
Professor Peter Flach
M.Sc.(Twente)
Current positions
Professor of Artificial Intelligence
Department of Computer Science
Contact
Media contact
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Research interests
Short Biography
Peter Flach has been Professor of Artificial Intelligence at the University of Bristol since 2003. An internationally leading researcher in the areas of mining highly structured data and the evaluation and improvement of machine learning models using ROC analysis, he has also published on the logic and philosophy of machine learning, and on the combination of logic and probability. He is author of Simply Logical: Intelligent Reasoning by Example (John Wiley, 1994) and Machine Learning: the Art and Science of Algorithms that Make Sense of Data (Cambridge University Press, 2012).
From 2010 to 2020, Prof Flach was the Editor-in-Chief of the Machine Learning journal, one of the two top journals in the field that has been published for over 25 years by Kluwer and now Springer. He was Programme Co-Chair of the 1999 International Conference on Inductive Logic Programming, the 2001 European Conference on Machine Learning, the 2009 ACM Conference on Knowledge Discovery and Data Mining, and the 2012 European Conference on Machine Learning and Knowledge Discovery in Databases in Bristol. He is a founding board member and current President of the European Association for Data Science.
Prof Flach's research has been funded by EPSRC, MRC, TSB and the EU, among others. He is currently leading the Machine Learning work package in the SPHERE Next Steps project funded by EPSRC, and Director of the UKRI Centre for Doctoral Training in Interactive Artificial Intelligence.
Expertise
My main expertise is in data-driven computational methods such as machine learning and data science, and in human-centred artificial intelligence which combines data-driven and knowledge-driven approach to AI with human-AI interaction and responsible AI.
Keywords
- Machine Learning
- Data Science
- Human-Centred Artificial Intelligence
Projects and supervisions
Research projects
8030 H2020 TAILOR 952215
Principal Investigator
Managing organisational unit
Department of Computer ScienceDates
01/09/2020 to 31/08/2023
InnovateUK ML4D: Machine Learning for Enhanced Diabetes Self-Care
Principal Investigator
Role
Co-Investigator
Description
Innovate UK: Digital health technology catalyst round 2, collaboration between Quin Technologies Ltd and University of BristolManaging organisational unit
Department of Computer ScienceDates
01/11/2018 to 30/04/2020
Towards a Measurement Theory for Data Science and Artificial Intelligence
Principal Investigator
Managing organisational unit
Department of Computer ScienceDates
01/11/2018 to 30/04/2021
SPHERE2
Principal Investigator
Role
Co-Investigator
Managing organisational unit
Department of Electrical & Electronic EngineeringDates
01/10/2018 to 30/09/2021
SPHERE (EPSRC IRC)
Principal Investigator
Role
Principal Investigator
Description
SPHERE : An EPSRC Interdisciplinary Research Collaboration (IRC).
This project aims to develop a platform of sensors to be deployed in people's homes to monitor the health and wellbeing
SPHERE is…Managing organisational unit
Department of Electrical & Electronic EngineeringDates
01/10/2013 to 30/09/2018
Thesis supervisions
Object-oriented data mining
Supervisors
Higher-order frameworks for profiling and matching heterogeneous data
Supervisors
Towards Intelligible and Robust Surrogate Explainers
Supervisors
Efficient Continual Learning
Supervisors
Publications
Selected publications
01/04/2017Beta calibration
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS 2017)
Computational support for academic peer review
Communications of the ACM
Background Check
2016 IEEE 16th International Conference on Data Mining (ICDM 2016)
Unsupervised learning of sensor topologies for improving activity recognition in smart environments
Neurocomputing
Reframing in context
AI Communications
Recent publications
03/02/2022Continuous Adaptation with Online Meta-Learning for Non-Stationary Target Regression Tasks
Signals
Co-Designing Personal Health?
Proceedings of the ACM on Human-Computer Interaction
Machine Learning Explanations as Boundary Objects: How AI Researchers Explain and Non-Experts Perceive Machine Learning
Joint Proceedings of the ACM IUI 2021 Workshops
Efficient and Robust Model Benchmarks with Item Response Theory and Adaptive Testing
International Journal of Interactive Multimedia and Artificial Intelligence
Risk Sensitive Model-Based Reinforcement Learning using Uncertainty Guided Planning
Risk Sensitive Model-Based Reinforcement Learning using Uncertainty Guided Planning