Event Archive

2024

February

• Phi-ML meets Engineering: Enhancing Scientific Computing Through Physics-Informed Neural Networks

  01 February 2024, 13:00 - 14:00

  The group will provide an overview of the current capabilities and limitations of Physics-Informed Neural Networks (PINNs), highlighting diverse applications where PINNs have proven to be highly effective compared to traditional approaches. Additionally, they will explore extensions of the PINN method, such as conservative PINNs (cPINNs) and eXtended PINNs (XPINNs),...

January

• The Turing-Roche knowledge share series: Transparent AI for healthcare (Virtual Seminar)

  30 January 2024, 15:00 - 16:00

  A series for Turing-Roche partnership updates, knowledge sharing and new perspectives, this event will be on the topic of transparency in AI and the different ways this can be considered. We will be hearing from our Turing-Roche Senior Postdoctoral Research Associate Dr Tapabrata Rohan Chakraborty. Rohan will talk about the different...

• Policy Priorities & AI for SDGs

  29 January - 09 February 2024

  29 January to 2 February and 9 February, 2024 (online event)

• AI's Data Dilemma: Confronting the Paradox of Poor Quality Data in the Age of AI

  26 January 2024, 12:00 - 13:00

  University of Exeter (live-streamed)

• Tech-Talk: A principled approach to writing collaborative research code (Virtual Seminar)

  23 January 2024, 15:00 - 16:00

  At this first Turing-Roche Partnership Community Scholar Tech Talk, we will hear from final-year Oxford University DPhil student, Claudia Vanea. Claudia will explore the most useful techniques and practises for writing collaborative research code with examples from research codebases and personal experience. She will focus on version control, abstraction, project...

• Phi-ML meets Engineering: Feature Encoded and Multi-Resolution Physics-Informed Machine Learning Approaches for Musculoskeletal Digital Twin Applications

  18 January 2024, 13:00 - 14:00

  Machine Learning (ML) approaches offer effective tools to identify biological system properties from physiological measurements, e.g., motion data and raw surface electromyography (sEMG), providing opportunities to construct a subject-specific musculoskeletal (MSK) digital twin system for health condition assessment and motion prediction. This event forms part of the Physics-informed machine learning...