News: The Distributed Algorithms CDT takes part in the latest Siemens Challenge

Published on 5 May 2021

A group of PhD students from the Distributed Algorithms CDT at the University of Liverpool are participating in a competition run by Siemens, namely ‘Artificial Intelligence Dependability Assessment - Student's Challenge’.   

 

The Challenge 

The challenge is suitable for AI-learning students who will be able to contribute their knowledge and ideas to improving safety decisions in mobility.  Students are encouraged to develop an AI model for a simple classification problem with demanding safety requirements, with ‘trust’ being central to the investigative research.  

There are a number of parameters in place and the students are tasked with producing a model with certain classifications.  Details of the challenge can be found here.  There is a prize fund of 10,000 EUR for the best and most reliable AI models.  

Our students have been distributed into five teams, each of which utilise a different AI technique to tackle the challenge. The techniques employed include Gaussian Processes, Kernel Methods, and Variational Autoencoders. Each of these approaches address a number of the requirements outlined, if not in their entirety. 

Siemens  

Siemens is a technology company focused on industry, infrastructure, mobility, and healthcare. Creating technologies for more resource-efficient factories and resilient supply chains to smarter buildings and grids, to cleaner, comfortable transportation and advanced healthcare, the company empowers customers to transform the industries that form the backbone of economies, transforming the everyday for billions of people. 

Distributed Algorithms CDT 

The Distributed Algorithms CDT is an Innovative Data Science, AI and Machine Learning Research Centre, aligning PhD students, academics and industrialists to work together to generate novel solutions to tough data science challenges. If you would like to find out more about our programme and would like to talk about becoming an active member of our CDT community, please visit our website or email kelli.cassidy@liverpool.ac.uk