Felipe Campelo

Senior Fellow of AdvanceHE/HEA, Ph.D. Systems Science and Informatics, M.Sc. Information Science and Technology, B.Eng. Electrical Engineering

    • School of Engineering and Applied Science, Aston University

      B4 7ET Birmingham

      United Kingdom

    Accepting PhD Students

    PhD projects

    Possible research topics for PhD supervision include:

    - Machine learning approaches for bioinformatics, particularly focused on epitope prediction (e.g., in the context of neglected and emerging diseases)

    - Computational approaches to investigate, select and optimise phage treatments against antibiotic-resistant bacteria.

    - Statistical approaches for performance assessment and comparison of machine learning and optimisation algorithms.

    - Computational Intelligence methods for single and multi-objective optimisation, robust optimisation, constrain handling, applications.

    Personal profile


    Felipe Campelo is a Senior Lecturer and Deputy Head of Computer Science at Aston University.

    After graduating as an Electrical Engineer from Universidade Federal de Minas Gerais (UFMG, Brazil) in 2003, Felipe received the prestigious MEXT (Monbusho) Scholarship from the Japanese government to pursue his postgraduate studies in Hokkaido University, Japan, where he received first his M.Sc. (Information Science and Technology, 2006) and then his Ph.D. (Systems Science and Informatics, 2009). He returned to Brazil for a postdoctoral research post at UFMG in 2009 and joined UFMG's Department of Electrical Engineering in August 2010 as an Assistant Professor in Optimisation and Computational Intelligence. While at UFMG he supervised over 15 postgraduate research students and acted as deputy head of department between 2013 and 2017. He joined Aston University in 2019, and has since been working with applications of optimisation and data science to bioinformatics, as well as other areas of science and engineering. Felipe has been actively involved with the teaching of Data Mining and Data Science to both undergraduate and postgraduate students, and leads the research on machine learning approaches to bioinformatics in the Computer Science department.

    More information is available on ResearchGate or Google Scholar.

    Research Interests

    Dr. Campelo's current research focuses on the development of integrated solution frameworks for prescriptive data analysis, connecting data visualisation, consolidation and pre-processing, modelling, optimisation and decision support for the solution of a variety of problems in science and engineering, with a particular focus towards applications in biology/bioinformatics. He is also involved with the development of methodologically and statistically sound protocols for the experimental comparison of algorithms.

    Teaching Activity

    Undergraduate modules:

    • CS3440 - Data Mining

    Graduate Modules:

    • CS4850 - Data Mining
    • DC4500 - End-Point Assessment

    Membership of Professional Bodies

    Institute of Electrical and Electronics Engineers (IEEE) - since 2004
    Computational Intelligence Society

    Association for Computing Machinery (ACM) - since 2013
    Special Interest Group on Genetic and Evolutionary Computation

    Foundation for Open Access Statistics (FOAS) - since 2019


    2019 - present: Lecturer/Senior Lecturer in Computer Science, Aston University

    2010 - 2018: Assistant/Associate Professor, Department of Electrical Engineering, UFMG, Brazil

    2009 - 2010: Post-doctoral associate, Department of Electrical Engineering, UFMG, Brazil

    Funding Applications and Awards

    Current (granted)

    EPSRC Core Equipment (EP/V036106/1) - Granted October 2020

    • Requested: £249,999; Granted: £390,000
    • PI: Prof. Simon Green, Prof. Patricia Thornley
    • Role: Lead for the Machine Learning Server (~£55k). Co-writing of proposal/case for support.

    InnovateUK / KTP (12334) - Evolyst Ltd. - 2021-2023

    • Requested: £196,599 Granted: £196,599
    • PI: Dr. Chris Buckingham
    • Role: Lead on machine learning and prescriptive analytics. Co-writing of proposal.
    • Other collaborators: Dr. Luis Manso

    Current (Under Review)

    • Project: Cyber-Physical Care Programme (CP2) for supporting vulnerable adults in the community
    • Requested: £149,709
    • PI: Dr. Chris Buckingham
    • Role: Machine learning specialist.
    • Other Collaborators: Dr. Ulysses Bernardet

    Past Funding (as PI or Co-I)

    InnovateUK / KTP (12031) - Smart Apprentices Ltd (2020-2022)

    • Requested: £189,951 Granted: £189,951
    • PI: Dr. Felipe Campelo
    • Role: Original project idea, engagement with company, proposal writing. Project coordination, main supervision of research associate.
    • Collaborators: Dr. Anikó Ekárt

    InnovateUK / KTP (12026) - Arcus FM (2020-2022)

    • Requested: £218,026 Granted: £218,026
    • PI: Dr. Randa Herzallah
    • Role: Lead on optimisation modelling and solution strategy.
    • Other collaborators: Dr. Anikó Ekárt

    Eletrobras/CERON, Brazil - R&D Funding Program (2016-2018)

    • Granted: ~£250k (1.2M BRL)
    • Project: Development of an Integrated Fault Management System for CERON’s Power 
Distribution Grid
    • PI: Dr. Eduardo Carrano, UFMG/Brazil
    • Role: Co-I. Co-writing of application. Development of fault isolation module; Supervision of development and testing of optimisation models.

    CEMIG-D, Brazil - R&D Funding Program (2012-2016)

    • Granted: ~£800k (4.24M BRL)
    • Project: Strategic Asset Management System for CEMIG-D
    • PI: Dr. Eduardo Carrano, UFMG/Brazil
    • Role: Co-I. Co-writing of application. Design, implementation and testing of statistical modelling modules.

    CNPq and FAPEMIG, Brazil - General Funding calls (2011-2019)

    • Total Granted: ~£30k (165k BRL) (excl. salaries and studentships)
    • Role: PI of several projects approved and executed between 2011 and 2019.

    JSPS/Japan and CAPES/ Brazil – Bilateral Collaborations Fund (2013-2015)

    • Granted: ~£35k (5M JPY)
    • Project: Modelling and optimisation of wireless sensor antennas for harvesting environmental microwave radiation.
    • PI: Prof. Hajime Igarashi, Hokkaido University; Prof. Jaime Ramírez, UFMG.
    • Role: Co-I. Co-writing of application. Design of optimisation approaches.

    CAPES and FAPEMIG/Brazil - Graduate Student Funding (2012-2018)

    • Total granted: ~£100k (584k BRL)
    • Full stipend funding for 4 PhD students (4 years each) and 4 MSc Research students (2 years each) obtained via the Studentship Funding Track of UFMG’s Graduate Program in Electrical Engineering.
    • Role: project supervisor.


    PhD Supervision

    PhD Students (Current, Aston)

    Jomar Alcantara (Computer Science. Est. grad.: 2021): Using Language as an Indicator of Cognitive Decline in Pre-Clinical Alzheimer’s Disease. Role: Main supervisor.

    Jodie Ashford (Computer Science. Est. grad.: 2022): Machine Learning Methods for Linear B-Cell Epitope Prediction. Role: Main supervisor.

    Michael Pritchard (Computer Science. Est. grad.: 2022): Using Data from Motor Cortex to Enable a Multimodal Approach to Upper-Limb Prosthesis Control. Role: Associate supervisor.

    Tasmia Azim (Civil Engineering. Est. grad.: 2023): Artificial Intelligence for integrated management of linear highway assets. Role: Associate Supervisor.

    PhD Students (Current, external)

    Igor Lobo (UFMG/Brazil, PhD Genetics): Applications of machine learning to reverse vaccinology: prediction and validation of vaccine candidates based on parasite genomic data. Role: Advisory committee member (machine learning, data visualization); host of exchange student (Feb - Aug 2021, funded by Capes/Brazil).

    Reem Abukmeil (Dalhousie University/Canada, PhD Engineering): Machine Learning Approaches for Image-based Nutrient Deficiency Sensing. Role: Advisory committee member (data preprocessing and visualisation, statistical modelling, machine learning)

    PhD Students (Past)

    Athila Trindade (UFMG, 2019): A New SMBO-Based Parameter Tuning Framework for Optimisation Algorithms. Role: Main supervisor.

    Fernanda Takahashi (UFMG, 2018): Sample Size Estimation for Power and Accuracy in the Experimental Comparison of Meta-heuristics. Role: Main supervisor

    André Maravilha (UFMG, 2018): Development of Matheuristics for MIP Problems with Binary Variables. Role: Main supervisor.

    Fillipe Goulart (UFMG, 2018): Preference-guided Optimisation for the Load Restoration Problem. Role: Main supervisor.

    André L. Silva (UFMG, 2016): Modelling and Optimisation of Vehicle Routing and Loading Problem with Multiple Stacks. Role: Main supervisor.

    Rafael F. Alexandre (UFMG, 2015): Dynamic Dispatch of a Heterogenous Fleet of Trucks in Open-pit Mining Operations Using Evolutionary Multi-objective Optimisation.
    Role: Associate supervisor.


    Other Research Students (past)

    UFMG, MSc Electrical Engineering (2-year combined taught + research degree): main supervisor of 8 students between 2011 and 2019 (https://ppgee.ufmg.br/bancodefesasi.php)


    Research and industry awards

    • OSE Awards 2019: Best R&D Project and Best Project Overall in the Brazilian electrical sector. Project: Development of an Integrated Fault Management System for CERON’s Power Distribution Grid. Belo Horizonte, Brazil, 2019
    • Best Paper Award on the Symposium of the Japanese Society of Evolutionary Computation. Paper: Understanding Multi-objective Evolutionary Algorithms through Component Oriented Design. Kyoto, Japan, 2017.
    • Best Paper Award on the 14th Brazilian Meeting on Artificial and Computational Intelligence. Paper: A Preference-guided Multi-objective Evolutionary Algorithm based on Decomposition. Uberlândia, Brazil, 2017.
    • Best Paper Award on the 2nd IEEE Latin American Congress on Evolutionary Computation. Paper: Towards Statistical Convergence Criteria for Mutation-Based Evolutionary Algorithms. Curitiba, Brazil, 2015.
    • Best Student Paper Award on the 2011 IEEE Congress on Evolutionary Computation. Paper: A Comparison of Dominance Criteria in Many-Objective Optimisation Problems. New Orleans, USA, 2011.
    • Best Poster Award on the 2008 IEEE Conference on Electromagnetic Field Computation. Paper: Hybrid Estimation of Distribution Algorithm Using Local Function Approximations. Athens, Greece, 2008.


    Teaching and Supervision awards

    Distinguished Professor (distinction that each class of graduates confers upon the member of the teaching staff that they considered the most influential or inspirational over their entire degree):

    • BSc Systems Engineering, UFMG: 2016, 2018
    • BSc Aerospace Engineering, UFMG: 2014
    • BSc Electrical Engineering, UFMG: 2012

    Best 2018-19 MSc Computer Science (Supervisor), Aston University. Student: Jodie Ashford. Project: Real Time Classification of EEG Signals from MUSE Headband.

    Best 2018 PhD thesis (Supervisor), Graduate Program in Electrical Engineering, UFMG. Student: Fillipe Goulart. Project: Permutation-based Optimisation for the Load Restoration Problem with Improved Time Estimation of Manoeuvres.

    Top 3 PhD Theses in Computational Intelligence 2018-19 (Supervisor), Brazilian Congress on Computational Intelligence 2019. Student: Fillipe Goulart. Thesis: Permutation-based Optimisation for the Load Restoration Problem with Improved Time Estimation of Manoeuvres.

    Top 3 MSc Dissertations in Computational Intelligence 2014-15 (Supervisor), Brazilian Congress on Computational Intelligence 2015. Student: Fillipe Goulart. Thesis: Preference-guided Evolutionary Algorithms for Optimization with Many Objectives.

    Administrative Roles

    Aston University, UK

    • Deputy Head of Computer Science (since Sep 2020)
    • Head for Engagement and Progression (2019-2022)
    • Member, ASTUTE board (2021-22), IT Expert Group (since 2022)

    UFMG, Brazil (selected)

    • Vice-Head of Department (peer-elected, 2013-15 and 2015-17)
    • President, Electrical Engineering Teaching Activities Committee (2011-2018)
    • Member, Department Management Team (peer-elected, 2013-2019)
    • Member, Systems Eng. Programme Design and Assessment Committee (2012-2018)
    • Member, Grad. Programme Electrical Engineering Management Team (2014-2018)
    • University Research Integrity Committee (2014-2015)
    • Permanent staff hiring committees (2013, 2014, 2016, 2018)

    Chair and member for international conferences

    Organisation of major conferences

    IEEE Congress on Evolutionary Computation, Glasgow, 2020.
    Role: Chair, Multi-Objective Optimization and Applications Session.

    IEEE World Congress on Computational Intelligence, Rio de Janeiro, 2018.
    Role: Social Media Chair; Local Organising Committee.

    Intl. Conference on Evolutionary Multi-criterion Optimisation, Ouro Preto, Brazil, 2011.
    Role: Local Organising Committee


    Invited Talks and presentations

    LIFELIKE workshop, Prague, Czechia, 2022. Keynote Talk: Sharks, Zombies and Volleyball - lessons from the Evolutionary Computation Bestiary.

    Computational Intelligence for Massive Optimisation Workshop, Lille, France, 2019. Sample Size Calculations for the Experimental Comparison of Algorithms.

    Evolutionary Computation in Practice Workshop, Genetic and Evolutionary Computation Conference, Denver, USA, 2016: Evolutionary Algorithms for Aeronautical Optimisation.

    Latin American School of Computational Intelligence, Curitiba, Brazil, 2015. Design of Experiments and Statistical Comparison of Evolutionary Algorithms.

    5th International Meeting on Speech Sciences, Belo Horizonte, Brazil, 2015. Design and Analysis of Experiments.


    Presentations at International Events

    EvoStar (2022)

    ACM Genetic and Evolutionary Computation Conference (2017, 2016, 2014)

    Latin American Congress on Computational Intelligence (2015)

    BRICS Countries Congress on Computational Intelligence (2013)

    Intl. Conf. Evolutionary Multi-criterion Optimisation (2011, 2007)

    IEEE Congress on Evolutionary Computation (2010, 2006)

    IEEE Conf. Computation of Electromagnetic Fields (2009, 2007, 2005)

    Iberian-Latin American Congress on Comp. Methods in Engineering (2009, 2003)

    IEEE Conf. Soft Computing in Industrial Applications (2008)

    IEEE Conf. Electromagnetic Fields Computation (2008)

    Intl. Symposium on Applied Electromagnetics and Mechanics (2007)

    IGTE Symposium (2006)

    Workshop on Optimisation and Inverse Problems in Electromagnetism (2006)

    Education/Academic qualification

    SFHEA, Senior Fellow of AdvanceHE/HEA, AdvanceHE

    Award Date: 12 May 2020

    Data Science Specialisation, Johns Hopkins University / Coursera

    7 Dec 20142 Dec 2015

    Award Date: 2 Dec 2015

    PhD, Evolutionary Design of Electromagnetic Systems using Topology and Parameter Optimization.

    3 Apr 200630 Jan 2009

    Award Date: 26 Mar 2009

    MSc, Immune Algorithms for Optimization of Electromagnetic Systems

    1 Sept 200426 Mar 2006

    Award Date: 26 Mar 2006

    BSc, Electrical Engineering

    1 Mar 199830 Jun 2003

    Award Date: 4 Aug 2003

    External positions

    Adjunct of the Faculty of Graduate Studies

    1 Jan 202130 Jun 2026

    Associate Professor

    6 Aug 201820 Jan 2019

    Assistant Professor

    6 Aug 20105 Aug 2019


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