Andrea Soltoggio received a combined BSc and MSc degree in Computer Science in 2004 from the Norwegian University of Science and Technology, Norway, and from Politecnico di Milano, Italy.  He was awarded a Ph.D. in Computer Science in 2009 from the University of Birmingham, UK. He was with the Laboratory of Intelligent Systems at EPFL, Lausanne, CH, in 2006 and 2008-2009.  He was a visiting researcher at the University of Central Florida, US, in 2009.  From 2010 to 2014 he was Technical Coordinator of the FP7 European large-scale integration project AMARSi with the Research Institute for Cognition and Robotics, Bielefeld University, Germany. From 2014 he is a lecturer in computer science and artificial intelligence at Loughborough University

He is a Fellow of the Higher Education Academy (FHEA).

For applications for PhD studentships please follow this link

See our DARPA ShELL project press release (Sep 2021)

See our DARPA L2M project press release at HRL.

Research areas

My research interests focus on neural plasticity, models of learning and memory, neuro-robotics, deep learning, evolutionary computation, artificial life, adaptive behaviour, human-robot interaction, control systems, cognition and intelligence, movement primitives, motor skills. 

For a list of publications, check the institutional repository or my personal web page.

Selected publications: 

  • Hu, Y, Soltoggio, A, Lock, R, Carter, S (2018)  A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation. Download code from GitHub: https://github.com/cyh4/FCTSFN
  • Skarysz, A., Alkhalifah, Y, Darnley, K, Eddleston, M, Hu, Y, McLaren, DB, Nailon, WH, Salman, D, Sykora, M, Thomas, CLP, Soltoggio, A (2018) Convolutional neural networks for automated targeted analysis of gas-chromatography mass-spectrometry data. In International Joint Conference on Neural Networks, Rio de Janeiro, Brazil. Download PDF.
  • Soltoggio, A, Stanley, K. O., Risi, S. (2017) Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Neural Networks. Neural Networks Journal (2018) arXiv: https://arxiv.org/abs/1703.10371
  • Bahroun, Y, Hunsicker, E, and Soltoggio, A. (2017) “Building Efficient Deep Hebbian Networks for Image Classification Tasks”, ICANN 2017, International Conference on Artificial Neural Networks 
  • Andrea Soltoggio (2014) Short-term plasticity as cause-effect hypothesis testing in distal reward learning, Biological Cybernetics, Feb 2015, Vol 109, p75-94, DOI: 10.1007/s00422-014-0628-0
  • Andrea Soltoggio, Andre Lemme, Felix Reinhart, Jochen J. Steil (2013) Rare neural correlations implement robotic conditioning with delayed rewards and disturbances, Frontiers in Neurorobotics, DOI: 10.3389/fnbot.2013.00006
  • Soltoggio, A., Bullinaria, A. J., Mattiussi, C., Dürr, P. and Floreano, D. (2008) Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward-based Scenarios. Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems. Download PDF

Funded projects: 

  • Defense Advanced Research Project Agency (DARPA) 2021, $893k. Shared Experience Lifelong Learning (principal investigator)
  • Defense Advanced Research Project Agency (DARPA) and US Air Force Research Laboratory, 2018, $680k. Lifelong Learning Machines (L2M) (principal investigator)
  • Innovate UK. 2017-2018, £107k. Knowledge Transfer Partnership. Deep learning and augmented reality deployment on mobile devices (principal investigator)
  • EPSRC 2017-2018, £70k. Digitisation of Collaborative Human-Robot Work Spaces (co-investigator)
  • EPSRC 2016-2017, £18k. Robotics and autonomous systems for manufacturing and infrastructure management (EPSRC Institutional Sponsorship) (co-investigator) (EP/N508706/1)

 Past projects: 

  • Technical co-ordinator of the EU FP7 #248311 AMARSi project (2010-2014), approx. 12 PIs, 30+ full-time researchers.  

I'm a guest editor for Frontiers in Neurorobotics, special issue: Neural plasticity for rich and uncertain robotic information streams.

Reviewer for:

  • Adaptive Behavior
  • AIMS Neuroscience
  • Archives of Pathology and Laboratory Medicine
  • Essays in Biochemistry
  • Frontiers in Computational Neuroscience
  • Frontiers in Psychology
  • IEEE Systems, Man, and Cybernetics, Part A and B
  • IEEE Transaction of Cognitive and Developmental Systems
  • Information Sciences
  • MIT Evolutionary Computation Journal
  • MIT Neural Networks Journal
  • Nature
  • Neural Networks Journal
  • Neurocomputing Journal
  • Robotics and Autonomous Systems
  • Soft Computing

Programme Committee (reviewer) of:

  • International Conference on Learning Representations (ICLR)
  • Genetic and Evolutionary Computation Conference (GECCO)
  • IEEE International Conference on Intelligent Computing
  • International Symposium on Bio-Medical Information and Cybernetics
  • Hybrid Intelligent Systems Conference
  • Congress on Evolutionary Computation (CEC)
  • IEEE Symposium Series on Computational Intelligence for Human-Like Intelligence (CIHLI)
  • Australasian Conference on Artificial Life and Computational Intelligence
  • International Conference on Neural Networks (ICONIP 2011)

In June 2018, our work Convolutional neural networks for automated targeted analysis of gas-chromatography mass-spectrometry data was reported by the following:

a montage of press logos: The Conversation, Focus, Independent, HN, World Economic Forum, BBC Radio Leicester, Smithsonian Magazine, Fox News Channel, Golem.de, Reddit, The Wire, SFG, Tech Explore, Nvdia developer, Newsweek, Ticbeat, Business Insider UK, Inquisitr, Marie Claire, UP magazine.

Press coverage

Outreach activities

  • BBC Radio Leicester, AI to make cars and roads safer. With Jimmy Carpenter (27/9/2021)
  • BBC Radio Leicester. AI becomes a job recruiter. With Jimmy Carpenter (26/9/2019)
  • BBC Radio Leicester. How AI will change our jobs and lifestyle. With Naomi Kent (12/8/2019)
  • BBC Radio Leicester. AI spring. With Jimmy Carpenter (11/4/2019)
  • BBC Radio Leicester. AI developments in 2019. With Jimmy Carpenter (16/1/2019)
  • BBC Radio Leicester. AI in medicine and surgery. With Ed Stagg (12/9/2018)
  • BBC Radio Leicester. Robotics and automation: risks and opportunities in the job market. With Ady Dayman (5/2/2018)
  • BBC One (East Midlands Today). The potential impact to East Midlands region of AI innovation. With Amy Harris (27/11/2017)
  • BBC Radio Leicester. Chatbots and emotional intelligence. With Ady Dayman (24/11/2017)
  • BBC Radio Leicester. AI and chatbots. With Jonathan Lampon (9/8/2017)
  • Debating Society Paderborn, "Bedroht künstliche Intelligenz die Grundlagen unserer Existenz?" (10 July 2016)
  • NAO robots at the British Science Week, STEM day (March 2016, March 2017, March 2018)
  • BBC Radio Leicester. Interview on robotics with NAO robots (14/9/2015)
  • STEM Science Taster Day (22/9/2015)

Administrative roles:

  • 2018 Programme director (Computer Science, Computer Science and AI, Computer Science and Mathematics)
  • 2016-2018 Post Graduate Taught Tutor (MSc thesis coordination)

Teaching

  • Current 2015 - 2021
    • Advanced Artificial Intelligence Systems (Part C). 2017/18, Qubit sponsors three prizes for best projects.  
    •  Artificial Intellience (MSc) 2019-present
  • Past:
    • Managing a project team (Part D)
    • Team projects (Part B) 2015-2018
  • Former institutions (Univesity of Birmingham)
    • Research skills (2008)
    • Evolutionary Computation
    • Neural Computation
    • Design and media team
    • Artificial Intelligence and Cognitive Science

Project/thesis supervision (Part C, Part D, MSc): approximately 50 since 2014.

  • 2018/19 (selected project titles)
    • Trading application with data analysis
    • AI controlled autonomous car network
    • Machine learning for comparing like-parts of song(s) and creating branches between them
    • Deep learning for cryptocurrency market predictions
    • Machine learning based natural language processing chatbot
    • Deep learning for adaptive control systems
    • Convolutional neural networks for image analysis in the biomedical domain
    • Classification of environmental sound events
  • 2017/18 (project titles)
    • Evolution of deep reinforcement learning
    • Deep learning for adaptive control systems
    • Machine learning in breathomics
    • Deep learning for automated cryptocurrency trading
  • older projects:
    • NAO as a robotic personal fitness instructor for children
    • Machine learning for wellbeing analysis
    • NAO as a robotic personal fitness instructor
    • Learning costumers intentions through social media
    • Football match prediction using AI