{"id":33,"date":"2016-10-09T10:00:42","date_gmt":"2016-10-09T09:00:42","guid":{"rendered":"https:\/\/dke.maastrichtuniversity.nl\/enrique.hortal\/?page_id=33"},"modified":"2022-03-29T13:10:39","modified_gmt":"2022-03-29T12:10:39","slug":"home-page","status":"publish","type":"page","link":"https:\/\/dke.maastrichtuniversity.nl\/enrique.hortal\/","title":{"rendered":"Home page"},"content":{"rendered":"
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Enrique Hortal<\/h3>\n

Welcome to my online curriculum\u00a0<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

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About me
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Personal Info<\/h3>\n

Name<\/strong>: Enrique Hortal Quesada<\/p>\n

Date of birth:<\/strong> 30 April 1985<\/p>\n

Nationality:<\/strong> Spanish<\/p>\n

Location:<\/strong> Maastricht, the Netherlands<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

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\n\t\t\tIn April 2016, I\u00a0joined the\u00a0Department of Data Science and Knowledge Engineering (renamed in 2022 as the Department of Advanced Computing Sciences<\/a>, DACS), at the Maastricht University<\/a>, the Netherlands, as post-doctoral researcher in the RAI (Robotics, Agents and Interactions) group<\/a>. Since August 2019 I work as an assistant professor in the same department. My teaching activities are mainly related to Computer Science and Machine Learning. From the academic year 2019\/2020 I am also the coordinator of the Bachelor thesis for the BSc on Data Science and Artificial Intelligence at the DACS department.<\/p>\n

I have a background in brain signal processing and classification as a member of the Brain Machine Interface Systems Lab at Miguel Hern\u00e1ndez University of Elche, Spain. In this group, I developed my first experience as a researcher, obtaining a PhD in Industrial and Telecommunications Technologies in February 2016.<\/p>\n

My research interests include machine\/deep learning, human-machine interaction, (bio)signal processing and analysis and affective computing. Until March 2019, I was working on MaTHiSiS project as a senior researcher in charge of coordination and research activities and co-supervising two PhD candidates. In the context of this European project (Horizon2020-ICT-20-2015), we developed an adaptive learning platform to enhance vocational training, workplace learning and mainstream education for individuals with or without learning disabilities. In parallel and currently, I am carrying out teaching responsibilities in several courses such as Computer Sciences and Machine Learning, the coordination\/examination of BSc research projects as well as the supervision of several BSc and Master students’ thesis.<\/p>\n

Thank you for visiting my profile!<\/em><\/p>\n

\u00a1Gracias por visitar mi perfil!<\/em>\t\t<\/div>\n<\/p><\/div>\n

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Experience
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Maastricht University, the Netherlands<\/h2>\n

August 2019 – Present<\/p>\n

Assistant professor at the Department of Advanced Computing Sciences.<\/p>\n

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April 2016 – July 2019<\/p>\n

Post-doctoral researcher at the Department of Advanced Computing Sciences .<\/p>\n

Miguel Hern\u00e1ndez University of Elche, Spain<\/h2>\n

September 2012 – December 2015<\/p>\n

Scienctific Researcher at the Engineering and Automation Department and member of the Brain-Machine Interfaces Systems Lab.<\/p>\n

Sistemas Avanzados Telecom Levante, Spain<\/h2>\n

\u00a0February 2007 – August 2012<\/p>\n

Microcontroller programmer at the Computer Science Department<\/p>\n

Miguel Hern\u00e1ndez University of Elche, Spain<\/h2>\n

October 2006 – January 2007<\/p>\n

Maintenance and management of laboratory of high frequency electronic devices at the Engineering Department<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

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Education
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Miguel Hern\u00e1ndez University of Elche, Spain<\/h2>\n

PhD in Industrial and telecommunications technologies (Tecnolog\u00edas Industriales y de Telecomunicaci\u00f3n)<\/p>\n

February 2016<\/p>\n

Miguel Hern\u00e1ndez University of Elche, Spain<\/h2>\n

Master Degree in Industrial and telecommunications technologies (Tecnolog\u00edas Industriales y de Telecomunicaci\u00f3n)<\/p>\n

October\u00a02012<\/p>\n

Miguel Hern\u00e1ndez University of Elche, Spain<\/h2>\n

Bachelor degree in Telecommunications engineering, specialized in electronic systems (Ingeniero t\u00e9cnico en telecomunicaciones, especializado en sistemas electr\u00f3nicos)<\/p>\n

February 2009<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

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Projects
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JOINclusion – Joint problem-solving strategy towards social inclusion of children with a migrant background<\/h2>\n
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JOINclusion is an Erasmus+ project under the Key Action 2 – Cooperation partnerships in school education with a total budget of 291.240 \u20ac.<\/p>\n

JOINclusion is intended to foster the\u00a0social inclusion<\/b>\u00a0of ALL children primary school students (with particular attention to those with a migrant background) through the use of a collaborative mobile application. This tool, designed by psychologists specializing in the field, aims to develop\u00a0empathy\u00a0<\/b>learning scenarios strengthening the impact of their use. The scenarios are designed to\u00a0promote dialogue<\/b>\u00a0between participants and facilitate channels to express themselves, promoting integration. Both the game and its scenarios are designed based on schools needs, involving end-users since early stages of the project development.<\/p>\n<\/div>\n<\/div>\n

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Furthermore, the\u00a0collaborative serious game\u00a0<\/b>is boosted by machine learning techniques conceived to enhance user experience and optimize its efficiency as a tool promoting prosociality through\u00a0personalisation based on affect detection<\/b>. The interactions with the collaborative serious game is also designed to encourage self-reflection and post-game interaction among the members of the targeted groups (children with and without a migrant background) while, for children at risk of exclusion, it promotes\u00a0reassurance<\/b>\u00a0to encourage them to learn to act as equal members of their new community and\u00a0find their place in society<\/b>.<\/p>\n<\/div>\n<\/div><\/div>\n<\/p><\/div>\n

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MaTHiSiS – Managing Affective-learning THrough Intelligent atoms and Smart InteractionS
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MaTHiSiS (Managing Affective-learning THrough Intelligent atoms and Smart InteractionS) is a H2020 project under the topic ICT-20-2015 Technologies for better human learning and teaching with a total cost of \u20ac7.618.584.<\/p>\n

The MaTHiSiS learning vision is to provide a product-system for vocational training and mainstream education for both individuals with an intellectual disablity and non-diagnosed ones. This product-system consists of an integrated platform, along with a set of re-usable learning components (educational material, digital educational artefacts etc.), which will respond to the needs of a future educational framework, as drawn by the call, and provide capabilities for: i) adaptive learning, ii) automatic feedback, iii) automatic assessment of learner\u2019s progress and behavioural state, iv) affective learning and v) game-based learning.<\/p>\n

The MaTHiSiS consortium is coordinated by Atos Spain and consists of 18 beneficiary organizations from 9 different Member States collaborating, namely Spain, France, Greece, UK, Netherlands, Belgium, Italy, Lithuania and Germany.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

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BioMot – Smart wearable robots with biospired sensory-motor skills
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The main objective of the project is to improve existing wearable robotic exoskeletons exploiting dynamic sensory-motor interactions and developing cognitive capabilities that can lead to symbiotic gait behavior in the interaction of a human with a wearable robot.<\/p>\n

BioMot proposes a cognitive architecture for WRs exploiting neuronal control and learning mechanisms which main goal is to enable positive co-adaptation and seamless interaction with humans.<\/p>\n

BioMot consortium brings together eight (8) partners from five different countries (Spain, Belgium, Italy, Iceland and Japan) on the basis of the multidisciplinary expertise and trans-nationality required for meeting its ambitious objectives and ensuring proper exploitation of results, both scientifically and clinically\/commercially.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

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Brain2Motion – Exoskeletal-neuroprosthesis\u00a0hybrid robotic system for the upper limb controlled by a multimodal brain-neural interface
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Exoskeletal robots (ERs) are person-oriented robots that supplement the function of a limb or replace it completely. A possible alternative to ERs are Motor Neuro-Prostheses (MNP) based on Functional Electrical Stimulation (FES). Both ERs and MNPs are technologies that seek to restore or substitute motor function. MNPs constitute an approach to restoring function by means of artificially controlling human muscles or muscle nerves with FES. ERs use volitional commands for controlling the application of controlled forces to drive paralyzed or weak limbs.<\/p>\n

The main goal of BRAIN2MOTION project is to develop a new hybrid ER-MNP for the upper limb interfaced to the users by means of non-invasive multimodal brain-neural computer interfaces (BNCIs). The robotic hybrid system will combine a light and kinematically compatible ER, and a textile-based surface MNP. In this combined ER-MNP, hardware and control strategies will be developed to combine the action of the ER and MNP while preserving motor latent capabilities of the user. A spontaneous non- invasive EEG-based Brain-Computer Interface (BCI) and an electrooculography (EOG) interface will compose the multimodal BNCI. The BCI will differentiate more than three mental tasks. This will be achieved incorporating new adaptive classifiers into the BCI. Learning strategies will be developed in order to improve the performance and versatility of the BCI. Control strategies combining EEG and EOG signals will be developed to control the ER-MNP.<\/p>\n

The hybrid ER-MNP controlled by the BNCI will be used to perform reaching and grasping operations. The system will be validated with patients suffering from neurological conditions leading to severe motor disorders, in particular cerebrovascular accident (CVA).<\/p>\n<\/p><\/div>\n<\/p><\/div>\n

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Publications
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Books:<\/h2>\n