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Amanda Lane
Observed name:
A. Lane
Institution:
Unilever (United Kingdom)
Observed institution:
Unilever (United Kingdom)
OpenAlex ID:
A5050029481
Probabilistic machine learning based soft-sensors for product quality prediction in batch processes
2022
·
M. Mowbray
, H. Kay
, et al.
·
Chemometrics and Intelligent Laboratory Systems
·
40
PDF
Integrating Autoencoder and Heteroscedastic Noise Neural Networks for the Batch Process Soft-Sensor Design
2022
·
Sam Kay
, Harry Kay
, et al.
·
Industrial & Engineering Chemistry Research
·
23
A two-step multivariate statistical learning approach for batch process soft sensing
2021
·
Aaron Hicks
, Matthew Johnston
, et al.
·
Digital Chemical Engineering
·
21
Constructing a Symbolic Regression-Based Interpretable Soft Sensor for Industrial Data Analytics and Product Quality Control
2024
·
Harry Kay
, Sam Kay
, et al.
·
Industrial & Engineering Chemistry Research
·
16
Integrating knowledge-guided symbolic regression and model-based design of experiments to automate process flow diagram development
2024
·
Alexander W. Rogers
, Amanda Lane
, et al.
·
Chemical Engineering Science
·
14
Interpretable‐AI‐Based Model Structural Transfer Learning to Accelerate Bioprocess Model Construction
2025
·
Alexander W. Rogers
, Fernando Vega‐Ramon
, et al.
·
Biotechnology and Bioengineering
·
13
PDF
Integrating transfer learning within data-driven soft sensor design to accelerate product quality control
2024
·
Sam Kay
, Harry Kay
, et al.
·
Digital Chemical Engineering
·
11
Symbolic regression based interpretable data-driven soft-sensor for process quality control
2023
·
Harry Kay
, Sam Kay
, et al.
·
Computer-aided chemical engineering/Computer aided chemical engineering
·
8
Integrating feature attribution and symbolic regression for automatic model structure identification and strategic sampling
2025
·
Alexander W. Rogers
, Amanda Lane
, et al.
·
Computers & Chemical Engineering
·
5
A novel approach to identify optimal and flexible operational spaces for product quality control
2025
·
Sam Kay
, Mengjia Zhu
, et al.
·
Chemical Engineering Science
·
3
Improving Fidelity and Diversity in Chemical Language Transformers for Inverse Molecular Design
2026
·
Alexander W. Rogers
, Ruediger Zillmer
, et al.
·
Journal of Chemical Information and Modeling
·
2
Integrating Knowledge-Guided Symbolic Regression and Model-Based Design of Experiments to Accelerate Process Flow Diagram Development
2024
·
Alexander W. Rogers
, Amanda Lane
, et al.
·
IFAC-PapersOnLine
·
2
Interactive Exploration of Ingredient Mixtures Using Multiple Coordinated Views
2009
·
Sara Johansson
, Kristina Knaving
, et al.
·
International Conference on Information Visualisation (IV)
·
2
Data-driven digitalisation of batch operations through automated reconstruction and clustering of process flow diagrams
2026
·
Tom Wyrwoll
, Stephanie Cunliffe
, et al.
·
Digital Chemical Engineering
·
1
Integrating autoencoder and heteroscedastic noise neural networks for industrial data analysis and soft-sensor design
2022
·
Sam Kay
, Harry Kay
, et al.
·
Computer-aided chemical engineering/Computer aided chemical engineering
·
1
Graph-to-Graph Inverse Design of Surfactants under Multiobjective and Structural Constraints
2026
·
Alexander W. Rogers
, Ruediger Zillmer
, et al.
·
Journal of Chemical Information and Modeling
Chemical Language Transformers for the Inverse Design of Novel Surfactants
2026
·
Alexander W. Rogers
, Ruediger Zillmer
, et al.
·
Systems and Control Transactions
PDF
A Surrogate-Enhanced Framework for flexible and optimal operational space identification under uncertainty
2025
·
Sam Kay
, Mengjia Zhu
, et al.
·
Chemical Engineering Science
AI-Driven Automatic Mechanistic Model Transfer Learning for Accelerating Process Development
2025
·
Alexander W. Rogers
, Amanda Lane
, et al.
·
Systems and Control Transactions
PDF
Machine Learning-Aided Robust Optimisation for Identifying Optimal Operational Spaces under Uncertainty
2025
·
Sam Kay
, Mengjia Zhu
, et al.
·
Systems and Control Transactions
PDF
Integrating Knowledge-Guided Symbolic Regression for Model-Based Design of Experiments to Automate Process Flow Diagram Development
2024
·
Alexander W. Rogers
, Amanda Lane
, et al.
·
Computer-aided chemical engineering/Computer aided chemical engineering
Probabilistic machine learning based soft-sensors for product quality prediction in batch processes
2022
·
Max Mowbray
, Aaron Hicks
, et al.
·
Computer-aided chemical engineering/Computer aided chemical engineering
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Works count:
22
Citation count:
162
H-index:
8
I10-index:
7
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