Photo of Dr Alberto Moraglio

Dr Alberto Moraglio

Senior Lecturer in Computer Science


Location: Innovation Centre Phase 1 M1b

Telephone: 01392 726628

Extension: (Streatham) 6628

Alberto holds a PhD in Computer Science from the University of Essex (2007) and Master and Bachelor degrees (Laurea) in Computer Engineering from the Polytechnic University of Turin, Italy. Before joining Exeter as a Lecturer in Computer Science (2013), he worked as a Research Fellow at the University of Birmingham on Complexity Analysis of Evolutionary Algorithms and at the University of Kent on Genetic Programming, as an Assistant Professor in the Department of Computer Engineering at the University of Coimbra, Portugal, and as a Researcher for HP Labs in Bristol on Multi-Agent Systems.

He has been active in Evolutionary Computation research for the last 2 decades with a substantial publication record in the area. He is the founder of the Geometric Theory of Evolutionary Algorithms, which unifies Evolutionary Algorithms across representations and has been used for the principled design of new successful search algorithms and for their rigorous theoretical analysis. He has pioneered the use of semantics in Genetic Programming, and invented Geometric Semantic Genetic Programming, a novel and very successful form of Genetic Programming with strong theoretical foundations, which has gained wide adoption in applications and has been used and extended by many research groups world-wide. 

Since 2018, Alberto has been working as a research consultant for Fujitsu Research Laboratores on Optimisation on Quantum Annealing Machines. He has formulated dozen of Combinatorial Optimisation problems in a format suitable for the Quantum hardware. He is also the inventor of a software (compiler) aimed at making these machines usable without specific expertise by automating the translation of high-level description of combinatorial optimisation problems to a low-level format suitable for the Quantum hardware (patented invention).

Research interests: general principles, theory and complexity analysis, principled design, representations and operators for bio-inspired search heuristics, including genetic programming and evolutionary approaches to machine learning, quantum optimisation and quantum machine learning.



  • ECMM444/ECMM456: Fundamentals of Data Science
  • ECM3412/ECMM409: Nature-Inpired Computation
  • ECMM423: Evolutionary Computation & Optimisation
  • ECM2423: Artificial Intelligence & Applications
  • ECM2419: Database Theory and Design
  • Introduction to Natural Computation (Birmingham)
  • Introduction to Artificial Intelligence (Coimbra)
  • Databases and Data Mining (Coimbra)
  • Informatic Systems (Coimbra)
  • Genetic Programming and Its Applications (Essex)

Students Wanted:

  • PhD studenship available to work on theory and applications of evolutionary algorithms (email me if interested)
  • I am interested in supervising students with projects in Evolutionary Computation and Heuristic Optimisation

Recent activities & news:

  • Main organiser of Workshop on Quantum Optimisation at GECCO 2022
  • Workshops chair (PPSN 2014, GECCO 2021, GECCO 2022)
  • Invited Conference Tutorials 'Semantic Genetic Programming' at GECCO, IEEE CEC, PPSN 2013-2020
  • GECCO Track Chair (Theory 2013, Genetic Programming 2015, Genetic Algorithms 2016-2017)
  • Co-chair of European Conference on Genetic Programming (2012 and 2013)
  • Co-organiser of Workshop on Semantic Methods in Genetic Programming (PPSN/GECCO 2014-2016)
  • Co-editor of the Theoretical Computer Science journal special issue on "Evolutionary Computation 2013"
  • Co-editor of the Springer book "Theory and Principled Methods for the Design of Metaheuristics"

Other relevant information: