World's Best Scientists 2026 revealed!
Manabu Kano

Manabu Kano

D-Index & Metrics

Engineering and Technology

D-Index
43
Citations
8804
World Ranking
6065
National Ranking
111

Manabu Kano publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Manabu Kano sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 282 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Manabu Kano D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Manabu Kano sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 43 D-Index — 39th percentile

39% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Manabu Kano is affiliated with Kyoto University in Japan and specializes in the field of engineering, with a particular focus on control and systems engineering. Their research spans several subfields including mechanical engineering, artificial intelligence, biomedical engineering, and cognitive neuroscience.

Their work involves multiple main topics of study, particularly:

  • Fault Detection and Control Systems
  • Advanced Control Systems Optimization
  • Mineral Processing and Grinding
  • Heart Rate Variability and Autonomic Control
  • Spectroscopy and Chemometric Analyses
  • Process Optimization and Integration
  • Advanced Statistical Process Monitoring

Manabu Kano has contributed extensively to scientific publications. Some notable recent papers include:

  • Over- and Under-sampling Approach for Extremely Imbalanced and Small Minority Data Problem in Health Record Analysis (2020), published in Frontiers in Public Health
  • Wearable Epileptic Seizure Prediction System with Machine-Learning-Based Anomaly Detection of Heart Rate Variability (2020), published in Sensors
  • Data-driven soft sensors in blast furnace ironmaking: a survey (2023), published in Frontiers of Information Technology & Electronic Engineering
  • Gray-box Soft Sensors in Process Industry: Current Practice, and Future Prospects in Era of Big Data (2020), published in Processes
  • Data-Driven Communication Efficient Distributed Monitoring for Multiunit Industrial Plant-Wide Processes (2021), published in IEEE Transactions on Automation Science and Engineering

Frequent co-authors collaborating with Manabu Kano include:

  • Shota Kato
  • Koichi Fujiwara
  • Xinmin Zhang
  • Iftikhar Ahmad
  • Hakan Çalışkan

Regarding publication venues, Kano's work appears most often in:

  • Computers & Chemical Engineering
  • IFAC-PapersOnLine
  • Chemical and Pharmaceutical Bulletin
  • CAAI Transactions on Intelligence Technology
  • International Journal of Pharmaceutics

Best Publications

  • Data-based process monitoring, process control, and quality improvement: Recent developments and applications in steel industry

    Manabu Kano;Yoshiaki Nakagawa

  • Monitoring independent components for fault detection

    Manabu Kano;Shouhei Tanaka;Shinji Hasebe;Iori Hashimoto

  • Soft‐sensor development using correlation‐based just‐in‐time modeling

    Koichi Fujiwara;Koichi Fujiwara;Manabu Kano;Manabu Kano;Shinji Hasebe;Shinji Hasebe;Akitoshi Takinami;Akitoshi Takinami

  • A new multivariate statistical process monitoring method using principal component analysis

    Manabu Kano;Shinji Hasebe;Iori Hashimoto;Hiromu Ohno

  • The state of the art in chemical process control in Japan: Good practice and questionnaire survey

    Manabu Kano;Morimasa Ogawa

  • Biodiesel Production from Palm Oil, Its By-Products, and Mill Effluent: A Review

    Khairul Azly Zahan;Manabu Kano

  • CFD-based optimal design of manifold in plate-fin microdevices

    Osamu Tonomura;Shotaro Tanaka;Masaru Noda;Manabu Kano

  • Inferential control system of distillation compositions using dynamic partial least squares regression

    Manabu Kano;Koichi Miyazaki;Shinji Hasebe;Iori Hashimoto

  • Comparison of multivariate statistical process monitoring methods with applications to the Eastman challenge problem

    Manabu Kano;Koji Nagao;Shinji Hasebe;Iori Hashimoto

  • Practical Model and Detection Algorithm for Valve Stiction

    Manabu Kano;Hiroshi Maruta;Hidekazu Kugemoto;Keiko Shimizu

  • Heart Rate Variability-Based Driver Drowsiness Detection and Its Validation With EEG

    Koichi Fujiwara;Erika Abe;Keisuke Kamata;Chikao Nakayama

  • Virtual Sensing Technology in Process Industries: Trends and Challenges Revealed by Recent Industrial Applications

    Manabu Kano;Koichi Fujiwara

  • Statistical process monitoring based on dissimilarity of process data

    Manabu Kano;Shinji Hasebe;Iori Hashimoto;Hiromu Ohno

  • Evolution of multivariate statistical process control: application of independent component analysis and external analysis

    Manabu Kano;Shinji Hasebe;Iori Hashimoto;Hiromu Ohno

  • Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features

    Koichi Fujiwara;Miho Miyajima;Toshitaka Yamakawa;Erika Abe

  • Estimation of active pharmaceutical ingredients content using locally weighted partial least squares and statistical wavelength selection.

    Sanghong Kim;Manabu Kano;Hiroshi Nakagawa;Shinji Hasebe

  • Detection and Diagnosis of Stiction in Control Loops State of the Art and Advanced Methods

    Shoukat Choudhury;Peter He;Alexander Horch;Manabu Kano

  • Development of soft-sensor using locally weighted PLS with adaptive similarity measure

    Sanghong Kim;Ryota Okajima;Manabu Kano;Shinji Hasebe

  • Comparison of statistical process monitoring methods: application to the Eastman challenge problem

    Manabu Kano;Koji Nagao;Shinji Hasebe;Iori Hashimoto

  • Adaptive Virtual Metrology Design for Semiconductor Dry Etching Process Through Locally Weighted Partial Least Squares

    Toshiya Hirai;Manabu Kano

  • Covariance-based Locally Weighted Partial Least Squares for High- Performance Adaptive Modeling

    Koji Hazama;Manabu Kano

Frequent Co-Authors

Bhavik R. Bakshi
Bhavik R. Bakshi The Ohio State University
Sirish L. Shah
Sirish L. Shah University of Alberta
S. Joe Qin
S. Joe Qin Lingnan University
Zhiqiang Ge
Zhiqiang Ge Zhejiang University
Zhihuan Song
Zhihuan Song Zhejiang University
Hiroshi Sawada
Hiroshi Sawada NTT (Japan)
Christos Georgakis
Christos Georgakis Tufts University
Juergen Hahn
Juergen Hahn Rensselaer Polytechnic Institute
Nina F. Thornhill
Nina F. Thornhill Imperial College London
Hirofumi Takeuchi
Hirofumi Takeuchi Gifu Pharmaceutical University

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