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
  • 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
  • Elected to the Executive Board of the ACM Special Interest Group SIGEVO
  • Invited to join the IEEE CIS Evolutionary Computation Technical Committee for 2012
  • Appointed to the UK Operational Research Society Research Panel

 

Conference Organising Activity

  • Senior Program Committee Member AAAI-19
  • Track Chair: Complex Systems @ GECCO 2017
  • General Chair of PPSN 2016, Edinburgh
  • 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: • 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)
  • 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

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

 

Fellowships and Awards

  • Leverhulme Research Fellowship

 

Grant Reviewer

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

 

Invited Speaker

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

 

Media Activity

  • FOCAS project featured in EU FET newsletter
  • 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

 

Research Degree External Examining

  • PhD Examiner: University of Cardiff (School of Mathematics)
  • Phd External Examiner Queen Mary University
  • PhD Examiner: Robert Gordon 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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Date


161 results

Using novelty search to explicitly create diversity in ensembles of classifiers

Conference Proceeding
Cardoso, R. P., Hart, E., Kurka, D. B., & Pitt, J. V. (2021)
Using novelty search to explicitly create diversity in ensembles of classifiers. In GECCO '21: Proceedings of the Genetic and Evolutionary Computation Conference (849-857). https://doi.org/10.1145/3449639.3459308
The diversity between individual learners in an ensemble is known to influence its performance. However, there is no standard agreement on how diversity should be defined, and...

Automated, Explainable Rule Extraction from MAP-Elites archives

Conference Proceeding
Urquhart, N., Höhl, S., & Hart, E. (2021)
Automated, Explainable Rule Extraction from MAP-Elites archives. In Applications of Evolutionary Computation: 24th International Conference, EvoApplications 2021. , (258-272). https://doi.org/10.1007/978-3-030-72699-7_17
Quality-diversity(QD) algorithms that return a large archive of elite solutions to a problem provide insights into how high-performing solutions are distributed throughout a f...

WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets

Conference Proceeding
Pitt, J., Burth Kurka, D., Hart, E., & Cardoso, R. P. (2021)
WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets. In Applications of Evolutionary Computation: EvoApplications 2021 Proceedings. , (649-664). https://doi.org/10.1007/978-3-030-72699-7_41
In order to address scalability issues, which can be a challenge for Deep Learning methods, we propose Wide Learning of Diverse Architectures-a model that scales horizontally ...

Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training

Conference Proceeding
Panagiaris, N., Hart, E., & Gkatzia, D. (2020)
Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training. In Proceedings of the 13th International Conference on Natural Language Generation. , (41-51
In this paper we consider the problem of optimizing neural Referring Expression Generation (REG) models with sequence level objectives. Recently reinforcement learning (RL) te...

Hardware Design for Autonomous Robot Evolution

Conference Proceeding
Hale, M. F., Angus, M., Buchanan, E., Li, W., Woolley, R., Le Goff, L. K., …Tyrrell, A. M. (2020)
Hardware Design for Autonomous Robot Evolution. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (2140-2147). https://doi.org/10.1109/SSCI47803.2020.9308204
The long term goal of the Autonomous Robot Evolution (ARE) project is to create populations of physical robots, in which both the controllers and body plans are evolved. The t...

Evolution of Diverse, Manufacturable Robot Body Plans

Conference Proceeding
Buchanan, E., Le Goff, L., Hart, E., Eiben, A. E., De Carlo, M., Li, W., …Tyrrell, A. M. (2020)
Evolution of Diverse, Manufacturable Robot Body Plans. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI) (2132-2139). https://doi.org/10.1109/SSCI47803.2020.9308434
Advances in rapid prototyping have opened up new avenues of research within Evolutionary Robotics in which not only controllers but also the body plans (morphologies) of robot...

Generating Unambiguous and Diverse Referring Expressions

Journal Article
Panagiaris, N., Hart, E., & Gkatzia, D. (2021)
Generating Unambiguous and Diverse Referring Expressions  . Computer Speech and Language, 68, Article 101184. https://doi.org/10.1016/j.csl.2020.101184
Neural Referring Expression Generation (REG) models have shown promising results in generating expressions which uniquely describe visual objects. However, current REG models ...

Towards Autonomous Robot Evolution

Book Chapter
Eiben, A. E., Hart, E., Timmis, J., Tyrrell, A. M., & Winfield, A. F. (2021)
Towards Autonomous Robot Evolution. In A. Cavalcanti, B. Dongol, R. Hierons, J. Timmis, & J. Woodcock (Eds.), Software Engineering for Robotics (29-51). Springer. https://doi.org/10.1007/978-3-030-66494-7_2
We outline a perspective on the future of evolutionary robotics and discuss a long-term vision regarding robots that evolve in the real world. We argue that such systems offer...

Bootstrapping artificial evolution to design robots for autonomous fabrication

Journal Article
Buchanan, E., Le Goff, L. K., Li, W., Hart, E., Eiben, A. E., De Carlo, M., …Tyrrell, A. M. (2020)
Bootstrapping artificial evolution to design robots for autonomous fabrication. Robotics, 9(4), https://doi.org/10.3390/robotics9040106
A long-term vision of evolutionary robotics is a technology enabling the evolution of entire autonomous robotic ecosystems that live and work for long periods in challenging a...

Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples

Conference Proceeding
Babaagba, K., Tan, Z., & Hart, E. (2020)
Improving Classification of Metamorphic Malware by Augmenting Training Data with a Diverse Set of Evolved Mutant Samples. https://doi.org/10.1109/CEC48606.2020.9185668
Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this,...

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