Richard Allmendinger

Prof

  • Professor of Applied Artificial Intelligence, Associate Dean for Business Engagement, Civic and Cultural Partnerships for the Faculty of Humanities, Management Sciences
  • Alliance Manchester Business School, The University of Manchester , Room 3.017, Booth Street West

    M15 6PB Manchester

    United Kingdom

Accepting PhD Students

PhD projects

- Bayesian optimisation
- Reinforcement learning
- Machine learning
- Search
- Explainable AI
- AI applications

Personal profile

Biography

Richard is Associate Dean for Business Engagement, Civic & Cultural Partnerships of the Faculty of Humanities, and Professor of Applied Artificial Intelligence at The University of Manchester. 

He is also co-Lead of the North West Productivity Forum, External Examiner for Warwick Business School, Senior Member of the IEEE, Vice-Chair of the IEEE Bioinformatics and Bioengineering Technical Committee, Editorial Board Member of several international journals, Senior Scientist at Eharo, and AI Advisor for Guru AI (an AI-driven music education spin-out) and River Capital, a private equity business managing the first dedicated AI fund in the North of UK. 

Prior to Manchester, he was Honorary Lecturer and Research Associate at the Biochemical Engineering Department, University College London.  He studied Business Engineering at the Karlsruhe Institute of Technology and the Royal Melbourne Institute of Technology and completed a PhD in Computer Science (Machine Learning & Optimization) at The University of Manchester.

Richard's research interests are in the field of data science and in particular in the development and application of optimization and machine learning techniques to real-world problems arising in areas such as healthcare, manufacturing, engineering, economics, sports, music, and forensics. Much of research has been funded by UK funding bodies (e.g. ESRC, EPSRC, Innovate UK) and industrial partners.

Overview

Qualifications

 

Opportunities

I am interested in supervising research students in the following areas:

  • Multiobjective optimization
  • Non-standard optimization and learning problems
  • Expensive optimization 
  • Merging optimization with machine learning
  • Real-world applications of optimization and machine learning
  • Decision-support systems

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 4 - Quality Education
  • SDG 7 - Affordable and Clean Energy
  • SDG 8 - Decent Work and Economic Growth
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 10 - Reduced Inequalities
  • SDG 11 - Sustainable Cities and Communities
  • SDG 12 - Responsible Consumption and Production
  • SDG 13 - Climate Action
  • SDG 16 - Peace, Justice and Strong Institutions
  • SDG 17 - Partnerships for the Goals

External positions

AI Advisor , Guru AI

Jan 2024 → …

Senior Scientist - Artificial Intelligence, Applied AI & Decision Science Specialist , Eharo Ltd

Apr 2023 → …

Advisory Board Member, Alliance Fund Managers Ltd

1 Dec 2022 → …

External Examiner, Warwick Business School

1 Nov 2020 → …

RMIT Honorary, Royal Melbourne Institute of Technology

1 Feb 201930 Apr 2019

Areas of expertise

  • QA75 Electronic computers. Computer science
  • optimization
  • decision-support systems
  • real-world problems
  • TS Manufactures
  • biochemical Engineering
  • Bioprocessing

Research Beacons, Institutes and Platforms

  • Institute for Data Science and AI
  • Digital Futures
  • Biotechnology
  • Sustainable Futures
  • Christabel Pankhurst Institute
  • The Productivity Institute

Fingerprint

Dive into the research topics where Richard Allmendinger is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
  • 1 Similar Profiles

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or