Applications for Ph.D. studentships: follow the link at: http://www.lboro.ac.uk/study/postgraduate/apply/

See our STELLAR-DARPA project press release at HRL.

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.

I'm currently supervising 7 Ph.D. students, and have 2 Ph.D. students completions in 2017 and 2018.

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
  

The word cloud of our new review paper: 

Funded projects: 

• 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:

• 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:

Press coverage

• BBC Radio Leicester. Lifelong Learning Machines: a DARPA project at Loughborough University (with Jimmy Carpenter, 11/4/2019)
• Nvidia Developer Newsletter: https://news.developer.nvidia.com/ai-can-smell-illnesses-in-human-breath/
• World Economic Forum: https://www.weforum.org/agenda/2018/06/ai-is-acquiring-a-sense-of-smell-that-can-detect-illnesses-in-human-breath-15f84f2f-865b-453a-b834-7ccef8d626a7
• The Conversation: https://theconversation.com/ai-is-acquiring-a-sense-of-smell-that-can-detect-illnesses-in-human-breath-97627
• BBC Radio Leicester. AI can smell illnesses in human breath (19 June 2018)

Outreach activities

• 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 - 2019
  • Advanced Artificial Intelligence Systems (Part C). 2017/18, Qubit sponsors three prizes for best projects.  
  • Managing a project team (Part D)  
• Past:
  • 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

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).