Emma Hart
Emma Hart

Prof Emma Hart

Professor

 0131 455 2783

  E.Hart@napier.ac.uk

  

Biography

Prof. Hart gained a 1st Class Honours Degree in Chemistry from the University of Oxford, followed by an MSc in Artificial Intelligence from the University of Edinburgh. Her PhD, also from the University of Edinburgh, explored the use of immunology as an inspiration for computing, examining a range of techniques applied to optimisation and data classification problems. 

She moved to Edinburgh Napier University in 2000 as a lecturer, and was promoted to a Chair in 2008 where she leads a group in Nature-Inspired Intelligent Systems, specialising in optimisation and learning algorithms applied in domains that range from combinatorial optimisation to robotics. Her work mainly involves development of algorithms inspired by biological evolution to discover novel solutions to challenging problems.

She was appointed as Editor-in-Chief of Evolutionary Computation (MIT Press) in 2017. She has been invited to give keynotes at major international conferences including CLAIO 2020, IEEE CEC 2019, EURO 2016 and UKCI 2015 and was General Chair of PPSN 2016, and as a Track Chair at GECCO for several years. She is an elected member of the Executive Board of the ACM SIG on Evolutionary Computation.

More broadly, she invited member of the UK Operations Research Society Research Panel, and in Scotland, co-leads the Artificial Intelligence theme within SICSA. She was appointed as a panel member for REF2021 (UoA11 Computer Science). In 2020 she was appointed to the Steering Committee that developed Scotland's AI Strategy published in 2021 . She has a sustained track record of obtaining funding from the EU, EPSRC and of engaging with industry via KTP projects and consultancy, and participates enthusiastically in public-engagement activity, e.g Pint of Science.

Her work in evolutionary robotics has attracted significant media attention, e.g. in New Scientist, the Guardian, Telegraph and the Conversation. In 2021, she gave a TED Talk on Evolutionary Robotics, available online

School

Research Groups

Themes

Research Areas

News

Events

Esteem

Advisory panels and expert committees or witness

  • Scottish Government Steering Committee: AI Strategy
  • Royal Society’s International Networks Committee
  • Appointed to the UK Operational Research Society Research Panel
  • Elected to the Executive Board of the ACM Special Interest Group SIGEVO
  • Invited to join the IEEE CIS Evolutionary Computation Technical Committee for 2012
  • Member of Royal Society delegation of UK scientists in UK-Russia Frontiers of Science Symposium (Kazan)
  • Invited to co-lead SICSA Research Theme on Artificial Intelligence

 

Conference Organising Activity

  • Senior Program Committee Member AAAI-19
  • Track Chair: Complex Systems @ GECCO 2017
  • General Chair of PPSN 2016, Edinburgh
  • Workshop Chair: • ECAL 2013, 1st Workshop on Fundamentals of Collective Systems, Italy
  • Co-chair and organiser, Dagstuhl Seminar on Artificial Immune Systems, 2011
  • Workshop co-chair: Steering Complex Adaptive Systems, ECAL 2015: 12th International Conference on Artificial Life
  • Technical Chair BioNETICS 2009, Avignon
  • General Chair: 9th International Conference on Artificial Immune Systems at Edinburgh Napier
  • Technical Chair of Bionetics 2011, York, UK
  • Chair of Workshop in Self-Organisation in Pervasive Adaptive Systems, at IEEE SASO 2010, Budapest. 28th September 2010
  • Track Chair: Artificial Immune Systems at GECCO 2014, an ACM SIGEVO Conference.
  • Track Chair: Artificial Immune Systems and Biological and Medical Applications, Genetic & Evolutionary Computation Conference, GECCO 2016
  • Track Chair. Real-World Applications of Optimisation at GECCO 2015 (ACM)
  • Technical chair of IEEE Congress on Evolutionary Computing (CEC), 2009
  • Workshop co-chair: ALIFE 2016, 2nd Workshop on Steering Complex Systems (Cancun, Mexico)
  • Program Chair of the ninth IEEE International Conference on Self-Adaptive and Self- Organizing Systems (2015)
  • Workshop Chair: IEEE SASO, 2nd Workshop on Fundamentals of Collective Systems, London,
  • Workshop Chair: IEEE SASO 2011, 1st Workshop on Self-Awareness in Autonomic Computing USA
  • Workshop Chair, Real-World-Optimisation @ GECCO 2013
  • Workshop Chair: 2nd Awareness workshop at IIEEE SASO 2012 : Challenges for Achieving Self-awareness in Autonomic Systems

 

Editorial Activity

  • Editor of the ACM SIGEVO newsletter
  • Editorial Board: International Journal Metaheuristics
  • Editor-in-Chief of Evolutionary Computation (MIT Press)
  • Associate Editor of the Journal of Evolutionary Computation (MITPress)
  • Guest Editor: Scalable Computing: Practice and Experience (Special Issue on Collective Adaptive Systems)
  • Guest Editor: Swarm Intelligence: (Special Issue on Artificial Immune Systems) 2010
  • Guest Editor: Special Issue of J. Evolutionary Intelligence on Aspects of Artificial Immune Systems

 

Fellowships and Awards

  • Leverhulme Research Fellowship

 

Grant Reviewer

  • Grant reviewer: Leverhulme Trust
  • Grant reviewer: Carnegie Trust
  • Re-elected to EPSRC peer review college

 

Invited Speaker

  • Invited Talk: Tecnologico de Monterrey, Mexico
  • Invited Talk: University of St Andrews (Computer Science)
  • AHDB Smart Agriculture Conference (Invited Speaker)
  • Invited Seminar: University of Aberystwyth: Seminar, Life Long Learning in Optimisation
  • University of Stirling: Research Seminar
  • University of Nottingham Research Seminar
  • Invited Speaker: Women@GECCO workshop, GECCO 2015
  • Keynote Speaker at 28th European Conference on Operational Research in Poznan in July 2016
  • Inivited Talk: Mathematical Modelling of Wind Risk, Arcachon, France. Optimisation for Forestry
  • Keynote: 15th UK Conference on Computational Intelligence (UKCI 
2015

 

Media Activity

  • The PerAda project hosted a public debate "Emotion as Interface" at Edinburgh International Science Festival, chaired by Emma Hart, with panel guests Prof Kevin Warwick, Prof Nikola Serbedzija, ad Dr Jenny Tillotson
  • FOCAS project featured in EU FET newsletter

 

Research Degree External Examining

  • PhD Examiner: University of Cardiff (School of Mathematics)
  • PhD Examiner: Robert Gordon University
  • Phd External Examiner Queen Mary University
  • PhD Examiner University of Edinburgh
  • PhD Examiner: University of York
  • PhD Examiner: University of Hong Kong
  • PhD Examiner: University of Aberytwyth
  • PhD Examiner: Manchester Metropolitan
  • PhD examiner, University of Pretoria, South Africa
  • PhD Examiner University of Kent Canterbury
  • PhD Examiner University of YorK (Computer Science)
  • PhD examiner, University of Nottingham
  • PhD external examiner at Hong Kong Polytechnic University
  • PhD Examiner: Swinburne University of Technology, Australia
  • PhD at the University of Cardiff, in the School of Computer Science and Informatics
  • PhD examiner at the University of York

 

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161 results

Evolutionary Approaches to Improving the Layouts of Instance-Spaces

Conference Proceeding
Sim, K., & Hart, E. (2022)
Evolutionary Approaches to Improving the Layouts of Instance-Spaces. In Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022 (207-219). https://doi.org/10.1007/978-3-031-14714-2_15
We propose two new methods for evolving the layout of an instance-space. Specifically we design three different fitness metrics that seek to: (i) reward layouts which place in...

A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem

Conference Proceeding
Marrero, A., Segredo, E., León, C., & Hart, E. (2022)
A Novelty-Search Approach to Filling an Instance-Space with Diverse and Discriminatory Instances for the Knapsack Problem. In Parallel Problem Solving from Nature – PPSN XVII. PPSN 2022 (223-236). https://doi.org/10.1007/978-3-031-14714-2_16
We propose a new approach to generating synthetic instances in the knapsack domain in order to fill an instance-space. The method uses a novelty-search algorithm to search for...

Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers

Conference Proceeding
Cardoso, R. P., Hart, E., Burth Kurka, D., & Pitt, J. (2022)
Augmenting Novelty Search with a Surrogate Model to Engineer Meta-Diversity in Ensembles of Classifiers. In Applications of Evolutionary Computation: EvoApplications 2022 (418-434). https://doi.org/10.1007/978-3-031-02462-7_27
Using Neuroevolution combined with Novelty Search to promote behavioural diversity is capable of constructing high-performing ensembles for classification. However, using grad...

Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn

Book Chapter
Hart, E. (2022)
Lifelong Learning Machines: Towards Developing Optimisation Systems That Continually Learn. In A. E. Smith (Ed.), Women in Computational Intelligence: Key Advances and Perspectives on Emerging Topics (187-203). Cham: Springer. https://doi.org/10.1007/978-3-030-79092-9_9
Standard approaches to developing optimisation algorithms tend to involve selecting an algorithm and tuning it to work well on a large set of problem instances from the domain...

Morpho-evolution with learning using a controller archive as an inheritance mechanism

Journal Article
Le Goff, L. K., Buchanan, E., Hart, E., Eiben, A. E., Li, W., De Carlo, M., …Tyrrell, A. M. (in press)
Morpho-evolution with learning using a controller archive as an inheritance mechanism. IEEE Transactions on Cognitive and Developmental Systems, https://doi.org/10.1109/tcds.2022.3148543
Most work in evolutionary robotics centres on evolving a controller for a fixed body-plan. However, previous studiessuggest that simultaneously evolving both controller ...

Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning

Journal Article
Hart, E., & Le Goff, L. K. (2022)
Artificial evolution of robot bodies and control: on the interaction between evolution, individual and cultural learning. Philosophical Transactions B: Biological Sciences, 377(1843), https://doi.org/10.1098/rstb.2021.0117
We survey and reflect on evolutionary approaches to the joint optimisation of the body and control of a robot, in scenarios where a the goal is to find a design that maximises...

Enhancing the practicality of tools to estimate the whole life embodied carbon of building structures via machine-learning models

Journal Article
Pomponi, F., Luque Anguita, M., Lange, M., D'Amico, B., & Hart, E. (2021)
Enhancing the practicality of tools to estimate the whole life embodied carbon of building structures via machine-learning models. Frontiers in Built Environment, 7, Article 745598. https://doi.org/10.3389/fbuil.2021.745598
The construction and operation of buildings account for significant environmental impacts, including greenhouse gas (GHG) emissions, energy demand, resource consumption and wa...

A Neural Approach to Generation of Constructive Heuristics

Conference Proceeding
Alissa, M., Sim, K., & Hart, E. (2021)
A Neural Approach to Generation of Constructive Heuristics. In 2021 IEEE Congress on Evolutionary Computation (CEC) (1147-1154). https://doi.org/10.1109/CEC45853.2021.9504989
Both algorithm-selection methods and hyper-heuristic methods rely on a pool of complementary heuristics. Improving the pool with new heuristics can improve performance, howeve...

A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics

Book Chapter
Stone, C., Hart, E., & Paechter, B. (2021)
A Cross-Domain Method for Generation of Constructive and Perturbative Heuristics. In N. Pillay, & R. Qu (Eds.), Automated Design of Machine Learning and Search Algorithms (91-107). Springer. https://doi.org/10.1007/978-3-030-72069-8_6
Hyper-heuristic frameworks, although intended to be cross-domain at the highest level, usually rely on a set of domain-specific low-level heuristics which exist below the doma...

On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme

Conference Proceeding
Goff, L. K. L., & Hart, E. (2021)
On the challenges of jointly optimising robot morphology and control using a hierarchical optimisation scheme. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference Companion (1498-1502). https://doi.org/10.1145/3449726.3463156
We investigate a hierarchical scheme for the joint optimisation of robot bodies and controllers in a complex morphological space. An evolutionary algorithm optimises body-plan...

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