Alexandra Brintrup

University Lecturer in Digital Manufacturing

University of Cambridge

United Kingdom

Research Interests

Explore related searches

Professors in United Kingdom Professors in Machine Learning Machine Learning professors in United Kingdom

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

Articles (16)

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Year:

2022

Collaborators (4)

Dale Rogers

ON Semiconductor Professor of Business

Arizona State University

UNITED STATES

View details

Diego Garlaschelli

Associate Professor (permanent)

IMT Institute for Advanced Studies

ITALY

View details

Ge Zheng

University of Cambridge

UNITED KINGDOM

View details

Dr. Vinod Kumar Chauhan

University of Oxford

UNITED KINGDOM

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Alexandra Brintrup

Research Interests

Explore related searches

Contact this professor

Articles (16)

A federated machine learning approach for order-level risk prediction in Supply Chain Financing

Digital supply chain surveillance using artificial intelligence: definitions, opportunities and risks

Reconstructing supply networks

A review of explainable artificial intelligence in supply chain management using neurosymbolic approaches

Identifying Contributors to Supply Chain Outcomes in a Multiechelon Setting: A Decentralised Approach

Financial ripple effect in complex adaptive supply networks: an agent-based model

Data-driven maintenance priority recommendations for civil aircraft engine fleets using reliability-based bivariate cluster analysis

Federated machine learning for privacy preserving, collective supply chain risk prediction

Real-time large-scale supplier order assignments across two-tiers of a supply chain with penalty and dual-sourcing

Fair collaborative vehicle routing: A deep multi-agent reinforcement learning approach

Bayesian autoencoders with uncertainty quantification: Towards trustworthy anomaly detection

A machine learning approach for predicting hidden links in supply chain with graph neural networks

Towards knowledge graph reasoning for supply chain risk management using graph neural networks

Dynamic inventory replenishment strategy for aerospace manufacturing supply chain: combining reinforcement learning and multi-agent simulation

A hybrid-learning decomposition algorithm for competing risk identification within fleets of complex engineering systems

Do Autoencoders Need a Bottleneck for Anomaly Detection?

Collaborators (4)

Dale Rogers

Diego Garlaschelli

Ge Zheng

Dr. Vinod Kumar Chauhan

Make your next move.