Digital twins for multiphase flow systems Integrating data, physics and machine learning to develop rapid predictive models for engineered multiphase flow systems
AI for control problems Using a competition platform to accelerate progress in data-driven control problems
Optimising hypertension management strategies Using smart algorithms to optimise treatment decisions in blood pressure management and reduce economic burden on healthcare providers
Safe AI for surgical assistance Developing methods for assistive robots to learn correct actions from human experts, in the domain of surgical assistance in operating rooms
Detecting hazardous physical activity Using human action detection to monitor safety in hazardous or physically demanding situations, such as escalator use and offshore wind turbine work
Critical infrastructures as a control system Developing smart data communication protocols to achieve robustness and resilience of complex critical infrastructures
Mathematics and data Thursday 12 Sep 2019 Time: 10:00 - 18:00 Alexander Gorban Chaim Even-Zohar Felipe Rincon Ginestra Bianconi John Oprea Nati Linial Shay Moran
Towards Autonomous Robotic Systems Conference (TAROS) Wednesday 03 Jul 2019 - Friday 05 Jul 2019 Time: 09:00 - 18:00
The future of test & evaluation in defence: AI and autonomy Wednesday 19 Jun 2019 Time: 10:00 - 17:30
The next step in precision agriculture Growing enough food for the world’s burgeoning population may require smart farms that can sense their crop conditions and feed themselves on demand, and Turing researchers are developing the technology they’ll need
Machine learning and dynamical systems How do we analyse dynamical systems on the basis of observed data, rather than attempt to study them analytically?