The Schedule

Opening of UKACM School 

Prof Jelena Ninic (UKACM President) 

Introduction to Digital Twins 

Lecture 1: Reduced Order Modelling 

Lecture 2: Regression-Based Modelling 

Lunch break

Lecture 3: Autoregressive Time Series Modelling 

Lecture 4: Accuracy Quantification and Active Learning 

Wrap-Up

Demonstration of a Full Workflow in Julia and Q&A 

Introduction

Lecture 1: Machine Learning (ML): Decode it all by Interactive Lectures

Break

Lecture 2: Physics-Informed ML Approaches for Mechanics: Landscape and Limitations 

Lunch break

Hands-on session 1: Build a generalised deep learning surrogate for homogenisation: Designing Data, Architecture and Enforcing Physics

Break

Discussions: Do we really need machine learning for mechanics? If yes, when and where?

Introduction

Lecture1: Building Reliable AI-CM Frameworks: Hybrid Architectures for Mechanics Simulations

Break

Lecture 2: Generative AI for Mechanics and Design: How do we approach?

Lunch break

Hands-on session 2: Build Generative Models for Design: Composite Materials and Compressor Blades as Examples

Break

Hands-on session 3: Build Hybrid Modelling Frameworks interfacing Mechanics and Machine Learning

Discussions: Ways Forward to Integrate ML workflows in Mechanics

Welcome & orientation

Lecture1:  What is an agent? ReAct, function-calling, hierarchies, and the LLM substrate

Lecture 2:  Design principles: myths, false friends, known bottlenecks; the harness — observability and evals

Break

Agents applied to computational mechanics: assistive (sim setup, constitutive modelling) and autonomous (auto-research, equation discovery)

Lunch Break

Lab 1 — Build a foundational reasoning-action loop from scratch

Lab 2 — Context management: dynamic solver-documentation lookup to cut syntax hallucination

Lab 3 — To be announced

 Wrap-up, Q&A, where to go next