Chris Aldrich

Universität Hamburg — Germany

Engineering · Physical Sciences

44h-index7.4kcitations328works3.32yr avg
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Research Topics

Mineral Processing and Grinding(127), Minerals Flotation and Separation Techniques(84), Fault Detection and Control Systems(71), Neural Networks and Applications(37), Spectroscopy and Chemometric Analyses(21)

Publications328 total

A review of the AG/SAG mill liner health monitoring systems
Minerals Engineering·2025Open Access
Predicting stress corrosion cracking in downhole environments: a Bayesian network approach for duplex stainless steels
npj Materials Degradation·2025Open Access
Deep Learning-Based Rock Particulate Classification Using Attention-Enhanced ConvNeXt
arXiv (Cornell University)·2025Open Access
DEEP LEARNING-BASED ROCK PARTICULATE CLASSIFICATION USING ATTENTIONENHANCED CONVNEXT
International Journal on Soft Computing Artificial Intelligence and Applications·2025Open Access
Pyrogenic carbon and carbonating minerals for carbon capture and storage (PyMiCCS) part II: organic and inorganic carbon dioxide removal in an Oxisol
Frontiers in Climate·2025· 4 citedOpen Access
Optimising SAG mill throughput and circulating load using machine learning models: A multi-objective approach for identifying optimal process parameters
Minerals Engineering·2025· 2 citedOpen Access
Unsupervised process monitoring of corrosion based on electrochemical noise and multivariate image analysis
npj Materials Degradation·2025· 4 citedOpen Access
Identification of Laminar Structure in the Yingxiongling Shale Oil Sediment in China with Random Forests and SHAP Analysis
ACS Omega·2025· 3 citedOpen Access
A Field-Scale Framework for Assessing the Influence of Measure-While-Drilling Variables on Geotechnical Characterization Using a Boruta-SHAP Approach
Mining·2025· 1 citedOpen Access
Synergistic effects of co-application and co-pyrolysis of biochar and enhanced weathering materials for CO2 removal in an Oxisol
2025Open Access
A Machine Learning Classification Approach to Geotechnical Characterization Using Measure-While-Drilling Data
Geosciences·2025· 3 citedOpen Access
Unlocking Subsurface Geology: A Case Study with Measure-While-Drilling Data and Machine Learning
Minerals·2025· 4 citedOpen Access
A Field-Scale Framework for Assessing the Influence of Measure-While-Drilling Variables on Geotechnical Characterization Using a Boruta-Shap Approach
Preprints.org·2025· 1 citedOpen Access
A Machine Learning Classification Approach to Geotechnical Characterisation Using Measure-While-Drilling Data
Preprints.org·2025· 1 citedOpen Access
Unlocking Subsurface Geology: A Case Study with Measure-While-Drilling Data and Machine Learning
Preprints.org·2025· 3 citedOpen Access
Imbalanced Classification of Ultrahigh Carbon Steel Microstructures with Vision Transformers and Image Synthesis of Minority Class
2025· 1 cited
Roping Prediction Versus Detection: Could Prediction Be Possible?
Minerals·2025· 1 citedOpen Access
Optimising Sag Mill Throughput and Circulating Load Using Machine Learning Models: A Multi-Objective Approach for Identifying Optimal Process Parameters
SSRN Electronic Journal·2025Open Access
Small Sample Multivariate Image Regression with Convolutional Neural Networks
IFAC-PapersOnLine·2025Open Access
XGBoost model for the quantitative assessment of stress corrosion cracking
npj Materials Degradation·2024· 11 citedOpen Access
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Frequent Co-authors

D. Feng(11), J.S.J. van Deventer(9), D.W. Moolman(7), Lidia Auret(6), L. Lorenzen(4), Hua Tan(2), C. Marais(2), G.P.J. Schmitz(2), Yifeng Fu(2), J.J. Eksteen(2), W. Stange(2), Tosca-Marie Heunis(2), Petrus J. de Vries(2), Yang Hou(2), Kateřina Lepková(2), Laura L. Machuca(2), Brian Kinsella(2), Gorden T. Jemwa(2), Ndeke Musee(2), B.J. Shean(1)