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Josep Lluís Arcos
Research Scientist

T: (+34) 93 580 9570
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Research
Projects
PhD Students
Publications
Google Scholar
Teaching
Talks
Awards
CV

Research Interests

Machine Learning for Healthcare

Interested in the research on machine learning and time-series analysis algorithms able to process big data in an efficient, adaptive, and robust way. Currently focused on Oocyte Biology Research (see Eurova Training Network and 2019-DI-24), on the assessment of the indoor air quality effects in health (see K-HiA project), on their application to Cognitive Stimulation and Rehabilitation (see Play&Sing, Innobrain, and Cognitio projects), and on Chronicity and Autism Spectrum Disorders (see BioMoCISVA and AMATE projects).

Machine Learning for Music

Another topic of my interest is the use of Machine Learning techniques to reason and learn about musical processes like expressive music generation. Currently focused on the study of musical expressivity in Nylon Guitars (see guitarLab) and social tools for music education (see PRAISE). We have studied the issue of expressiveness in the context of tenor saxophon interpretations (see Saxex and TempoExpress systems) in collaboration with the Music Technology Group (UPF).

Current Projects

Visor EEG: dispositiVo regIStro hOlter seRas EEG
K-HiA: Knowledge for improving indoor Air quality and Health
Eurova: European Oocyte Biology Research Innovation Training Network
2019-DI-24: Machine learning applications for the prediction of effective treatments in human infertility
Play&Sing: Playing and Singing for the Recovering Brain
Crowd4SDG: Citizen Science for Monitoring Climate Impacts and Achieving Climate Resilience
TECSAM: Innovation Network for New Technologies in Mental Health
CI-SUSTAIN: Advanced Computational Intelligence Techniques for Reaching Sustainable Development Goals

Past Projects

NanoMOOCs: New audiovisual format with advanced technological capabilities for learning
BioMoCISVA: Biometrical monitoring of Chronically ill and Support through a Virtual Agent
Innobrain: New technologies for the innovation in cognitive stimulation and rehabilitation
Draga: Digital Reconstruction of the Prehistoric Past
CityBeats: Meaningful civic engagement to build human cities
AMATE: Data-Mining for Therapeutic Analysis of Behaviors in Autism Spectrum Disorders
NASAID: New trends of ML systems for data-based computer science
Cognitio: Case-Based Reasoning for the optimization of cognitive rehabilitation on TBI
PRAISE: Practice and peRformance Analysis Inspiring Social Education
AT: Agreement Technologies
WorthPlay: Worth Playing Digital Games for Active and Positive Ageing
Next-CBR: Evolving CBR for multi-source experience and knowledge-rich applications
EVE: Engineering Self-* Virtually-Embeded Systems
BUSCAMEDIA: Atomatic generation of narrative content
ANERIS: Development of an Intelligent Oceanographic Probe with Autonomous Sampling Capabilities
ONCNOSIS: Identification of biomarkers with diagnostic and therapeutic value for the neoplastic disease
IEA: Autonomic Electronic Institutions
MID-CBR: An Integrative Framework for Developing Case-based Systems
eRep: Social Knowledge for e-Governance
QUALNAVEX: Qualitative Navigation of Autonomous Robots with Learning by Experience capabilities
CBR-ProMusic: Case-Based Reasoning for Content-Based Music Processing
TMS: The Touring Management System
ARGOS-QUALNAV: Autonomous Robot navigation guided by visual targets
TABASCO: Content-based Audio Transformation
e-Institutor: Automatic trade by Intelligent Autonomous agents in electronic Institutions
IBROW: An Intelligent Brokering Service for Knowledge-Component Reuse on the World Wide Web
MLnet II: Network of Excellence in Machine Learning II
Smash: Sistemas Multi-agente y su aplicación en servicios hospitalarios
COMRIS: Co-Habited Mixed-Reality Information Spaces
MLnet: Network of Excellence in Machine Learning
ANALOG: Foundations of Analogical Inference and their Applications to Symbolic Reasoning and Learning
AMP: A Learning System Based on a Massive Memory Architecture
SPES: Specification of Parallel Expert Systems

Current PhD Students

Athanasiou, Georgios (Eurova Training Network) Topic: Machine Learning for Healthcare
Correa, Núria (Industrial PhD) Topic: Machine Learning for Healthcare
David, Gomez (Co-advisored with ICO) Topic: Machine Learning for Healthcare
Velasco, Borja (Industrial PhD, AQUAS) Topic: Machine Learning for Healthcare

Former PhD Students

Tan Hakan Ozaslan (Ph.D. in 2013) Currently Big Data Scientist at Google
José Luis Fernández (Ph.D. in 2011) Currently at University of Geneva
Maarten Grachten (Ph.D. in 2006) Currently at Austrian Research Institute for Artificial Intelligence
Mulayim, Oguz (Ph.D. in 2020) Currently Postdoc researcher in the Crowd4SDG project
Sánchez-Pinsach, David (Ph.D. in 2020) Currently at Institut Guttmann, Neurorehabilitation hospital

Former Post-Doctoral Researchers

Ismel BritoCurrently at Lemonade Software Development
Enric GuausCurrently at ESMUC
Aaron MonteroCurrently Data Scientist at Chemotargets
Arturo RibesCurrently CEO at WeAR Technologies
Joan SerràCurrently at Dolby Labs.

Former Master Students

Sara Hoeksma (UPC, 2018)Artificial Intelligence Techniques to support Cognitive Rehabilitation
Daniel Verdes (UAB, 2018)Data Mining methodology to early detection of Alzheimer
Sergi Cebrián (UAB, 2018)Model-free video game personalization for educational serious games
Ferran Mestres (UAB, 2014)Q-Learning in an Open-Space Combat Scenario for Real-Time Strategy Games
David Perálvarez (UAB, 2013)Choosing the Recommender System to Best Fit Data
Albert Vilamala (UAB, 2010)Detection and Identification of Phytoplankton Assemblages using Case-Based Reasoning
Tan Hakan Ozaslan (UPF, 2009)Expressive Analysis of Violin Performers
Jose Luis Fernández (UAB, 2007)Modeling of Dynamic Systems by Artificial Neural Networks
Àngela Fàbregas (UAB, 2007)Identification of key elements for the control of complex systems
Christian Haendhel (U. Bremen, 2001)Case-based generation of melodic improvisations
Maarten Grachten (U.Groningen, 2001)Domain-based generation of melodic improvisations

Teaching

Teacher at Universitat de Girona (Advanced Techniques of Artificial Intelligence). Promoter of the Smart Healthcare Master.
I regularly teach master courses on Machine Learning and Case-Based Reasoning at different Spanish Universities.
Occasionally, I perform talks about AI and Healthcare, AI and Music, Machine Learning, or Self-* systems.

Awards

2013 "Best Paper Award" in the Int. Conf. on Advanced Cognitive Technologies and Applications (COGNITIVE-13)
2012 "Best in Class Award" in the 2012 Music Information Retrieval Evaluation eXchange contest (MIREX-12 Structure Segmentation task).
2006 "Best Paper Award" in the European Conference on Case-Based-Reasoning (ECCBR-06)
2005 "Best In Class Award" in the First Annual Music Information Retrieval Evaluation eXchange Contest (MIREX-05 Symbolic Melodic Similarity Contest).
2003 "Best Paper Award" in the International Conference on Case-Based-Reasoning (ICCBR-03)
1997 "Swets & Zeitlinger Distinguished Award" in the International Computer Music Conference (ICMC-97)

CV

Visiting Researcher at McGill University, collaborating with Dr. Robert J. Zatorre, Montreal Neurological Institute (2012).

Visiting Researcher at CIRMMT, collaborating with Dr. Marcelo M. Wanderley, Centre for Interdisciplinary Research in Music Media and Technology (2012).

Research Scientist at the Artificial Intelligence Research Institute (IIIA-CSIC) since 2009.

Visiting Researcher at Indiana University, collaborating with Dr. David B.Leake, School of Informatics and Computing (2005).

Tenured Scientist at the Artificial Intelligence Research Institute (IIIA-CSIC) from 2000 to 2009.

Head of the Technology Transfer Unit (UDT-IA) at de IIIA-CSIC from 2002 to 2007.

Ph.D. on Computer Science by the Technical University of Catalunya (UPC) in 1997. The Phd was devoted to the design and implementation of the Noos representation language (Advisor Enric Plaza). The Noos language is a reflective object-centered representation language for developing knowledge systems that integrate problem solving and learning. Learning methods were introduced as reasoning methods with introspection capabilities able to improve/modify the knowledge of the system.

M.Sc. on Music Creation and Sound Technology by the Universitat Pompeu Fabra (UPF) in 1996. The master thesis was devoted to the design and implementation of Saxex.

M.Sc. on Computer Science by the Facultat d'Informàtica de Barcelona (FIB) of the Technical University of Catalunya (UPC) in 1992. The master thesis was devoted to the design and implementation of a compiler for the MILORD II language. This language is focused to the incremental construction of knowledge bases by means of its modular, refinenent and generic description capabilities.

Degree on Computer Science by the Facultat d'Informàtica de Barcelona (FIB) of the Technical University of Catalunya (UPC) in 1991.

Born in 1968 in Callús (El Bages, Catalunya).