Inokuchi, A.
International Conference on Pattern Recognition (ICPR2008) 2008.1
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Partial Least Squares Regression for Graph Mining International conference
Saigo, H., Kraemer, N. and Tsuda, K.
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2008) 2008.8
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Reaction graph kernels for discovering missing enzymes in the plant secondary metabolism International conference
Saigo, H., M. Hattori and K. Tsuda:
NIPS Workshop on Machine Learning in Computational Biology, 2007.12
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Regression with Intervals International conference
Kashima, H., Yamazaki, K., Saigo, H. and Inokuchi, A.
International Workshop on Data-Mining and Statistical Science (DMSS2007) 2007.10
-
Graph boosting for molecular QSAR analysis International conference
Saigo, H., Kadowaki, T., Kudo, T. and Tsuda, K.
NIPS Workshop on Machine Learning in Computational Biology, 2006.12
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A Linear Programming Approach for Molecular QSAR analysis International conference
Saigo, H., Kadowaki, T. and Tsuda, K.
International Workshop on Mining and Learning with Graphs (MLG2006) 2006.9
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Introduction to Chemoinformatics
Saigo, H.
2015.1
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Pteris Vittata analysis report
Saigo, H.
2013.2
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Clustering approach to drug discovery International conference
Saigo, H.
Novartis Animal Health Department Seminar 2012.12
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Learn- ing from past treatments and their outcome improved prediction of in vivo response to anti-HIV therapy International conference
Saigo, H.
Ecole des Mines de Paris and Paris Tech in Paris Seminar 2010.2
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Incorporating detailed information on treatment history improves prediction of response to anti-HIV therapy International conference
Saigo, H.
Eidgenoesische Technische Hochschule (ETH) Zuerich Seminar 2009.12
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Incorporating detailed information on treatment history improves prediction of response to anti-HIV therapy International conference
Saigo, H.
Universitet van Amsterdam Seminar 2009.12
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Partial Least Squares Regression for Graph Mining International conference
Saigo, H.
Ecole des Mines de Paris and Paris Tech in Paris Seminar 2008.5
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A Linear Programming Approach for Molecular QSAR analysis International conference
Saigo, H.
Fraunhofer FIRST Seminar 2006.9
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Classification of chemical compounds using graph kernels
Saigo, H.
Information-Based Induction Science (IBIS) 2005 2005.10
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SNP間相互作用探索アルゴリズム
池田直人, 西郷浩人
第30回情報処理学会バイオ情報学研究会 2012.8
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カイ二乗検定によるｐ値の下限値を利用した遺伝子相互作用の効率的な数え上げ
山口拓郎, 西郷浩人
第42回バイオ情報学研究会 2015.6
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RF-NR: Random forest based approach for improved classification of Nuclear Receptors
Ismail, H.D., Saigo, H., Bahadur, K.C.D.
The 26th International Conference on Genome Informatics & International Conference on Bioinformatics (GIW/InCoB2015) 2015.9
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応答変数が連続値の際の組み合わせ仮説に対する多重検定補正法
井ノ口敬章, 永野竜輝, 西郷浩人
第103回人工知能基本問題研究会 2017.3
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Scalable Partial Least Squares Regression on Grammar- Compressed Data Matrices International conference
Tabei, Y., Saigo, H., Yamanishi, Y., Puglisi, S.
The 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD2016) 2016.8
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Mining and Learning with Structured Data, Japan America Germany Frontiers of Science Symposium Invited International conference
Japan America Germany Frontiers of Science Symposium 2017.9
MISC
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QSARモデルの構築; 機械学習と部分構造マイニングによるアプローチ
西郷 浩人
日本化学会情報化学部会誌 2013.7
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局所アラインメントカーネルを用いたアミノ酸置換行列の最適化
西郷 浩人, ジャンフィリップ・ヴェール, 阿久津 達也
情報処理学会研究報告数理モデル化と問題解決（MPS） 2006.3
Professional Memberships
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Japanese Society of Bioinformatics (JSBi)
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Japanese Society of Artificial Intelligence (JSAI)
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Japanese Society of Statistics (JSS)
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The Iron and Steel Institute of Japan (ISIJ)
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JAPANESE SOCIETY FOR BIOINFORMATICS
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THE JAPANESE SOCIETY FOR ARTIFICIAL INTELLIGENCE
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THE JAPAN STATISTICAL SOCIETY
Academic Activities
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Pattern Recognition International contribution
2023.12 - Present
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Screening of academic papers
Role(s)： Peer review
2023
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Screening of academic papers
Role(s)： Peer review
2022
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プログラム編集委員長
電気・情報関係学会九州支部連合大会 2021.9
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Screening of academic papers
Role(s)： Peer review
2021
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プログラム委員 International contribution
（ その他 ） 2020.12
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プログラム委員
生命医薬情報学連合大会 (IIBMP2020) （ その他 ） 2020.9
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プログラム委員 International contribution
（ その他 ） 2020.7
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Frontiers in Bioinformatics International contribution
2020.5 - Present
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Screening of academic papers
Role(s)： Peer review
2020
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プログラム委員 International contribution
2019.12
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プログラム委員 International contribution
2019.12
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プログラム委員
2019.11
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プログラム委員 International contribution
2019.6
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プログラム委員 International contribution
2019.4
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Screening of academic papers
Role(s)： Peer review
2019
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プログラム委員 International contribution
2018.12
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プログラム委員 International contribution
2018.12
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プログラム委員 International contribution
2018.10
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プログラム委員 International contribution
2018.4
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担当幹事
人工知能学会 人工知能基本問題研究会 （ 石垣島 ） 2018.1
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プログラム委員 International contribution
2018.1
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Screening of academic papers
Role(s)： Peer review
2018
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プログラム委員 International contribution
2017.12
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プログラム委員 International contribution
2017.11
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プログラム委員 International contribution
2017.4
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Screening of academic papers
Role(s)： Peer review
2017
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担当幹事
人工知能学会 人工知能基本問題研究会 （ 九州大学博多駅オフィス ） 2016.12
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座長（Chairmanship）
JSBi年会(2015) 2015.10
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座長（Chairmanship）
JSBi年会(2013) 2013.10
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座長（Chairmanship）
2012.11
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プログラム委員
JSBi年会(2015)
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プログラム委員 International contribution
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プログラム委員 International contribution
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プログラム委員 International contribution
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プログラム委員 International contribution
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プログラム委員 International contribution
-
プログラム委員 International contribution
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プログラム委員 International contribution
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プログラム委員 International contribution
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プログラム委員 International contribution
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プログラム委員 International contribution
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プログラム委員
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プログラム委員
JSBi年会(2013)
Research Projects
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機械学習による遺伝子、タンパク質、化合物の自動設計
2023.6
Authorship：Principal investigator
-
高レベル放射性廃棄物処理のための機械学習：高温多相融体の制御によるアプローチ
2023.4
Authorship：Principal investigator
-
高レベル放射性廃棄物処理のための機械学習：高温多相融体の制御によるアプローチ研究
Grant number：23H03356 2023 - 2027
日本学術振興会 科学研究費助成事業 基盤研究(B)
Authorship：Principal investigator Grant type：Scientific research funding
-
高炉操業の診断・予測方法の開発
2023
Grant type：Donation
-
A machine learning approach to automatic design of genes, proteins and chemical compounds
Grant number：22K19834 2022 - 2024
Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research Challenging Research(Exploratory)
Authorship：Principal investigator Grant type：Scientific research funding
-
スラグみえる化研究会
2022
Grant type：Donation
-
高炉操業の診断・予測方法の開発
2022
Grant type：Donation
-
高温酸化物サスペンションのレオロジー特性に及ぼす界面電気物性の影響
Grant number：21H01684 2021
日本学術振興会 科学研究費助成事業 基盤研究(B)
Authorship：Coinvestigator(s) Grant type：Scientific research funding
-
スラグみえる化研究会
2021
Grant type：Donation
-
高炉操業の診断・予測方法の開発
2021
Grant type：Donation
-
スラグみえる化研究会
2020
Grant type：Donation
-
高炉操業の診断・予測方法の開発
2020
Grant type：Donation
-
製造インフォマティクスに向けた機械学習技術の開発と鉄鋼製造における評価
2019.6 - 2022.6
Authorship：Principal investigator
-
Development of algorithms for manufacture informatics and its evaluation in steel industry
Grant number：19H04176 2019 - 2022
Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (B)
saigo hiroto
Authorship：Principal investigator Grant type：Scientific research funding
In the "Anomaly Detection in Blast Furnaces" problem, we have developed approaches using unsupervised learning based on the work of Itakura et al. (IBIS2022), and supervised learning based on the work of Kizaki (IBIS2021). In the supervised learning approach using CNN, we have confirmed that utilizing data from 5 to 15 minutes prior leads to improved accuracy.
<BR>
We have also developed a method for "Viscosity Prediction of High-Temperature States through Multi-Task Learning" as described in the study by Saigo et al. (Scientific Reports, 2022). In addition to robust extrapolation prediction, we have proposed a transfer learning method that leverages room temperature experimental data for high-temperature experiments. -
スラグみえる化研究会
2019
Grant type：Donation
-
高炉操業の診断・予測方法の開発
2019
Grant type：Donation
-
転移学習を利用した高温二相流体のレオロジー特性予測システム構築
2018.4 - 2020.3
Authorship：Coinvestigator(s)
-
転移学習を利用した高温二相流体のレオロジー特性予測システム構築
Grant number：18H01762 2018 - 2020
日本学術振興会 科学研究費助成事業 基盤研究(B)
Authorship：Coinvestigator(s) Grant type：Scientific research funding
-
転移学習を利用した高温二相流体のレオロジー特性予測システム構築継続中
2018 - 2020
日本学術振興会 科学研究費助成事業 基盤研究(C)
Grant type：Scientific research funding
-
構造データの学習とマイニング
2018
日本学術振興会 JSPS外国人招へい研究者
Authorship：Principal investigator Grant type：Joint research
-
高炉操業の診断・予測方法の開発
2018
Grant type：Donation
-
複数の遺伝要因及び環境要因の組み合わせを考慮したゲノムワイド相関解析法の開発
2017.3 - 2013.4
Authorship：Principal investigator
-
深層学習によるタンパク質分類法の開発
2017
スタートアップ支援
Authorship：Principal investigator Grant type：On-campus funds, funds, etc.
-
マルチモーダル多視点画像を用いたタンパク質立体構造の解析 研究課題
2013.4 - 2015.3
Authorship：Coinvestigator(s)
-
複数の遺伝要因及び環境要因の組み合わせを考慮したゲノムワイド相関解析法の開発
2013 - 2016
日本学術振興会 科学研究費助成事業 基盤研究(C)
Authorship：Principal investigator Grant type：Scientific research funding
-
複数の遺伝要因及び環境要因の組み合わせを考慮したゲノムワイド相関解析法の開発
Grant number：25700004 2013 - 2016
科学研究費助成事業 若手研究(A)
Authorship：Principal investigator Grant type：Scientific research funding
-
マルチモーダル多視点画像を用いたタンパク質立体構造の解析
Grant number：25540062 2013 - 2014
科学研究費助成事業 挑戦的萌芽研究
Authorship：Coinvestigator(s) Grant type：Scientific research funding
-
マルチモーダル多視点画像を用いたタンパク質立体構造の解析
2013 - 2014
日本学術振興会 科学研究費助成事業 基盤研究(C)
Grant type：Scientific research funding
-
全cDNA解析によるヒ素高蓄積植物土壌浄化システムの解析
2011.4 - 2012.3
Authorship：Coinvestigator(s)
-
大量のタンパク質リガンドデータより相互作用の構造的特徴をマイニングする方法の開発 研究課題
2011.4 - 2012.3
Authorship：Principal investigator
-
大量のタンパク質リガンドデータより相互作用の構造的特徴をマイニングする方法の開発
Grant number：23700338 2011 - 2013
科学研究費助成事業 若手研究(B)
Authorship：Principal investigator Grant type：Scientific research funding
-
大量のタンパク質リガンドデータより相互作用の構造的特徴をマイニングする方法の開発
2011 - 2012
日本学術振興会 科学研究費助成事業 基盤研究(C)
Authorship：Principal investigator Grant type：Scientific research funding
-
全cDNA解析によるヒ素高蓄積植物土壌浄化システムの解析
Grant number：23710085 2011 - 2012
科学研究費助成事業 若手研究(B)
Authorship：Coinvestigator(s) Grant type：Scientific research funding
-
全cDNA解析によるヒ素高蓄積植物土壌浄化システムの解析
2011 - 2012
日本学術振興会 科学研究費助成事業 基盤研究(C)
Grant type：Scientific research funding
Class subject
-
【通年】情報理工学研究Ⅰ
2024.4 - 2025.3 Full year
-
【通年】情報理工学講究
2024.4 - 2025.3 Full year
-
【通年】情報理工学演習
2024.4 - 2025.3 Full year
-
データ科学
2024.4 - 2024.9 First semester
-
情報理工学論議Ⅰ
2024.4 - 2024.9 First semester
-
情報理工学論述Ⅰ
2024.4 - 2024.9 First semester
-
情報理工学読解
2024.4 - 2024.9 First semester
-
サイバーセキュリティ基礎論
2024.4 - 2024.6 Spring quarter
-
機械学習特論Ⅱ
2023.12 - 2024.2 Winter quarter
-
Machine Learning II
2023.12 - 2024.2 Winter quarter
-
機械学習特論
2023.10 - 2024.3 Second semester
-
生物情報科学
2023.10 - 2024.3 Second semester
-
情報理工学論議Ⅱ
2023.10 - 2024.3 Second semester
-
情報理工学論述Ⅱ
2023.10 - 2024.3 Second semester
-
情報理工学演示
2023.10 - 2024.3 Second semester
-
機械学習特論Ⅰ
2023.10 - 2023.12 Fall quarter
-
Machine Learning I
2023.10 - 2023.12 Fall quarter
-
国際演示技法Ⅰ
2023.4 - 2024.3 Full year
-
【通年】情報理工学講究
2023.4 - 2024.3 Full year
-
【通年】情報理工学演習
2023.4 - 2024.3 Full year
-
【通年】情報理工学研究Ⅰ
2023.4 - 2024.3 Full year
-
Advanced Project Management II
2023.4 - 2024.3 Full year
-
Advanced Project Management I
2023.4 - 2024.3 Full year
-
Exercise in Teaching II
2023.4 - 2024.3 Full year
-
Exercise in Teaching I
2023.4 - 2024.3 Full year
-
Intellectual Property Management II
2023.4 - 2024.3 Full year
-
Intellectual Property Management I
2023.4 - 2024.3 Full year
-
Scientific English Presentation II
2023.4 - 2024.3 Full year
-
Scientific English Presentation I
2023.4 - 2024.3 Full year
-
先端プロジェクト管理技法Ⅱ
2023.4 - 2024.3 Full year
-
先端プロジェクト管理技法Ⅰ
2023.4 - 2024.3 Full year
-
ティーチング演習Ⅱ
2023.4 - 2024.3 Full year
-
ティーチング演習Ⅰ
2023.4 - 2024.3 Full year
-
知的財産技法Ⅱ
2023.4 - 2024.3 Full year
-
知的財産技法Ⅰ
2023.4 - 2024.3 Full year
-
国際演示技法Ⅱ
2023.4 - 2024.3 Full year
-
国際演示技法Ⅰ
2023.4 - 2024.3 Full year
-
Advanced Seminar in Information Science and Technology
2023.4 - 2024.3 Full year
-
Advanced Research in Information Science and Technology II
2023.4 - 2024.3 Full year
-
Advanced Research in Information Science and Technology I
2023.4 - 2024.3 Full year
-
情報理工学特別演習
2023.4 - 2024.3 Full year
-
情報理工学特別研究Ⅱ
2023.4 - 2024.3 Full year
-
情報理工学特別研究Ⅰ
2023.4 - 2024.3 Full year
-
Advanced Research in Data Science
2023.4 - 2024.3 Full year
-
データサイエンス特别講究
2023.4 - 2024.3 Full year
-
Advanced Project Management II
2023.4 - 2024.3 Full year
-
Advanced Project Management I
2023.4 - 2024.3 Full year
-
Exercise in Teaching II
2023.4 - 2024.3 Full year
-
Exercise in Teaching I
2023.4 - 2024.3 Full year
-
Intellectual Property Management II
2023.4 - 2024.3 Full year
-
Intellectual Property Management I
2023.4 - 2024.3 Full year
-
Scientific English Presentation II
2023.4 - 2024.3 Full year
-
Scientific English Presentation I
2023.4 - 2024.3 Full year
-
先端プロジェクト管理技法Ⅱ
2023.4 - 2024.3 Full year
-
先端プロジェクト管理技法Ⅰ
2023.4 - 2024.3 Full year
-
ティーチング演習Ⅱ
2023.4 - 2024.3 Full year
-
ティーチング演習Ⅰ
2023.4 - 2024.3 Full year
-
知的財産技法Ⅱ
2023.4 - 2024.3 Full year
-
知的財産技法Ⅰ
2023.4 - 2024.3 Full year
-
国際演示技法Ⅱ
2023.4 - 2024.3 Full year
-
データ科学
2023.4 - 2023.9 First semester
-
情報理工学論議Ⅰ
2023.4 - 2023.9 First semester
-
情報理工学論述Ⅰ
2023.4 - 2023.9 First semester
-
情報理工学読解
2023.4 - 2023.9 First semester
-
機械学習特論Ⅱ
2022.12 - 2023.2 Winter quarter
-
Machine Learning II
2022.12 - 2023.2 Winter quarter
-
機械学習特論
2022.10 - 2023.3 Second semester
-
Machine Learning
2022.10 - 2023.3 Second semester
-
情報理工学論議Ⅱ
2022.10 - 2023.3 Second semester
-
情報理工学論述Ⅱ
2022.10 - 2023.3 Second semester
-
情報理工学演示
2022.10 - 2023.3 Second semester
-
情報科学講究
2022.10 - 2023.3 Second semester
-
生物情報科学
2022.10 - 2023.3 Second semester
-
国際科学特論Ⅱ
2022.10 - 2022.12 Fall quarter
-
Machine Learning I
2022.10 - 2022.12 Fall quarter
-
機械学習特論Ⅰ
2022.10 - 2022.12 Fall quarter
-
基幹教育セミナー
2022.6 - 2022.8 Summer quarter
-
国際演示技法
2022.4 - 2023.3 Full year
-
Advanced Seminar in Informatics
2022.4 - 2023.3 Full year
-
Advanced Research in Informatics II
2022.4 - 2023.3 Full year
-
Advanced Research in Informatics I
2022.4 - 2023.3 Full year
-
情報学特別演習
2022.4 - 2023.3 Full year
-
情報学特別講究第二
2022.4 - 2023.3 Full year
-
情報学特別講究第一
2022.4 - 2023.3 Full year
-
Advanced Research in Data Science
2022.4 - 2023.3 Full year
-
データサイエンス特别講究
2022.4 - 2023.3 Full year
-
Advanced Project Management Technique
2022.4 - 2023.3 Full year
-
Exercise in Teaching
2022.4 - 2023.3 Full year
-
Intellectual Property Management
2022.4 - 2023.3 Full year
-
Scientific English Presentation
2022.4 - 2023.3 Full year
-
先端プロジェクト管理技法
2022.4 - 2023.3 Full year
-
ティーチング演習
2022.4 - 2023.3 Full year
-
知的財産技法
2022.4 - 2023.3 Full year
-
情報理工学研究Ⅰ
2022.4 - 2023.3 Full year
-
情報理工学講究
2022.4 - 2023.3 Full year
-
情報理工学演習
2022.4 - 2023.3 Full year
-
データ科学
2022.4 - 2022.9 First semester
-
情報理工学論議Ⅰ
2022.4 - 2022.9 First semester
-
情報理工学論述Ⅰ
2022.4 - 2022.9 First semester
-
情報理工学読解
2022.4 - 2022.9 First semester
-
電気情報工学入門
2022.4 - 2022.6 Spring quarter
-
サイバーセキュリティ基礎論
2022.4 - 2022.6 Spring quarter
-
(IUPE)Data Structure and Algorithms IB
2021.12 - 2022.2 Winter quarter
-
Machine Learning II
2021.12 - 2022.2 Winter quarter
-
機械学習特論Ⅱ
2021.12 - 2022.2 Winter quarter
-
機械学習特論
2021.10 - 2022.3 Second semester
-
情報理工学演示
2021.10 - 2022.3 Second semester
-
生物情報科学
2021.10 - 2022.3 Second semester
-
情報科学講究
2021.10 - 2022.3 Second semester
-
Machine Learning
2021.10 - 2022.3 Second semester
-
情報学論議Ⅱ
2021.10 - 2022.3 Second semester
-
情報学論述Ⅱ
2021.10 - 2022.3 Second semester
-
(IUPE)Data Structure and Algorithms IA
2021.10 - 2021.12 Fall quarter
-
Machine Learning I
2021.10 - 2021.12 Fall quarter
-
機械学習特論Ⅰ
2021.10 - 2021.12 Fall quarter
-
国際演示技法
2021.4 - 2022.3 Full year
-
情報学特別講究第二
2021.4 - 2022.3 Full year
-
情報学特別講究第一
2021.4 - 2022.3 Full year
-
Advanced Research in Data Science
2021.4 - 2022.3 Full year
-
データサイエンス特别講究
2021.4 - 2022.3 Full year
-
Advanced Project Management Technique
2021.4 - 2022.3 Full year
-
Exercise in Teaching
2021.4 - 2022.3 Full year
-
Intellectual Property Management
2021.4 - 2022.3 Full year
-
Scientific English Presentation
2021.4 - 2022.3 Full year
-
先端プロジェクト管理技法
2021.4 - 2022.3 Full year
-
ティーチング演習
2021.4 - 2022.3 Full year
-
知的財産技法
2021.4 - 2022.3 Full year
-
情報学特別演習
2021.4 - 2022.3 Full year
-
[M2]情報学講究
2021.4 - 2022.3 Full year
-
情報理工学演習
2021.4 - 2022.3 Full year
-
情報理工学研究Ⅰ
2021.4 - 2022.3 Full year
-
情報学演習
2021.4 - 2022.3 Full year
-
Advanced Seminar in Informatics
2021.4 - 2022.3 Full year
-
Advanced Research in Informatics II
2021.4 - 2022.3 Full year
-
Advanced Research in Informatics I
2021.4 - 2022.3 Full year
-
データ科学
2021.4 - 2021.9 First semester
-
[M2]情報学論議Ⅰ
2021.4 - 2021.9 First semester
-
[M2]情報学論述Ⅰ
2021.4 - 2021.9 First semester
-
情報理工学読解
2021.4 - 2021.9 First semester
-
(IUPE)Data Structure and Algorithms IB
2020.12 - 2021.2 Winter quarter
-
【修士】機械学習特論
2020.10 - 2021.3 Second semester
-
Machine Learning
2020.10 - 2021.3 Second semester
-
【博士】機械学習特論
2020.10 - 2021.3 Second semester
-
情報学論議Ⅱ
2020.10 - 2021.3 Second semester
-
情報学論述Ⅱ
2020.10 - 2021.3 Second semester
-
情報学演示
2020.10 - 2021.3 Second semester
-
(IUPE)Data Structure and Algorithms IA
2020.10 - 2020.12 Fall quarter
-
国際演示技法
2020.4 - 2021.3 Full year
-
Advanced Project Management Technique
2020.4 - 2021.3 Full year
-
Exercise in Teaching
2020.4 - 2021.3 Full year
-
Intellectual Property Management
2020.4 - 2021.3 Full year
-
Scientific English Presentation
2020.4 - 2021.3 Full year
-
先端プロジェクト管理技法
2020.4 - 2021.3 Full year
-
ティーチング演習
2020.4 - 2021.3 Full year
-
知的財産技法
2020.4 - 2021.3 Full year
-
データサイエンス特别講究
2020.4 - 2021.3 Full year
-
Advanced Seminar in Informatics
2020.4 - 2021.3 Full year
-
Advanced Research in Informatics II
2020.4 - 2021.3 Full year
-
Advanced Research in Informatics I
2020.4 - 2021.3 Full year
-
情報学特別演習
2020.4 - 2021.3 Full year
-
情報学特別講究第二
2020.4 - 2021.3 Full year
-
情報学特別講究第一
2020.4 - 2021.3 Full year
-
Advanced Research in Data Science
2020.4 - 2021.3 Full year
-
データ科学
2020.4 - 2020.9 First semester
-
【修士】機械学習特論
2019.10 - 2020.3 Second semester
-
生物情報科学
2019.10 - 2020.3 Second semester
-
【博士】機械学習特論
2019.10 - 2020.3 Second semester
-
情報学論議Ⅱ
2019.10 - 2020.3 Second semester
-
情報学論述Ⅱ
2019.10 - 2020.3 Second semester
-
情報学演示
2019.10 - 2020.3 Second semester
-
(IUPE)Data Structure and Algorithms I
2019.10 - 2019.12 Fall quarter
-
情報学演習
2019.4 - 2020.3 Full year
-
情報学講究
2019.4 - 2020.3 Full year
-
データ科学
2019.4 - 2019.9 First semester
-
情報学論議Ⅰ
2019.4 - 2019.9 First semester
-
情報学論述Ⅰ
2019.4 - 2019.9 First semester
-
情報学読解
2019.4 - 2019.9 First semester
-
機械学習特論
2018.10 - 2019.3 Second semester
-
生物情報科学
2018.10 - 2019.3 Second semester
-
情報学読解
2018.4 - 2018.9 First semester
-
情報学論議Ⅰ
2018.4 - 2018.9 First semester
-
情報学論述Ⅰ
2018.4 - 2018.9 First semester
-
サイバーセキュリティ基礎論
2018.4 - 2018.6 Spring quarter
-
情報学演示
2017.10 - 2018.3 Second semester
-
情報学論議Ⅱ
2017.10 - 2018.3 Second semester
-
情報学論述Ⅱ
2017.10 - 2018.3 Second semester
-
情報学読解
2017.4 - 2017.9 First semester
-
高度プログラミング
2017.4 - 2017.9 First semester
-
情報学論議Ⅰ
2017.4 - 2017.9 First semester
-
情報学論述Ⅰ
2017.4 - 2017.9 First semester
-
生物情報科学
2016.10 - 2017.3 Second semester
-
データ科学
2016.4 - 2016.9 First semester
FD Participation
-
2023.5 Role：Participation Title：【シス情FD】農学研究院で進めているDX教育について
Organizer：[Undergraduate school/graduate school/graduate faculty]
-
2023.3 Role：Participation Title：【シス情FD】独・蘭・台湾での産学連携を垣間見る-Industy 4.0・量子コンピューティング・先端半導体-
Organizer：[Undergraduate school/graduate school/graduate faculty]
-
2022.6 Role：Participation Title：【シス情FD】電子ジャーナル等の今後について
Organizer：[Undergraduate school/graduate school/graduate faculty]
-
2022.5 Role：Participation Title：【シス情FD】若手教員による研究紹介④「量子コンピュータ・システム・アーキテクチャの研究～道具になることを目指して～」
Organizer：[Undergraduate school/graduate school/graduate faculty]
-
2022.3 Role：Participation Title：全学FD:メンタルヘルス講演会
Organizer：University-wide
-
2022.1 Role：Participation Title：【シス情FD】シス情関連の科学技術に対する国の政策動向（に関する私見）
Organizer：[Undergraduate school/graduate school/graduate faculty]
-
2021.10 Role：Participation Title：【シス情FD】熊本高専と九大システム情報との交流・連携に向けて ー 3年半で感じた高専の実像 ー
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2021.9 Role：Participation Title：博士後期課程の充足率向上に向けて
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2021.5 Role：Participation Title：先導的人材育成フェローシップ事業(情報・AI分野)について
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2020.12 Role：Participation Title：令和２年度 第２回工学部ＦＤ（１日目） 総合型選抜の実施に向けて―面接の全般的な内容（注意事項、採点方法など）
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2020.11 Role：Participation Title：マス・フォア・イノベーション卓越大学院について
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2020.9 Role：Participation Title：電気情報工学科総合型選抜（AO入試）について
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2019.10 Role：Participation Title：電子ジャーナルの現状と今後の動向に関する説明会
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2019.6 Role：Participation Title：8大学情報系研究科長会議の報告
Organizer：[Undergraduate school/graduate school/graduate faculty]
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2016.6 Role：Participation Title：【全学ＦＤ(第2回)】教育の質向上支援プログラム（EEP）成果発表会
Organizer：University-wide
Visiting, concurrent, or part-time lecturers at other universities, institutions, etc.
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2022 理化学研究所革新的人工知能研究センター Classification:Affiliate faculty Domestic/International Classification:Japan
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2021 理化学研究所革新的人工知能研究センター Classification:Affiliate faculty Domestic/International Classification:Japan
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2020 理化学研究所 Classification:Affiliate faculty Domestic/International Classification:Japan
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2019 京都大学 Classification:Affiliate faculty Domestic/International Classification:Japan
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2019 東京大学 Classification:Part-time lecturer Domestic/International Classification:Japan
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2016 鹿児島大学 Classification:Part-time lecturer Domestic/International Classification:Japan
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2016 九州工業大学 Classification:Part-time lecturer Domestic/International Classification:Japan
Other educational activity and Special note
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2023 Class Teacher
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2022 Class Teacher
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2020 Class Teacher
Acceptance of Foreign Researchers, etc.
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North Carolina A&T State Univeristy
Acceptance period： 2018.6 - 2018.7 （Period）：1 month or more
Nationality：United States
Business entity：Japan Society for the Promotion of Science
Travel Abroad
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2008.7 - 2010.3
Staying countory name 1：Germany Staying institution name 1：Max Planck Institute for Informatics
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2006.6 - 2008.6
Staying countory name 1：Germany Staying institution name 1：Max Planck Institute for Biological Cybernetics
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2003.8 - 2004.8
Staying countory name 1：United States Staying institution name 1：University of California, Irvine