Interdisciplinary Workshop on Machine Learning and AI

Interdisciplinary Workshop on Machine Learning and AI

By University of Liverpool Management School

Overview

Join the LAMBDA Research Centre for an interdisciplinary workshop on 'Machine Learning and AI’.

Hosted by the Liverpool Advanced Methods for Big Data Analytics (LAMBDA) Research Centre, this workshop is organised by LAMBDA Director, Professor Abderrahim Taamouti in collaboration with the Professor Xiaowei Huang from the Department of Computer Science at the University of Liverpool and Professor Taylor. T Johnson from the Department of Computer Science at Vanderbilt University, US.

Participants will have the opportunity to:

  • Learn about the latest research and methodological developments in AI and machine learning across management, economics, data science and related disciplines
  • Discover how these techniques are being applied to address real-world business and policy challenges from improving decision-making to driving productivity and innovation.
  • Connect with colleagues across different disciplines within the School, fostering collaboration and interdisciplinary projects.
  • Exchange ideas and receive feedback on ongoing research in a supportive, intellectually stimulating environment.
  • Build capacity by deepening understanding of data-driven methods that are increasingly vital in both academic research and industry applications.

Whether you're a researcher, student, or professional, this workshop offers a unique opportunity to engage with the University of Liverpool’s experts, discover interdisciplinary insights, and connect with a vibrant community of AI and machine learning enthusiasts at the University of Liverpool.

Category: Science & Tech, Science

Good to know

Highlights

  • 6 hours 15 minutes
  • In person

Location

University of Liverpool School of Law & Social Justice

Event Space

Ground Floor Liverpool L69 7ZR United Kingdom

How do you want to get there?

Organized by

University of Liverpool Management School

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Free
Dec 11 · 10:00 AM GMT