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J. Nathan Kutz

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 85 379 357 126 115 532 37645

J. Nathan Kutz publications per year

The chart shows the history of publications by J. Nathan Kutz between 1993 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. J. Nathan Kutz published across 33 years, from 1993 to 2025, averaging 20.1 papers a year. Output peaked at 66 publications in 2019. 62 of the 664 publications appeared in the last two years.

No. of publications
20 40 60
Bar chart. Horizontal axis: year, 1993 to 2025. Vertical axis: number of publications, 0 to 66. Peak 66 publications in 2019. 1993: 5 publications 1994: 1 publication 1995: 0 publications 1996: 5 publications 1997: 8 publications 1998: 12 publications 1999: 8 publications 2000: 6 publications 2001: 7 publications 2002: 6 publications 2003: 7 publications 2004: 7 publications 2005: 15 publications 2006: 4 publications 2007: 10 publications 2008: 11 publications 2009: 21 publications 2010: 28 publications 2011: 24 publications 2012: 16 publications 2013: 22 publications 2014: 21 publications 2015: 22 publications 2016: 39 publications 2017: 36 publications 2018: 36 publications 2019: 66 publications 2020: 48 publications 2021: 46 publications 2022: 25 publications 2023: 40 publications 2024: 32 publications 2025: 30 publications
1993 2025

664 publications in total across all disciplines

View publications per year as a table
J. Nathan Kutz: publications per year, 1993 to 2025
Year Publications
1993 5
1994 1
1995 0
1996 5
1997 8
1998 12
1999 8
2000 6
2001 7
2002 6
2003 7
2004 7
2005 15
2006 4
2007 10
2008 11
2009 21
2010 28
2011 24
2012 16
2013 22
2014 21
2015 22
2016 39
2017 36
2018 36
2019 66
2020 48
2021 46
2022 25
2023 40
2024 32
2025 30
Total 664
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J. Nathan Kutz 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 J. Nathan Kutz sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 528–537 publications, is where this scientist sits. 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
38–47 publications 804+

This scientist: 532 publications — 95th percentile

95% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23 532
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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J. Nathan Kutz 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 J. Nathan Kutz sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 85 D-Index, is where this scientist sits. 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: 85 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380
44 310
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18 85
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
Download as CSV

Overview

J. Nathan Kutz is affiliated with the University of Washington in the United States. Their research spans multiple fields, primarily focused on Engineering and Physics and Astronomy. They contribute extensively to the subfields of Statistical and Nonlinear Physics, Artificial Intelligence, Control and Systems Engineering, Computational Mechanics, and Statistics, Probability and Uncertainty.

Their work encompasses a range of interconnected topics including Model Reduction and Neural Networks, Probabilistic and Robust Engineering Design, Fluid Dynamics and Turbulent Flows, Control Systems and Identification, Fault Detection and Control Systems, Cardiac Arrest and Resuscitation, as well as Fluid Dynamics and Vibration Analysis.

J. Nathan Kutz has published prolifically, with frequent contributions appearing in these venues:

  • arXiv (Cornell University)
  • Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
  • IEEE Access
  • Zenodo (CERN European Organization for Nuclear Research)
  • Circulation

Recent papers include:

  • Modern Koopman Theory for Dynamical Systems, 2022, SIAM Review
  • Ensemble-SINDy: Robust sparse model discovery in the low-data, high-noise limit, with active learning and control, 2022, Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
  • SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics, 2020, Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
  • Shallow neural networks for fluid flow reconstruction with limited sensors, 2020, Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences
  • PySINDy: A Python package for the sparse identification of nonlinear dynamical systems from data, 2020, The Journal of Open Source Software

The scientist has collaborated frequently with a core group of coauthors, including Steven L. Brunton, Bingni W. Brunton, Heemun Kwok, Jason Coult, and Thomas D. Rea.

J. Nathan Kutz is also an author of books published by Springer Nature, including a recent work titled Model Order Reduction and Applications (2023).

Best Publications

  • Discovering governing equations from data by sparse identification of nonlinear dynamical systems

    Steven L. Brunton;Joshua L. Proctor;J. Nathan Kutz

  • On dynamic mode decomposition: Theory and applications

    Jonathan H. Tu;Clarence Worth Rowley;Dirk M. Luchtenburg;Steven L. Brunton

  • Data-driven discovery of partial differential equations.

    Samuel H. Rudy;Steven L. Brunton;Joshua L. Proctor;J. Nathan Kutz

  • Deep learning for universal linear embeddings of nonlinear dynamics.

    Bethany Lusch;J. Nathan Kutz;Steven L. Brunton

  • Dynamic Mode Decomposition with Control

    Joshua L. Proctor;Steven L. Brunton;J. Nathan Kutz

  • Dynamic Mode Decomposition: Data-Driven Modeling of Complex Systems

    J. Nathan Kutz;Steven L. Brunton;Bingni W. Brunton;Joshua L. Proctor

  • Deep learning in fluid dynamics

    J. Nathan Kutz

  • Data-driven discovery of coordinates and governing equations

    Kathleen Champion;Bethany Lusch;J. Nathan Kutz;Steven L. Brunton

  • Koopman Invariant Subspaces and Finite Linear Representations of Nonlinear Dynamical Systems for Control

    Steven L. Brunton;Bingni W. Brunton;Joshua L. Proctor;J. Nathan Kutz

  • Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control

    Steven L. Brunton;J. Nathan Kutz

  • Chaos as an intermittently forced linear system.

    Steven L. Brunton;Bingni W. Brunton;Joshua L. Proctor;Eurika Kaiser

  • Extracting spatial–temporal coherent patterns in large-scale neural recordings using dynamic mode decomposition

    Bingni W. Brunton;Lise A. Johnson;Jeffrey G. Ojemann;J. Nathan Kutz

  • Sparse identification of nonlinear dynamics for model predictive control in the low-data limit.

    E. Kaiser;J. N. Kutz;S. L. Brunton

  • Data-Driven Sparse Sensor Placement for Reconstruction

    Krithika Manohar;Bingni W. Brunton;J. Nathan Kutz;Steven L. Brunton

  • Multiresolution Dynamic Mode Decomposition

    J. Nathan Kutz;Xing Fu;Steven L. Brunton

  • Modern Koopman Theory for Dynamical Systems.

    Steven L. Brunton;Marko Budisic;Eurika Kaiser;J. Nathan Kutz

  • Sparse identification of nonlinear dynamics for model predictive control in the low-data limit

    Eurika Kaiser;J. Nathan Kutz;Steven Brunton

  • Data-Driven Sparse Sensor Placement for Reconstruction: Demonstrating the Benefits of Exploiting Known Patterns

    Krithika Manohar;Bingni W. Brunton;J. Nathan Kutz;Steven L. Brunton

  • Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics

    Niall M. Mangan;Steven L. Brunton;Joshua L. Proctor;J. Nathan Kutz

  • Data-Driven Modeling & Scientific Computation: Methods for Complex Systems & Big Data

    J. Nathan Kutz

  • Bose-Einstein condensates in standing waves: the cubic nonlinear Schrödinger equation with a periodic potential.

    Jared C. Bronski;Lincoln D. Carr;Bernard Deconinck;J. Nathan Kutz

  • Neural Networks and Deep Learning

    Steven L. Brunton;J. Nathan Kutz

Frequent Co-Authors

Steven T. Cundiff
Steven T. Cundiff University of Michigan–Ann Arbor
Ping-kong Alexander Wai
Ping-kong Alexander Wai Hong Kong Polytechnic University
Herbert G. Winful
Herbert G. Winful University of Michigan–Ann Arbor
Frank W. Wise
Frank W. Wise Cornell University
Roberto Morandotti
Roberto Morandotti Institut National de la Recherche Scientifique
Demetrios N. Christodoulides
Demetrios N. Christodoulides University of Southern California
Richard P. Mirin
Richard P. Mirin National Institute of Standards and Technology
Clarence W. Rowley
Clarence W. Rowley Princeton University
Keren Bergman
Keren Bergman Columbia University
William L. Kath
William L. Kath Northwestern University

External Links

Wikipedia of J. Nathan Kutz Personal website of J. Nathan Kutz Google Scholar page

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