Meet ApplyKite Twin, the application assistant that learns with you

Meet your Twin, it learns with you

Your Twin learns with you

Launch week codes:30% off annual Pro20% off monthly Pro

Ends in00h00m00s

Marvin Carl May

Has grant

Assistant Professor

Nanyang Technological University (NTU)

Singapore

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in Artificial Intelligence

Recent Grants

Grant: Close

Digital Manufacturing Technologies for Zero-defect Industry 4.0 Production

Open Date:

Close Date:

Articles (20)

Year:

2027

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (6)

Gisela Lanza

head of institute

Karlsruher Institut für Technologie

GERMANY

View details

Shady Salama

Assistant professor

Ritsumeikan University

JAPAN

View details

ANDREA MATTA

Professor

Politecnico di Milano

ITALY

View details

Peter Mark

Ruhr-Universität Bochum

GERMANY

View details

Qing Chang

Professor

Stony Brook University

UNITED STATES

View details

John Sutherland

Distinguished Professor and Head

Purdue University

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Marvin Carl May

Research Interests

Make your next move.

Explore related searches

Recent Grants

Articles (20)

Large Language Model-Driven Rescheduling for Semiconductor Manufacturing Equipment Contingency Events

LLM actor-critic based dispatching rule generation for dynamic job shop scheduling

Optimizing Learning Pathways for Digital Twin Education in Manufacturing Systems

Large Language Models for Heuristics to Solve Aggregate Production Planning

A method for considering aleatory and epistemic uncertainties as well as product variance in discrete event simulation of production systems

Condition-aware capacity planning for agile hybrid disassembly systems in remanufacturing

Assisted production system planning by means of complex robotic assembly line balancing

View planning in the visual inspection for remanufacturing using supervised- and reinforcement learning approaches

Unlocking the Potential of Remanufacturing Through Machine Learning and Data-Driven Models—A Survey

Managing product-inherent constraints with artificial intelligence: production control for time constraints in semiconductor manufacturing

Selective disassembly planning considering process capability and component quality utilizing reinforcement learning

IIoT System Canvas — From architecture patterns towards an IIoT development framework

Automated model generation framework for material flow simulations of production systems

Framework for automatic production simulation tuning with machine learning

Reinforcement learning for sustainability enhancement of production lines

Interoperable Architecture For Logical Reconfigurations Of Modular Production Systems

Towards a Service-Oriented Architecture for Production Planning and Control: A Comprehensive Review and Novel Approach

Reinforcement learning for energy-efficient control of multi-stage production lines with parallel machine workstations

Artificial Intelligence Implementation Strategy for Industrial Companies Using the AI Tool Box - A Morphology for Selecting Relevant AI Use Cases

Generalization of Reinforcement Learning Agents for Production Control

Collaborators (6)

Gisela Lanza

Shady Salama

ANDREA MATTA

Peter Mark

Qing Chang

John Sutherland

Make your next move.