In the modern world, we generate large and diverse datasets describing all kinds of systems in the real and virtual worlds.

One of the main goals of Artificial Intelligence is to process, understand and extract useful information from such data. In the group at York, we work with data that has a particular interesting, complex or unusual structure. 

Contact us

Professor Richard Wilson

Professor Richard Wilson

Artificial Intelligence Research Group lead

richard.wilson@york.ac.uk

Related links

AI Google site

In the modern world, we generate large and diverse datasets describing all kinds of systems in the real and virtual worlds. One of the main goals of Artificial Intelligence is to process, understand and extract useful information from such data. In the group at York, we work with data that has a particular interesting, complex or unusual structure.

Examples include natural language processing, where we work on understanding natural language, knowledge representation and generating natural-feeling dialogues between human and computer, and on reasoning and argumentation. Other interesting datasets are represented by networks, which are used extensively throughout the sciences to represent power grids, road systems, animal interactions, protein networks in cells and airline connections, and there are countless other examples.

At York, we explore new representations and algorithms for learning about and extracting information from these datasets. Other systems may have complex configurations and constraints, and here we study the use of AI to automatically model and solve these systems. One of the core topics of the group is the development of novel learning algorithms for these difficult datasets, using bio-inspired techniques such as multi-agent systems, genetic algorithms and reinforcement learning. 

The main aim of the AI group is to carry out cutting-edge research into data-driven algorithms and techniques for discovering information from large and complex datasets. We work to develop novel learning algorithms for this data, methods for representing rich and complex data and problems, and how to extract and codify knowledge from data. The data we study has interesting structure, such as sequences, networks and graphs, natural language and data governed by constraints. Our objectives are

  • To discover new methods for machine learning with structured data. This includes both data representation and learning techniques.
  • The study of new machine learning techniques such as multi-agent systems, bio-inspired algorithms and reinforcement learning.
  • To develop systems which can learn about natural dialogue and argument between human and computer.
  • The development of intelligent automated modelling for large combinatorial problems with significant constraints.

The group's research is driven by the study of real-world problems such as fact checking, RNA classification, telemedicine, city planning, financial data, computational chemistry, games and many other areas.

Artificial Intelligence has huge potential to tackle real-world problems, and the AI group is extensively involved in applications of their work in the real world. Members of the group have worked on the problem of fake news detection. Other work in the group has been applied in the medical domain, both for telemedicine for Covid-19 patients and in the study of Alzheimer's disease. Machine learning has been applied to infrastructure inspection problems, including railway maintenance and solar panel inspection. Our work on analytics is currently being applied to the study of safe driving in cars. Constrained combinatorial optimisation is of huge commercial importance (for example in logistics and operations research) and our work in this area contributes to improving solvers in the commercial setting. Games and gaming are also a large commercial concern now, and members of the group have made contributions to games, game AI, game difficulty assessment and gaming analytics.

Stories

Group members

Photo Contact details
Academic staff
Dr Tarique Anwar

Dr Tarique Anwar

Academic staff

tarique.anwar@york.ac.uk

Dr Dimitar Kazakov

Dr Dimitar Kazakov

Academic staff

dimitar.kazakov@york.ac.uk

Dr Peter Nightingale

Dr Peter Nightingale

Academic staff

peter.nightingale@york.ac.uk

Mr Frank Soboczenski

Academic Staff

frank.soboczenski@york.ac.uk

Dr James Walker

Dr James Walker

Academic staff

james.walker@york.ac.uk

Professor Richard Wilson

Professor Richard Wilson

Academic staff - group lead

richard.wilson@york.ac.uk

 Dr Tommy Yuan

Dr Tommy Yuan

Academic Staff

tommy.yuan@york.ac.uk

Research staff
Felix Ulrich-Oltean

Felix Ulrich Oltean

Research Associate

Postgraduate research students
Noof Alfear 

Noof Alfear

Postgraduate Research Student

Zainab Almugbel 

Zainab Almugbel

Postgraduate Research Student

Fahad Alzaidee

Fahad Alzaidee

Postgraduate Research Student

fmfa501@york.ac.uk 

Charmaine Barker

Charmaine Barker

Postgraduate Research Student

charmaine.barker@york.ac.uk

Philip Crispin

Philip Crispin

Postgraduate Research Student

philip.crispin@york.ac.uk

Kevin Denamganai 

Kevin Denamganai

Postgraduate Research Student

Adrian de Wynter

Adrian de Wynter

Postgraduate Research Student

adrian.dewynter@york.ac.uk

Hani Elgabou 

Hani Elgabou

Postgraduate Research Student

Can Erten 

Can Erten

Postgraduate Research Student

Mark Ferguson 

Mark Ferguson

Postgraduate Research Student

Yusif Ibrahimov

Postgraduate Research Student

Viktor Ivanov 

Viktor Ivanov

Postgraduate Research Student

Adam Katona 

Adam Katona

Postgraduate Research Student

Alan Pedrassoli Chitayat 

Alan Pedrassoli Chitayat

Postgraduate Research Student

Hosein Rezaei

Hosein Rezaei

Postgraduate Research Student

hosein.rezaei@york.ac.uk

Jonathan Oliva Salinas

Jonathan Oliva Salinas

Postgraduate Research Student

Chris Solomou 

Chris Solomou

Postgraduate Research Student

Tianda Sun

Tianda Sun

Postgraduate Research Student

Other affiliates
Dr Adrian Bors 

Dr Adrian Bors

Affiliate

adrian.bors@york.ac.uk

Dr Simon OKeefe

Dr Simon O'Keefe

Affiliate

simon.okeefe@york.ac.uk

 Jamie Sykes

Jamie Sykes

Affiliate

  

Contact us

Professor Richard Wilson

Professor Richard Wilson

Artificial Intelligence Research Group lead

richard.wilson@york.ac.uk

Related links

AI Google site