Waseda Univ, Dr..Yasuo Matsuyama

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

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
  • Big and heterogeneous data processing with blockchain (IoCT)
  • Retrieval engines for still images and videos
  • Brain machine interface
  • 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


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


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


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


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


Stanford University, Information Systems Laboratory, Research Assistant


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


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


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


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

Academic Societies




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



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


WASEDA e-Teaching Award (2016)


Outstanding Educational Material Award (Textbook) (2015)


Fellow Award of IPSJ (2014)


IEEE Life Fellow (2013)


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


LSI IP Design Award, Intellectual Product Award (2006)


APNNA Best Paper Award for Application Oriented Research (2004)


Fellow Award of IEICE (2002)


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


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


IEEE Fellow Award (1998)


IEICE Transactions, Best Paper Award (1992)


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

List of Selected Publications

* Y. Matsuyama, The alpha-HMM estimation algorithm: Prior cycle guides fast paths, IEEE Trans. Signal Processing, Vol. 65, pp. 3446-3461 and 6-page supplementary material, 2017.
* Y. Matsuyama, Human-aware IoCT via machine learning and HPC, Invited talk at the 15th HPC Connection Workshop, Wuxi, April, 2017 (
* 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.
* 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)   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.
* 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.
* 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.