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.
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.
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.
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.
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:
Their recent papers demonstrate a focus on mining and mineral processing technologies, image analysis, and process control methodologies. Selected recent papers include:
Collaborations play a significant role in their research, with frequent co-authors including:
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.
D. Feng;C. Aldrich;H. Tan
C. Aldrich;C. Marais;B.J. Shean;J.J. Cilliers
D Feng;C Aldrich
Lidia Auret;Chris Aldrich
B. Qi;Chris Aldrich
D. Feng;J.S.J. van Deventer;C. Aldrich
D. Feng;C. Aldrich
G.P.J. Schmitz;C. Aldrich;F.S. Gouws
Chris Aldrich;Lidia Auret
D.W. Moolman;C. Aldrich;J.S.J. Van Deventer;D.J. Bradshaw
D.W. Moolman;J.J. Eksteen;C. Aldrich;J.S.J. van Deventer
D Feng;C Aldrich
D.W. Moolman;C. Aldrich;J.S.J. Van Deventer;W.W. Stange
Y. Fu;C. Aldrich
Yihao Fu;Chris Aldrich;Chris Aldrich
C. Mpinga;Jacques Eksteen;Chris Aldrich;L. Dyer
D. Feng;L. Lorenzen;C. Aldrich;P.W. Maré
Lidia Auret;Chris Aldrich
C. Aldrich;D. Feng
D.W. Moolman;C. Aldrich;G.P.J. Schmitz;J.S.J. Van Deventer
D Feng;C Aldrich;H Tan
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