講演（国外）

Presentation

2024

2024.1.Physics informed Artificial Intelligence in Plasma Science, online seminar, “Bayesian kernel regression for functional data” （Minoru Kusaba）[WEB]
2024.1.The 27th SANKEN International Symposium, online seminarHyogo, Japan, “Beyond Data Limits: Innovations in Data-Driven Materials Science” （Ryo Yoshida）[WEB]

2023

2023.12.Thirty-seventh Conference on Neural Information Processing Systems, New Orleans, USA, “Transfer Learning with Affine Model Transformation”, (Shunya Minami*, Kenji Fukumizu, Yoshihiro Hayashi, Ryo Yoshida) [WEB]
2023.12.The 3rd Materials Research Meeting (MRM 2023), Kyoyo, Japan, “Non-iterative crystal structure prediction”, (Ryo Yoshida, Chang Liu, Hiromasa Tamaki, Tomoyasu Yokoyama, Kensuke Wakasugi, Satoshi Yotsuhashi, Minoru Kusaba) [WEB]
2023.9.International Conference on Complex Orders in Condensed Matter (ICCOCM 2023), Evian, France, “Exploring semiconductor quasicrystals with machine learning”, (Minoru Kusaba*, Chang Liu, Erina Fujita, Yukari Katsura, Kaoru Kimura, Ryo Yoshida) [Poster session] [WEB]
2023.9.International Conference on Complex Orders in Condensed Matter (ICCOCM 2023), Evian, France, “Machine learning for quasicrystals”, (Ryo Yoshida) [WEB]
2023.8.International Symposium on Living Systems Materialogy, Kanagawa, Japan, “Exploring vast material landscapes using artificial intelligence”, (Ryo Yoshida)
2023.4.The 4th International Conference on Data-Driven Plasma Science (ICDDPS-4), Okinawa, Japan, “Machine learning for overcoming data scarcity”, (Ryo Yoshida) [WEB]
2023.3.TMS 2023 Annual Meeting & Exhibition, CA, USA, “XenonPy: an open source platform for data-driven materials design with small data”, (Wu Stephen) [WEB]

2022

2022.12.The 17th Pacific Polymer Conference (PPC17), Brisbane, Australia, “Development of an automated polymer property calculation system “RadonPy” and data platform co-creation through industry-academia collaboration”, (Yoshihiro Hayashi*, Yoh Noguchi, Aiko Takahashi, Stephen Wu, Ryo Yoshida) [WEB]
2022.12.The 17th Pacific Polymer Conference (PPC17), Brisbane, Australia, “Design of liquid-crystalline polyimides by integrating expert knowledge to a data-driven machine learning framework”, (Stephen Wu*, Hayato Maeda, Rika Marui, Erina Yoshida, Yuta Nabae, Teruaki Hayakawa, Yoh Noguchi, Yoshihiro Hayashi, Ryo Yoshida) [WEB]
2022.12.5th G’L’owing Polymer Symposium in KANTO (GPS-K2022), online seminar, “Multitask machine learning for prediction and understanding of polymer-solvent solubility” （Yuta Aoki, Teruki Tsurimoto, Tadamichi Okubo, Stephen Wu, Yoshihiro Hayashi, Shunya Minami, Kazuya Shiratori, Ryo Yoshida）[WEB]
2022.11.The 23rd Asian Workshop on First-Principles Electronic Structure Calculations (ASIAN-23), online seminar, “Development of an automated polymer property calculation system “RadonPy” and data platform co-creation through industry-academia collaboration”, (Y. Hayashi) [WEB]
2022.9.ACS Fall 2022 (Division of Polymer Chemistry), Chicago, US, “Data-driven design and synthesis of new liquid crystal polyimides”, (W. Stephen) [WEB]
2022.7.Conference on a FAIR Data Infrastructure for Materials Genomics 2022, online seminar, “Challenges and opportunities in polymer informatics from a statistical perspective”, (W. Stephen) [WEB]
2022.6.Aperiodic 2022(10th International Conference on Aperiodic Crystals), Sapporo, Japan, “Using machine learning to discover quasicrystals”, (R. Yoshida) [WEB]
2022.4.2022 SIAM International Conference on Data Mining, online seminar, “Statistical machine learning for materials modeling and simulation”, (R. Yoshida) (invited) [WEB]
2022.1.PiAI Seminar, online seminar, “Scientific understanding from machine learning in materials Sscience”, (R. Yoshida) [WEB]

2021

2021.12.Materials Research Meeting 2021, Yokohama, Japan, “Experimental datasets of compositions, physical properties, and phase regions for quasicrystals and their approximants”, (E. Fujita*, L. Chang, R. Yoshida, Y. Katsura, K. Kimura) [WEB]
2021.12.Materials Research Meeting 2021, Yokohama, Japan, “Machine learning phase prediction of quasicrystals”, (R. Yoshida) [WEB]
2021.9.International Conference on Flexible and Printed Electronics, online seminar, “Machine learning for inverse materials design” (R. Yoshida) (invited) [WEB]
2021.6.1st International School on Hypermaterials, online seminar, “Introduction to hypermaterials informatics” (R. Yoshida) (invited) [WEB]

2020

2020.10.Bristol-ISM Data Science Seminar Series, online seminar, “Machine learning for materials discovery”, (R. Yoshida).
2020.1.2020 I2CNER-IMI International workshop on applied math for energy, Fukuoka, Japan, “Materials informatics: state-of-the-art and future perspectives”, (R. Yoshida).

2019

2019.12.Materials Research Meeting 2019 (MRM2019) , Yokohama, Japan, “Breaking the curse of small data in materials informatics”, (R. Yoshida).
2019.7.The 4th Eastern Asia Chapter Meeting on Bayesian Statistics(EAC-ISBA2019) , Kobe, Japan, “Bayesian methods and their applications”, (R. Yoshida).
2019.5.2nd International Conference on Data Driven Plasma Science (2ndICDDPS) , Marseille, France, “Machine learning for materials design and discovery: how do we learn from little?”,（R. Yoshida).
2019.2.ICMMA2018 , Tokyo, Japan, “Machine learning for accelerated materials discovery”,（R. Yoshida).

2018

2018.10. 10th International Workshop on Combinatorial Materials Science and Technology (COMBI2018) , Yokohama, Japan, “Accelerated materials discovery powered by machine learning”,（R. Yoshida).
2018.8. The 10th MEI3 Center International Symposium , Suita, Japan, “Frontiers of applied Bayesian inference”,（R. Yoshida).
2018.5. 6th International IBM Cloud Academy Conference 2018 (ICA CON 2018) , Tokyo, Japan, “Materials Informatics: State-of-the-Art and Future Perspectives”,（R. Yoshida).
2018.3. 255th ACS National Meeting & Exposition , New Orleans, USA, “Inverse design of novel polymeric materials through Bayesian machine learning and experimental design algorithms”,（R. Yoshida).

2017

2017.11. Advances in Neuroinformatics (AINI 2017) , Tsukuba, Japan, “Materials Informatics: an emerging interdisciplinary field of materials science”,（R. Yoshida).
2017.11. The 16th International Symposium on Molecular and Neural Mechanisms of Taste and Olfactory Perception , Fukuoka, Japan, “How taste preference is modulated in the nematode”,（Y. Iino*, T. Nagashima, H. Sato, MS. Jang, S. Oe, Y. Toyoshima, M. Tomioka, H. Kunitomo, S. Wu, R. Yoshida, Y. Iwasaki, T. Ishihara).
2017.4. International Workshop on Quantitative Biology 2017 , Yokohama, Japan, “Whole neural network analysis of C. elegans using an automated image processing pipeline”,（S. Wu). (invited)
2017.4. International Workshop of Materials Informatics and Materials Data (MIMD) , Tsukuba, Japan, “Inverse design of functional materials:advanced machine learning techniques coupled to computational experiments”, (G. Lambard*, S. Wu, R. Yoshida). (invited)
2017.3.Simulations Encounter with Data Science Data Assimilation,Emulators, Rare Events and Design , Tachikawa, Japan, “Inverse design of functional materials through computer experiments and machine learning”, (R. Yoshida). (invited)
2017.1.ISM-ZIB-IMI Joint Workshop on Optimization and Data-intensive High Performance Computing , Tokyo, Japan, “Inverse design of functional materials through computer experiments and machine learning”, (R. Yoshida). ( invited)

2016

2016.10.BioImage Informatics Conference 2016 , Singapore, “A machine learning pipeline for whole brain imaging of Caenorhabditis elegans: cell tracking, quantification, annotation and visualizations”, (S. Wu*, T. Tokunaga, O. Hirose, Y. Toyoshima, T. Teramoto, Y. Iwasaki, T. Ishihara, Y. Iino, R. Yoshida).
2016.7.Seventh Joint Sheffield Conference on Chemoinformatics (SHEFFIELD 2016) , Sheffield, UK, “A Bayesian algorithm for finding novel small organic molecules”, (R. Yoshida*, H. Ikebata, K. Hongo, R. Maezono, T. Isomura).
2016.2.Waseda International Symposium, Tokyo, Japan, “Bayesian approach towards data science driven materials discovery”, (R. Yoshida). (invited)

2015

2015.10.BioImage Informatics Conference 2015 , Gaithersburg, USA, “SPF-CellTracker: Tracking multiple cells with strongly-correlated moves using a spatial particle filter”, (O. Hirose*, S. Kawaguchi, T. Tokunaga, T. Teramoto, S. Kuge, T. Ishihara, Y. Toyoshima, Y. Iino, R. Yoshida).
2015.9.GIW/InCoB 2015 , Tokyo, Japan, “SPF-CellTracker: Tracking multiple cells with strongly-correlated moves using a spatial particle filter”, (O. Hirose*, S. Kawaguchi, T. Tokunaga, T. Teramoto, S. Kuge, T. Ishihara, Y. Toyoshima, Y. Iino, R. Yoshida).
2015.3.Wiring the Brain , New York, USA, “Whole-brain imaging of C. elegans reveals multi-neuronal dynamics under non-stimulus condition”, (T. Teramoto*, T. Tokunaga, O. Hirose, Y. Toyoshima, Y. Iino, R. Yoshida, T. Ishihara).

2014

2014.7.C.elegans Topic Meeting: Neuronal Development, Synaptic Function & Behavior , Madison, USA, “4-D imaging of neuronal activities in the whole central nervous system visualizes correlative patterns between multiple neuron”, (T. Teramoto*, Y. Toyoshima, T. Tokunaga, R. Yoshida, Y. Iino, T. Ishihara).
2014.7.22nd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2014) , Boston, USA, “Automated detection and tracking of many cells by using 4D live-cell imaging data”, (T. Tokunaga*, O. Hirose, S. Kawaguchi, Y. Toyoshima, T. Teramoto, H. Ikebata, S. Kuge, T. Ishihara, Y. Iino, R. Yoshida).
2014.1.Cooperation of Computation Materials Science and Mathematics toward Smart Materials Design , Tokyo, Japan, “Bayesian statistics for data assimilation”, (R. Yoshida). (invited)

2013

2013.11.Forum “Math-for-Industry” 2013 , Fukuoka, Japan, “Bayesian statistics for designing systems, molecules and others”, (R. Yoshida). (invited)
2013.8.Joint Statistical Meeting 2013 , Montreal, Canada, “Preimage reconstruction of molecules with a graph kernel”, (R. Yoshida*, H. Yamashita, Y. Iba, T. Higuchi).
2013.8.Joint Statistical Meeting 2013 , Montreal, Canada, “Repulsive parallel MCMC for motif discovery”, (H. Ikebata*, R. Yoshida).

2012

2012.6.ISBA 2012, Kyoto, Japan, “Bayesian sparse reconstruction: Latent factor analysis of gene regulatory programs”, (R. Yoshida).
2012.6.BayesComp 2012 , Tokyo, Japan, “Bayesian robust networking”, (R. Yoshida). ( invited)

2011

2011.12.Joint Meeting of The 2011 Taipei International Statistical Symposium and 7th Conference of The Asian Regional Section of the IASC (YIRCoBL 2011), Taipei, Taiwan, “Bayesian supercomputing tackles cancers”, (R. Yoshida).
2011.6. Yeditepe International Research Conference on Bayesian Learning (YIRCoBL 2011) , Istanbul, Turky, “Dynamic Bayesian modelling of biological pathways and decoupling of hidden regulatory signals using nonlinear state space models”, (R. Yoshida*, H. Nagao, M. Saito, T. Higuchi).
2011.6. Yeditepe International Research Conference on Bayesian Learning (YIRCoBL 2011) , Istanbul, Turky, ” Hybrid Bayesian filter algorithm for multivariate time-series modellings on cloud computing systems”, (H. Nagao*, R. Yoshida, T. Higuchi).

2010

2010.9. 9th European Conference on Computational Biology (ECCB 2010) , Ghent, Belgium, “Bayesian experts in exploring reaction kinetics of transcription circuits”, (R. Yoshida*, M. Saito, H. Nagao, and T. Higuchi).
2010.9. 2010 Asia-Pacific Radio Science Conference (AP-RASC’10) , Toyama, Japan, “Easy and simple methods to estimate parameter values in the numerical simulation model for sequential data assimilation”, (T. Higuchi*, R. Yoshida).
2010.8.13th International Conference on Information Fusion (FUSION 2010) , Edinburgh, UK, “Implementation of sequential importance sampling in GPGPU”, (K. Hayashi, M. Saito*, R. Yoshida, T. Higuchi).

2009

2009.8. 2009 Joint Statistical Meetings (JSM 2009) , Washington, DC, USA, “Sparse Bayes learning by annealing entropy”, (R. Yoshida*, M. West).

2008

2008.8. 9th International Conference on Systems Biology (ICSB 2008), Gothenburg, Sweden, “Exploring biological processes with pathway simulations by data assimilation approach”, (R. Yamaguchi*, R. Yoshida, M. Nagasaki, S. Imoto, T. Shimamura, M. Yamauchi, T. Higuchi, N. Gotoh, S. Miyano). (invited)
2008.6. International Conference on Multivariate Statistical Modelling & High Dimensional Data Mining (HDM) 2008 , Kayseri, Turkey, “Mixed factors analysis: unsupervized statistical discrimination with kernel feature extraction”, (R. Yoshida). ( invited)
2008.5.2nd Asia International Conference on Modelling & Simulation , Malaysia, “Analyzing time course gene expression data with biological and technical replicates to estimate gene networks by state space models”, (O. Hirose, R. Yoshida, R. Yamaguchi, S. Imoto*, T. Higuchi, S. Miyano).

2007

2007.11.Workshop on Destruction: Mathematical Modeling of Tsunami Waves and Cracks Propagation (The 21th Century COE Program, Center for Integrative Mathematical Sciences, Faculty of Science and Technology, Keio University; Yokohama, Japan, “Statistical inference of biological molecular network on genomic data assimilation”, (R. Yoshida). ( invited)
2007.11. The 1st Joint Meeting between Institute of Statistical Science, Academia Sinica and the Institue of Statistical Mathematics , Tokyo, Japan, “Genomic data assimilation for inferring gene regulatory networks from gene expression profiles”, (R. Yoshida).
2007.11.International Workshop on the Interface between Statistical Causal Inference and Bayesian Networks , Tokyo, Japan, “Bayesian learning of biological pathways on genomic data assimilation”, (R. Yoshida). (invited)
2007.10. IEEE 7th International Symposium on Bioinformatics and Bioengineering (BIBE) 2007 , Boston, USA, “Computational genome-wide discovery of aberrant splice variations with exon expression profiles”, (R. Yoshida*, K. Numata, S. Imoto, M. Nagasaki, A. Doi, K. Ueno, S. Miyano).
2007.10.The International Workshop on Data-Mining and Statistical Science (DMSS) 2007 , Tokyo, Japan, “Mixed factors analysis: unsupervized statistical discrimination with kernel feature extraction”, (R. Yoshida*, T. Higuchi, S. Imoto, S. Miyano).
2007.8. IEEE Statistical Signal Processing Workshop , Madison, USA, “Identification of module-based gene networks from time course gene expression profiles with state space models”, (R. Yamaguchi). (invited)
2007.7. The Seventh Annual International Workshop on Bioinformatics andSystems Biology (IBSB2007) , Tokyo, Japan, “Clustering with time course gene expression profiles and the mixture of state space models “, (O. Hirose*, R. Yoshida, R. Yamaguchi, S. Imoto, T. Higuchi, S. Miyano).
2007.7. The Seventh Annual International Workshop on Bioinformatics and Systems Biology (IBSB2007) , Tokyo, Japan, “Identification of activated transcription factors from microarray gene expression data of Kampo-medicine treated mice”, (R. Yamaguchi*, M. Yamamoto, S. Imoto, M. Nagasaki, R. Yoshida, K. Tsuji, A. Ishige, H. Asou, K. Watanabe, S. Miyano).
2007.6.The 2007 IASC-ARS Special Coference, Seoul, Korea, “Identification of module-based gene networks from time course gene expression profiles with state space models”, (O. Hirose*, R. Yoshida, R. Yamaguchi, S. Imoto, T. Higuchi, S. Miyano).
2007.5.The International Symposium on Bioinformatics Research and Applications (ISBRA2007), Atlanta, USA, “Statistical absolute evaluation of gene ontology terms with gene expression data”, (P.K. Gupta, R. Yoshida*, S. Imoto, R. Yamaguchi, S. Miyano)

2006

2006.12.The 16th International Conference on Genome Informatics (GIW2005), Yokohama, Japan, ” Modeling and estimation of dynamic EGFR pathway by data assimulation approach using time series proteomic data”, (S. Tasaki*, M. Nagasaki, M. Oyama, H. Hata, K. Ueno, R. Yoshida, T. Higuchi, S. Sugano, S. Miyano).
2006.9.International Workshop on Data-Mining and Statistical Science (DMSS2006), Sapporo, Japan, “Unsupervised learning of n<<p data and its application to bioinformatics”, (R. Yoshida*, S. Imoto, T. Higuchi S. Miyano).(invited)
2006.7.International Workshop on Bioinformatics and System Biology, USA, “A statistical framework for genome-wide discovery of biomarker splice variations with GeneChip Human Exon 1.0 ST arrays”, (R. Yoshida, K. Numata*, S. Imoto, M. Nagasaki, A. Doi, K. Ueno, S. Miyano).
2006.7.International Workshop on Bioinformatics and System Biology, USA, “Genomic data assimilation for estimating Hybrid Functional Petri Net from time-course gene expression data”, (M. Nagasaki, R. Yamaguchi*, R. Yoshida, S. Imoto, A. Doi, Y,Tamada, H. Matsuno, S. Miyano, T. Higuchi).
2006.3.Affymetrix Data Analysis Workshop, Boston, USA, “Comutational genome-wide discovery of tumor-specific splice variants with GeneChip Human Exon 1.0 ST array”, (R. Yoshida*, S. Imoto, K. Numata, S. Miyano). (invited)
2006.3.ESF-JSPS Frontier Science Conference Series for Young, Hayama, Japan, “Genome-wide discovery of tissue-specific alternative splicing with all exon microarray”, (R. Yoshida*, S. Imoto, K. Numata, S. Miyano).

2005

2005.8.2005 Joint Statistical Meeting, Minneapolis; Minnesota, USA, “Mixed factors analysis with the application to clustering of DNA microarray experiments”, (R. Yoshida*, T. Higuchi, S. Imoto).
2005.5.The 1st International Workshop on Data Mining and Bioinformatics (DMBIO2005), Singapore, “A penalized likelihood estimation on transcriptional module-based clustering”, (R. Yoshida*, S. Imoto, T. Higuchi).

2004

2004.10.Factor Analysis Centennial Symposium, Osaka, Japan, “Mixed factors analysis for finding groups in gene expression patterns”, (R. Yoshida*, T. Higuchi, S. Imoto). (invited)
2004.8.The 3rd IEEE Computational Systems Bioinformatics (CSB2004), Stanford University, USA, “A mixed factors model for dimension reduction and extraction of a group structure in gene expression data”, (R. Yoshida*, T. Higuchi, S. Imoto).