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Chris Aldrich

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 45 5449 5250 283 279 254 8402

Chris Aldrich publications per year

The chart shows the history of publications by Chris Aldrich between 1985 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Chris Aldrich published across 41 years, from 1985 to 2025, averaging 7.4 papers a year. Output peaked at 19 publications in 2024. 38 of the 303 publications appeared in the last two years.

No. of publications
5 10 15
Bar chart. Horizontal axis: year, 1985 to 2025. Vertical axis: number of publications, 0 to 19. Peak 19 publications in 2024. 1985: 1 publication 1986: 0 publications 1987: 0 publications 1988: 0 publications 1989: 0 publications 1990: 0 publications 1991: 0 publications 1992: 0 publications 1993: 2 publications 1994: 6 publications 1995: 13 publications 1996: 9 publications 1997: 3 publications 1998: 6 publications 1999: 6 publications 2000: 16 publications 2001: 9 publications 2002: 5 publications 2003: 7 publications 2004: 9 publications 2005: 14 publications 2006: 14 publications 2007: 8 publications 2008: 5 publications 2009: 3 publications 2010: 16 publications 2011: 12 publications 2012: 7 publications 2013: 16 publications 2014: 7 publications 2015: 7 publications 2016: 6 publications 2017: 8 publications 2018: 14 publications 2019: 8 publications 2020: 7 publications 2021: 6 publications 2022: 9 publications 2023: 6 publications 2024: 19 publications 2025: 19 publications
1985 2025

303 publications in total across all disciplines

View publications per year as a table
Chris Aldrich: publications per year, 1985 to 2025
Year Publications
1985 1
1986 0
1987 0
1988 0
1989 0
1990 0
1991 0
1992 0
1993 2
1994 6
1995 13
1996 9
1997 3
1998 6
1999 6
2000 16
2001 9
2002 5
2003 7
2004 9
2005 14
2006 14
2007 8
2008 5
2009 3
2010 16
2011 12
2012 7
2013 16
2014 7
2015 7
2016 6
2017 8
2018 14
2019 8
2020 7
2021 6
2022 9
2023 6
2024 19
2025 19
Total 303
Download as CSV

Chris Aldrich 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 Chris Aldrich 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, 248–257 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: 254 publications — 65th percentile

65% 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
248–257 280 254
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
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
Download as CSV

Chris Aldrich 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 Chris Aldrich 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, 45 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: 45 D-Index — 46th percentile

46% 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 45
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
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

Chris Aldrich is affiliated with Curtin University in Australia, focusing on research primarily within the field of engineering. Their work extends into multiple subfields including mechanical engineering, ocean engineering, control and systems engineering, artificial intelligence, and water science and technology.

The scientist's main research topics include mineral processing and grinding, fault detection and control systems, minerals flotation and separation techniques, drilling and well engineering, non-destructive testing techniques, reservoir engineering and simulation methods, and anomaly detection techniques and applications.

Key publication venues where Chris Aldrich has frequently contributed are:

  • Minerals Engineering
  • IFAC-PapersOnLine
  • Minerals
  • Preprints.org
  • Metals

Their recent papers demonstrate a focus on mining and mineral processing technologies, image analysis, and process control methodologies. Selected recent papers include:

  • Recent advances in flotation froth image analysis (2022, Minerals Engineering)
  • Process Variable Importance Analysis by Use of Random Forests in a Shapley Regression Framework (2020, Minerals)
  • Deep Learning in Mining and Mineral Processing Operations: A Review (2020, IFAC-PapersOnLine)
  • Deep Learning Approaches to Image Texture Analysis in Material Processing (2022, Metals)
  • Detection and severity identification of control valve stiction in industrial loops using integrated partially retrained CNN-PCA frameworks (2020, Chemometrics and Intelligent Laboratory Systems)

Collaborations play a significant role in their research, with frequent co-authors including:

  • Xiu Liu
  • Louisa O'Connor
  • Massimiliano Zanin
  • Lei Chen
  • Daniel Goldstein

Chris Aldrich's academic output reflects an integration of engineering principles with advanced data analysis techniques such as machine learning and deep learning applied to mineral processing and control systems. This interdisciplinary approach is evident in their exploration of process variable importance and fault detection within industrial processes.

Best Publications

  • Treatment of acid mine water by use of heavy metal precipitation and ion exchange

    D. Feng;C. Aldrich;H. Tan

  • Online monitoring and control of froth flotation systems with machine vision: A review

    C. Aldrich;C. Marais;B.J. Shean;J.J. Cilliers

  • Adsorption of heavy metals by biomaterials derived from the marine alga Ecklonia maxima

    D Feng;C Aldrich

  • Interpretation of nonlinear relationships between process variables by use of random forests

    Lidia Auret;Chris Aldrich

  • Biosorption of heavy metals from aqueous solutions with tobacco dust.

    B. Qi;Chris Aldrich

  • Removal of pollutants from acid mine wastewater using metallurgical by-product slags

    D. Feng;J.S.J. van Deventer;C. Aldrich

  • Effect of particle size on flotation performance of complex sulphide ores

    D. Feng;C. Aldrich

  • ANN-DT: an algorithm for extraction of decision trees from artificial neural networks

    G.P.J. Schmitz;C. Aldrich;F.S. Gouws

  • Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods

    Chris Aldrich;Lidia Auret

  • The interpretation of flotation froth surfaces by using digital image analysis and neural networks

    D.W. Moolman;C. Aldrich;J.S.J. Van Deventer;D.J. Bradshaw

  • The significance of flotation froth appearance for machine vision control

    D.W. Moolman;J.J. Eksteen;C. Aldrich;J.S.J. van Deventer

  • Sonochemical treatment of simulated soil contaminated with diesel

    D Feng;C Aldrich

  • Digital image processing as a tool for on-line monitoring of froth in flotation plants

    D.W. Moolman;C. Aldrich;J.S.J. Van Deventer;W.W. Stange

  • Flotation froth image recognition with convolutional neural networks

    Y. Fu;C. Aldrich

  • Froth image analysis by use of transfer learning and convolutional neural networks

    Yihao Fu;Chris Aldrich;Chris Aldrich

  • Direct leach approaches to Platinum Group Metal (PGM) ores and concentrates: A review

    C. Mpinga;Jacques Eksteen;Chris Aldrich;L. Dyer

  • Ex situ diesel contaminated soil washing with mechanical methods

    D. Feng;L. Lorenzen;C. Aldrich;P.W. Maré

  • Empirical comparison of tree ensemble variable importance measures

    Lidia Auret;Chris Aldrich

  • Removal of heavy metals from wastewater effluents by biosorptive flotation.

    C. Aldrich;D. Feng

  • The interrelationship between surface froth characteristics and industrial flotation performance

    D.W. Moolman;C. Aldrich;G.P.J. Schmitz;J.S.J. Van Deventer

  • Removal of heavy metal ions by carrier magnetic separation of adsorptive particulates

    D Feng;C Aldrich;H Tan

Frequent Co-Authors

Damien W. M. Arrigan
Damien W. M. Arrigan Curtin University
Markus A. Reuter
Markus A. Reuter Helmholtz-Zentrum Dresden-Rossendorf
Risto Miikkulainen
Risto Miikkulainen The University of Texas at Austin
Jannie S.J. van Deventer
Jannie S.J. van Deventer University of Melbourne
Mohammad Sarmadivaleh
Mohammad Sarmadivaleh Colorado School of Mines
Maurice S. Onyango
Maurice S. Onyango Tshwane University of Technology
Jan J. Cilliers
Jan J. Cilliers Imperial College London
Mostafa Sharifzadeh
Mostafa Sharifzadeh Curtin University
Mustafa Sahin
Mustafa Sahin Boston Children's Hospital
Dee Bradshaw
Dee Bradshaw University of Queensland

External Links

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Publications: 7

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