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Introduction

Waseda Univ, Dr..Yasuo Matsuyama

Professor Emeritus,
Honorary Researcher of Research Institute of Science and Engineering,
Waseda University
Yasuo Matsuyama

yasuo2-at-waseda.jp
http://www.f.waseda.jp/yasuo2/en/

Integration of symbols and patterns for human-aware IoCT (Internrt of Collaborative Things)
Machine learning theory and applications are Professor Matsuyama's main target.
He is well-known as the founder of the α-EM algorithm (cf. his publication of 2003).

  • Theory and applications of machine learning and computational intelligence towards IoCT
  • Machine learning algorithms using generalized amount of information
  • Integration of machinelearning and blockchain
  • Retrieval engines for still images and videos
  • Brain machine interfaces
  • Neural networks and spiking neuron modeling
  • Bioinformatics

Curriculum vitae

2017-present Waseda University, Professor Emeritus and Honorary Researcher of the Research Institute of Science and Engineering
1996-2017

Waseda University, Full Professor (Department of Computer Science and Engineering),
Director of the Media Network Center(2011-2014)

1994

National Personnel Authority, Co-Chief Examiner (Dual position): Comprehensive Examination of Grade 1

1979-96

Ibaraki University, {Assistant -> Associate -> Full} Professor}

1978

Stanford University, Graduate School of Engineering, EE Major: Ph.D.

1977-78

Stanford University, Information Systems Laboratory, Research Assistant

1974-78

Japan-US Exchange Fellow (Japan Society for the Promotion of Science, Fulbright, IIE)

1974

Waseda University, Graduate School of Science and Engineering, EE Major: Dr. Engineering

1971

Waseda University, Graduate School of Science and Engineering, EE Major: M. Engineering

1969

Waseda University, School of Science and Engineering, Department of Electrical Engineering: B. Engineering

Academic Societies

International

IEEE, ACM

National

IEICE (The Institute of Electrical, Communications and Information Engineers),
IPSJ (The Information Processing Society of Japan ,
JNNS (The Japanese Neural Network Society),

Awards

14

Okuma Academic Award (The Founder's Memorial Prize) (2016)

13

WASEDA e-Teaching Award (2016)

12

Outstanding Educational Material Award (Textbook) (2015)

11

Fellow Award of IPSJ (2014)

10

IEEE Life Fellow (2013)

9

CSTST (International Conference on Soft Computing as Transdisciplinary Science and Technology) Best Paper Award, ACM & IEEE (2008)

8

LSI IP Design Award, Intellectual Product Award (2006)

7

APNNA Best Paper Award for Application Oriented Research (2004)

6

Fellow Award of IEICE (2002)

5

IEEE Transactions on Neural Networks, Outstanding Paper Award (2001)

4

The Telecommunications Advancement Foundation, Telecommunication Systems Technology, Major Award (2001)

3

IEEE Fellow Award (1998)

2

IEICE Transactions, Best Paper Award (1992)

1

The Telecommunications Advancement Foundation, Telecommunication Systems Technology, Promotion Award (1989)

List of Selected Publications

* Y. Matsuyama, Divergence family contribution to data evaluation in blockchain via alpha-EM and log-EM algorithms, IEEE Access, Vol. 9, pp. 24546-24559, 2020. DOI: 10.1109/ACCESS.2012.3056710
* Y. Matsuyama, Divergence family attains blockchain applications via α-EM algorithm, Proceedings of IEEE International Symposium on Information Theory, pp. 727-731, 2019. DOI: 10.1109/ISIT.2019.8849300
* T. Horie, M. Uchida, Y. Matsuyama, Similar video retrieval via order-aware exemplars and alignment, Journal of Signal and Information Processing, Vol. 9, pp. 73-91, 2018. DOI: 10.4236/jsip.2018.92005
* Y. Matsuyama, The alpha-HMM estimation algorithm: Prior cycle guides fast paths, IEEE Transactions on Signal Processing, Vol. 65, pp. 3446-3461, and 6-page supplemanrary materials, 2017. DOI: 10.1109/TSP.2017.2692724
* H. Iwase, T. Horie, and Y. Matsuyama, (corresponding author), Verification of fraudulent PIN holders by brain waves, Proc. Int. Joint Conf. Neural Networks, pp. 2068-2075, Vancouver, 2016.
* Y. Matsuyama, Human-aware IoCT via machine learning and HPC, invited talk at the 15th HPC Connection Workshop, Wuxi, April, 2017 (http://www.asc-events.org/ASC17/Workshop.php).
* H. Iwase, T. Horie, and Y. Matsuyama, (corresponding author), Verification of fraudulent PIN holders by brain waves, Proc. Int. Joint Conf. Neural Networks, pp. 2068-2075, Vancouver, 2016.
* T. Horie, M. Moriwaki, R. Yokote, S. Ninomiya, A. Shikano, Y. Matsuyama, Similar-video retrieval via learned exemplars and time-warped alignment, Lecture Notes in Computer Science, No. 8836, pp. 85-94. DOI: 10.1007/978-3-319-12643-2_11. http://link.springer.com/chapter/10.1007%2F978-3-319-12643-2_11
* Y. Matsuyama, Machine Learning Strategies for Big Data Utilization: Assembling via Statistical Soft Label, Plenary/Keynote Speak, Int. Conf. Audio, Language and Image Processing, Shanghai, July, (2014) http://www.icalip2014.org/KeynoteSpeakerMatsuyama.aspx   presentation
* H. Kamiya, R. Yokote and Y. Matsuyama, Icon Placement Regularization for Jammed Profiles: Applications to Web-Registered Personnel Mining, Communications in Computer and Information Science, Vol. 409, pp. 70-79, 2013. http://link.springer.com/book/10.1007%2F978-3-319-03783-7
* M. Shozawa, R. Yokote, S. Hidano, Chi-Hua Wu and Y. Matsuyama, Brain Signal Based Continuous Authentication: Functional NIRS Approach, Lecture Notes in Computer Science, Vol. 7903, pp. 171-180, 2013. http://link.springer.com/book/10.1007%2F978-3-642-38679-4
* M. Maejima, R. Yokote, Y. Matsuyama, Composite data mapping by multi-dimensional scaling: GUI design for clustering must-watch and no-need programs, Lecture Notes in Computer Science, No. 7667, pp. 267-274, 2012.
* R. Yokote and Y. Matsuyama, Rapid algorithm for independent component analysis, J. Signal and Information Processing, Vol. 3, pp. 275-285, 2012.
* Y. Matsuyama, R. Yokote, Y. Yokosawa, Conversion of sensitivity-based tasks from brain signals and motions: Applications to humanoid operation, Proc. IASTED Int. Conf. on Artificial Intelligence, pp. 271-277, 2012.
* Y. Matsuyama and R. Yokote, From convex divergence to human-aware information processing: Good models mismatch well, therefore serviceable, International Workshop on Anomalous Statistics, Generalized Entropies, and Information Geometry, invited presentation, Abstract p. 20, Nara, Japan, March 2012.
* Y. Matsuyama, Hidden Markov model estimation based on the alpha-EM algorithm: Discrete and continuous alpha-HMMs, Proc. of International Joint Conference on Neural Networks, pp. 809-816, San Jose, CA, 2011.
* R. Yokote, T. Nakamura and Y. Matsuyama, Independent component analysis with graphical correlation: Applications to multi-vision coding, Proceedings of International Joint Conference on Neural Networks, San Jose, CA, pp. 701-708, 2011.
* Y. Matsuyama, R. Hayashi and R. Yokote, Fast estimation of hidden Markov models via alpha-EM algorithm, Proc. of 2011 IEEE Statistical Signal Processing Workshop, Nice, France, pp. 89-92, 2011.
* Y. Matsuyama Bioinformatics in silico, Baifukan Pub. Co. Tokyo, 2011.
* Y. Matsuyama, K. Noguchi, T. Hatakeyama, N. Ochiai and T. Hori, Signal recognition and conversion towards symbiosis with ambulatory humanoids, Lecture Notes in Artificial Intelligence, Springer, No.6334, pp. 101-111, 2010.
* Y. Matsuyama and R. Hayashi, Alpha-EM gives fast hidden Markov model estimation: Derivation and evaluation of alpha-HMM, Proc. Int. Joint Conf. on Neural Networks, pp. 663-670, 2010.
* R. Yokote and Y. Matsuyama, Yet rapid ICA: Applications to un-indexed image-to-image retrieval, Proc. Int. Joint Conf. on Neural Networks, pp. 4255-4262, 2010.
Bio-signal integration for humanoid operation: Gesture and brain signal recognition by HMM/SVM-embedded BN, Lecture Notes in Computer Science, No. 5506, pp. 351-359, 2009.
* T. Kato, S. Honma, Y. Matsuyama, T. Yoshino and Y. Hoshino, Sensibility-aware image retrieval using computationally learned bases: RIM, JPG, J2K and their mixtures, Lecture Notes in Computer Science, No. 5506, pp. 620-627, 2009.
* M. Takata and Y. Matsuyama, Protein folding classification by committee SVM array, Lecture Notes in Computer Science, No. 5507, pp. 369-377, 2009.
* Y. Matsuyama, F. Matsushima, Y. Nishida, T. Hatakeyama, N. Ochiai and S. Aida, Multimodal belief integration by HMM/SVM-embedded Bayesian network: Applications to ambulating PC operation by body motions and brain signals, Lecture Notes in Computer Science, No. 5768, pp. 767-778, 2009.
* Y. Matsuyama and Y. Nishida, HMM-embedded Bayesian network for heterogeneous command integration: Applications to biped humanoid operation over the network, Proc. CSTST 2008, pp.138-145, 2008.
* Y. Matsuyama, F. Ohashi, F. Horiike, T. Nakamura, S. Honma, N. Katsumata, and Y. Hoshino, Image-to-image retrieval using computationally learned bases and color information, Proc. IJCNN, 1158, 2007.
* Y. Matsuyama, Y. Ishihara, Y. Ito, T. Hotta, K. Kawasaki, T. Hasegawa and M. Takata, Promoter recognition involving motif detection : Studies on E. coli and human genes, ISMB/ECCB, H06, 2007.
* J. Kato, N. Takahashi, Y. Ueda, Y. Sugihara and Y. Matsuyama, Networked remote operation of humanoid via motion interpretation and image recognition, Proceedings of Int. Conf. on Autonomous Robots and Agents, Vol. 1, pp. 51-56, 2006.
* N. Katsumata, Y. Matsuyama, T. Chikagawa, F. Ohashi, F. Horiike, S. Honma and T. Nakamura, Retrieval-aware image compression, its format and viewer based upon learned bases, Lecture Notes in Computer Science, No. 4233, pp. 420-429, 2006.
* Y. Matsuyama, K. Onuki, Y. Ito, Y. Ishihara, k. Kawasaki and T. Hasegawa, Decomposition of DNA sequences into hidden components; Applications to human genome's promoter recognition, Intelligent Systems for Molecular Biology, H67, 2006.
* D. Kawakita, K. Hosaki and Y. Matsuyama, Turbo encoder and decoder using fake-process interleaver, 8th LSI IP Award, design specification document, 2006.
* Y. Matsuyama, T. Shiga, T. Chikagawa, N. Takahashi and Y. Ueda, Network communication strategies for cooperative physical agents, Proceedings of Asia-Pacific Symposium on Information and Telecommunication Technologies, Vol. 1, pp. 148-153, 2005.
* Y. Matsuyama, Y. Ito, K. Onuki and Y. Ishihara, Decomposition of Discrete-symbol biosequences to hidden components: Independent component analysis for DNA promoter recognition, Proceedings of International Conference on Neural Information Processing, Vol. 1, pp. 538-543, 2005.
* N. Katsumata and Y. Matsuyama, Database retrieval for similar images using ICA and PCA bases, Engineering Applications of Artificial Intelligence, Vol. 18, pp. 705-717, 2005.
* Y. Matsuyama, S. Yoshinaga, H. Okuda, K. Fukumoto, S. Nagatsuma, K. Tanikawa, H. Hakui, R. Okuhara and N. Katsumata, Towards the unification of human movement, animation and humanoid in the network, Lecture Notes in Computer Science, Springer Verlag, No. 3316, pp. 1135-1141, 2004.(APPNA Best Paper Award for Application Oriented Research)
* Y. Matsuyama and R. Kawamura, Promoter recognition for E. coli DNA segments by independent component analysis, Proc. Computational Systems Bioinformatics, Vol. 1, pp. 686-691, 2004.
* Y. Matsuyama, H. Kataoka, N. Katsumata and K. Shimoda, ICA photographic encoding gear: Image bases towards IPEG, Proc. IJCNN, vol. 3, pp. 2129-2134, 2004.
* N. Nishioka, Y. Matsuyama, A. Saitoh, Y. Morita, N. Katsumata, H. Kataoka, R. Mizuta and S. Yoshika, Agent generation and resource allocation in a network computing environment, Proc. Asia-Pacific Symposium on Information and Telecommunication Technologies, Proc. Asia-Paific Symposium on Information and Telecommunication Technologies, Vol. 1, pp. 63-68, 2003.
* Y. Matsuyama, N. Katsumata and R. Kawamura, Independent component analysis minimizing convex divergence, Lecture Notes in Computer Science, Springer Verlag, No. 2714, pp. 27-34, 2003.
* Y. Matsuyama, The alpha-EM algorithm: Surrogate likelihood maximization using alpha-logarithmic information measures, IEEE Trans. on Information Theory, Vol. 49, pp. 692-706, 2003.
* Y. Matsuyama, S. Imahara and N. Katsumata, Optimization transfer for computational learning: A hierarchy from f-ICA and alpha-EM to their offsprings, Proceedings of International Joint Conference on Neural Networks, Vol. 3, pp. 1883-1888, 2002.
* Y. Matsuyama, N. Katsumata, Y. Suzuki and S. Imahara, The alpha-ICA algorithm, Proceedings of Independent Component Analysis and Blind Signal Separation, pp. 297-302, 2000.
* Y. Matsuyama Theα-EM algorithm and its basic properties, Trans IEICE, Vol. J82-D-I,pp. 1347-1358, 1999.
* Y. Matsuyama, Multiple descent cost competition: Restorable self-organization and multimedia information processing, IEEE Trans. on Neural Networks,Vol. 7,pp. 652-668, 1998. (Outstanding Paper Award of IEEE Trans. NN, 2001
* S. Okamoto, Y. Matsuyama and K. Oshima, Computer Dictionary,Kyoritsu Pup. Co, Tokyo,1997.
* Y. Matsuyama, The alpha-EM Algorithm: A block connectable generalized learning tool for neural networks, Lecture Notes in Computer Science, Springer Verlag, No. 1240, pp. 1240,483-492, 1997.
* Y. Matsuyama, Harmonic competition: A self-organizing multiple criteria optimization, IEEE Trans. on Neural Networks,Vol. 7,pp. 652-668, 1996.
* Y. Matsuyama, Competitive learning among massively parallel agents: Applications to traveling salesperson problems, Neural, Parallel & Scientific Computations, Vol. 1, pp. 181-197, 1993.
* Y. Matsuyama and T. Tomizawa, Introduction to VLSI Design, Kyoritsu Pub. Co., Tokyo, 1983.
* Y. Matsuyama and R. M. Gray, Voice coding and tree encoding speech compression systems based upon inverse filter matching, IEEE Trans. on Communications, Vol. COM-30, pp. 711-720, 1982.
* Y. Matsuyama and R. M. Gray, Universal tree encoding for speech, IEEE Trans. Information Theory, Vol. IT-27, pp. 31-40, 1981.
* R. M. Gray, A. Buzo, A. H. Gray, Jr. and Y. Matsuyama, Distortion measures for speech processing, IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. ASSP-24, pp. 367-376, 1980.
* Y. Matsuyama, Mismatch robustness of linear prediction and its relationship to coding, Information and Control (Information and Computation), Vol. 47. pp. 237-262, 1980. (IEEE Fellow Award対象論文,1998)
* Y. Matsuyama, Process distortion measures and signal processing, Ph.D. Dissertation, Stanford University, Aug., 1978.
* Y. Matsuyama, A note on stochastic modeling of shunting inhibition, Biological Cybernetics, Vol. 24, pp. 139-145, 1976.
* Y. Matsuyama, K. Shirai and K. Akizuki, On some properties of stochastic information processes in neurons and neuron populations, Kybernetik (Biological Cybernetics), Vol. 15, pp. 127-145, 1974.
* Y. Matsuyama, Studies on stochastic modeling of neurons, Dr. Engineering Dissertation, Waseda University, Mar., 1974.

Et cetera

He enjoys sports quite often
and reads E-mails frequently. But, please refrain from sending unnecessary ones.