Professor Ferrante Neri
Academic and research departments
Nature Inspired Computing and Engineering Research Group, Department of Computer Science, Surrey Institute for People-Centred Artificial Intelligence.About
Biography
I am an all-round academic equally passionate about teaching and research. My teaching expertise is about Mathematical subjects for Computer Science while my research expertise lies at the intersection of Optimisation, Explainable AI, and Machine Learning. I am also happy to serve the community I work for, by undertaking managerial duties.
Before joining the faculty at Surrey I was at the University of Nottingham and previously I was at De Montfort University and at the University of Jyväskylä (Finland). I am a scholar in Optimisation and Computational Modelling. I work at the boundary between mathematical theory and practical engineering solutions. I’m the author of Linear Algebra for Computational Sciences and Engineering. I am also a very active editor for multiple journals including Information Sciences, Memetic Computing, and Integrated Computer-Aided Engineering.
My qualifications
Previous roles
Affiliations and memberships
ResearchResearch interests
My research expertise is in optimisation and machine learning. I am currently interested in algorithmic design for black-box optimisation problems informed by fitness landscape analysis. This topic lies at the intersection of optimisation, both exact and heuristic, and machine learning. I am also interested in applications of data science.
Historically, my main topic has been (and still is) the design and understanding of meta-heuristic algorithms. The main two subareas I contributed to are Memetic Computing and Differential Evolution. Since 2010 I am Chair/Vice-Chair of the IEEE Task Force on Memetic Computing.
Indicators of esteem
In the list of the top 2% scientists according to Stanford World Ranking of Scientists
Research interests
My research expertise is in optimisation and machine learning. I am currently interested in algorithmic design for black-box optimisation problems informed by fitness landscape analysis. This topic lies at the intersection of optimisation, both exact and heuristic, and machine learning. I am also interested in applications of data science.
Historically, my main topic has been (and still is) the design and understanding of meta-heuristic algorithms. The main two subareas I contributed to are Memetic Computing and Differential Evolution. Since 2010 I am Chair/Vice-Chair of the IEEE Task Force on Memetic Computing.
Indicators of esteem
In the list of the top 2% scientists according to Stanford World Ranking of Scientists
Supervision
Postgraduate research supervision
Current PhD students and starting month
- Aisha E S E Saeid Aug 2022
If you are looking for a PhD in a topic related to Artificial Intelligence, send me an email to have an informal chat about it. Please include in your email
- your CV
- a short description of the topic (maximum 2 pages) you would like to investigate
- a statement about how you are planning to fund your PhD studies, e.g., you are self-funded, have a scholarship, or are seeking for financial support
Be aware that PhD scholarships are available only at some points of the year through competitive processes (usually deadlines in January to start in October).
Postgraduate research supervision
Graduated PhD students
Hoang Lam Le, University of Nottingham. Thesis: “Novel Strategies to Accelerate Search Algorithms in Data Reduction", 2022
Shouyong Jiang, De Montfort University, "Dynamic Multi-Objective Optimisation", 2017
Michael Cochez, University of Jyväskylä, “Taming Big Knowledge Evolution”, 2016
Fabio Caraffini, De Montfort University, “Novel Memetic Structures for Continuous Optimisation”, 2014
Ilpo Poikolainen, University of Jyväskylä, “Simple Memetic Computing Structures for Global Optimization”, 2014
Annemari Soranto, University of Jyväskylä, “Interest-based topology management in unstructured peer-to-peer networks”, 2012
Ernesto Mininno, University of Jyväskylä, “Advanced Optimization Algorithms for Applications in Control Engineering”, 2011
Giovanni Iacca, University of Jyväskylä, “Memory-saving Optimization Algorithms for Systems with Limited Hardware”, 2011
Matthieu Weber, University of Jyväskylä, “Parallel Global Optimization, Structuring Populations in Differential Evolution”, 2010
Ville Tirronen with University of Jyväskylä, “Global Optimization using Memetic Differential Evolution with Applications to Low-Level Machine Vision”, 2008
Teaching
Happiness is to be understood – Georgi Polonsky – (We’ll Live Till Monday)
Past Teaching as module leader
Undergraduate Modules
- 2020-2022 Mathematics for Computer Scientists 2, University of Nottingham, UK
- 2019-2022 Languages and Computation, University of Nottingham, UK
- 2018-2019 Abstract Algebra I and II, De Montfort University, UK
- 2015-2018 Linear Algebra and Discrete Mathematics, De Montfort University, UK
- 2014-2018 Foundations and Algebra, De Montfort University, UK
- 2012-2013 Introduction to Artificial Intelligence and Mobile Robotics, De Montfort University, UK
- 2012-2013 Connected Devices, De Montfort University, UK
Postgraduate Modules
- 2013-2015 Computational Intelligence Optimisation, De Montfort University, UK
- 2007-2012 Research Projects, University of Jyväskylä, Finland
- 2007 Evolutionary Computational Intelligence, University of Jyväskylä, Finland
International Research/Postgraduate Modules
- 2020 Automatic Design of Optimisation Algorithms in the Continuous Domain, NATCOR Course Heuristics & Approximation Algorithms, Nottingham, UK
- 2008 Medicine+Computer Science=Computational Medicine; Computational Intelligence for Multi-drug Therapies, Winter School on Mathematical and Computational Biology, University of Newcastle, Australia
- 2007 Recent Advances in Evolutionary Computing, 17th Jyväskylä Summer School, University of Jyväskylä, Finland