Manuel Chica Serrano

Ramon y Cajal Senior Researcher

University of Granada

Biography

Manuel Chica is Ramon y Cajal Senior Researcher (RYC-2016-19800), granted by the Spanish Government, at the University of Granada (Computer Science and AI Deparment). He is also Chief AI Officer at ZIO Analytics and Conjoint Lecturer at the University of Newcastle, Australia.

His current research interests include agent-based modeling, evolutionary game theory, single and multi-objective evolutionary optimization, data science, and complex systems. His research is mainly applied and has been applied to a diverse range of fields: from industrial engineering and marketing, to healthcare systems and climate change.

Interests

Artificial Intelligence
Social Simulation
Optimization
Data Science

Education

PhD in Artificial Intelligence and Computer Science (cum laude), 2011
University of Granada
Master in Soft Computing and Intelligent Systems, 2009
University of Granada
MEng in Computer Science, 2006
University of Jaen
BSc in Computing Engineering (Management), 2004
University of Jaen

Publications

JCR-indexed papers

Q1 ranked papers

Citations

More than 1.2K (h-index = 20)

R&D projects

Patents

Academic Positions

Ramon y Cajal Senior Researcher

University of Granada

Jun 2018 – Present Granada, Spain

Researcher at the Computer Science and AI Department. Research, R&D project, and teaching

Conjoint Lecturer

University of Newcastle, Australia

Aug 2017 – Present Callaghan, Australia

Supervision of Master and PhD students, research collaboration, and teaching support

Senior Researcher

Internet Interdisciplinary Institute (IN3)

Jun 2016 – Feb 2017 Barcelona, Spain

Scientific research using optimization algorithms and metaheuristics, complex systems, and projects’ writing.

Visiting Researcher

Wroclaw University of Technology

Sep 2015 – Jan 2016 Wroclaw, Poland

Collaborative work with other members of the EU ENGINE project (social network analysis, simulation, diffusion of innovations)

Visiting Scholar

R.H. Smith School of Business, University of Maryland

Aug 2014 – Dec 2014 College Park, Maryland, US

Research stay, working at the Marketing Department and Center for Complexity in Business

Visiting Researcher

University of Auckland

Sep 2012 – Dec 2012 Auckland, New Zealand

Basic research about metaheuristics, radiation therapy optimization, mathematical programming

Research Assistant

University of Jaen

Aug 2005 – Jun 2006 Jaen

Research on data mining and pre-processing techniques. Develop of feature selection algorithms for the Keel project (a Java open-source data mining software).

Experience in Industry

Chief AI Officer

ZIO Analytics

Apr 2017 – Present Madrid, Spain

Partner, scientific and technological direction, projects’ support.

Deputy Principal Researcher

European Centre for Soft Computing

Feb 2012 – May 2016 Asturias, Spain

R&D projects management. Leading actions on agent-based modelling, system dynamics and artificial economics for brand management and marketing . Applied research on multicriteria decision making. Unit management and preparation of FP7 proposals.

R&D Engineer

Inspiralia

Jul 2008 – Jan 2012 Madrid, Spain

Delivery of FP7 projects related with intelligent systems, image analysis, pattern recognition, data mining and and software development. Technical management of the projects.

Research Assistant

European Centre for Soft Computing

Jun 2007 – Jun 2008 Asturias, Spain

R&D projects about metaheuristics, optimization and production.

Internship

Apple Computer

Mar 2007 – May 2007 Cork, Ireland

Testing of software and hardware devices on Windows over a Mac architecture.

Awards and Grants

Endeavour Research Fellowship

Australian Government Sep 2016 – Feb 2017

Best PhD in Engineering and Architecture

University of Granada Oct 2011

Best Master degree curriculum (course 2001-2006)

University of Jaen Mar 2007

Featured Projects

Multi-manned assembly line balancing

Metaheuristics and mixed integer linear models (MILP) for multi-manned assembly line balancing (MALBP)

PhD Thesis

Ant Colony Optimization (ACO) and Genetic Algorithms to solve the Time and Space Assembly Line Balancing Problem (TSALBP).

SIMARK

Massive Agent-based Simulations and Explainable Artificial Intelligence in Marketing

Zio

A cutting-edge Web application for marketing using agent-based modeling and AI

Toxdtect

The aim of FP7 TOXDTECT project is to develop an intelligent packaging solution for fresh bovine meat products. The technology is based on the identification of specific volatile organic compounds (VOCs) produced inside the packaging during microorganisms’ growth. The signal coming from the interaction between VOCs and polymer inks is recorded by an external device where data are processed. A predictive software based on data mining correlates the sensors signal with the remaining shelf-life of meat (i.e., number of days during which meat is still safe to be consumed).

Forfire

Identimod

A decision support system based on computational intelligence and system dynamics for branding and marketing

Apifresh

A European project funded by the European Commission 7th Framework Program. The objective of the Apifresh project is to provide European beekeepers with the scientific and technological aids necessary to improve the quality of European pollen and royal jelly and also to promote the regulatory means that will allow European bee products compete under fair conditions against lower quality or adulterated products.

Eposbed

This FP7 for SMEs project was developed in Inspiralia to create a medical device which automatically recognizes patient’s intentions. Manuel led the intelligent system based on neural networks to identify the patient’s movements

Featured Publications

Manuel Chica, Juan M. Hernandez, Jacques Bulchand

March 2021 Scientific Reports

A collective risk dilemma for tourism restrictions under the COVID-19 context

COVID-19 pandemic has impacted millions of people and the global economy and tourism has been one the most affected economic sectors. We propose an evolutionary game model that reflects a collective risk dilemma behind these decisions, given that the dependence on tourism of each region is diverse. Our analysis shows that the existence of heterogeneous costs enhances global agreements. A layout of groups based on similar costs of cooperation boosts the regions’ agreements and avoid the risk of having a total lock-down and a negligible tourism activity

PDF

Manuel Chica, Juan M. Hernandez, Casiano Manrique de Lara Penate, Raymond Chiong

January 2021 IEEE Computational Intelligence Magazine

An Evolutionary Game Model for Understanding Fraud in Consumption Taxes

We present a computational evolutionary game model to study and understand fraud dynamics in the consumption tax system, using real-world data of VAT declarations by businesses registered in the Canary Islands, Spain. Players are cooperators if they correctly declare their value added tax (VAT), and are defectors otherwise. We see increasing the subjective audit probability for low transactions is more efficient than increasing this probability for high transactions. Second, favoring social rewards for cooperators or alternative penalties for defectors can be effective policies, but their success depends on the distribution of the audit probability for low and high transactions.

PDF

Manuel Chica, Raymond Chiong, Michael Kirley, Hisao Ishibuchi

January 2018 IEEE Transactions on Evolutionary Computation