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Artificial Intelligence

As of today, the doctoral programme in Artificial Intelligence is the only doctoral programme in Catalonia focusing exclusively on artificial intelligence.

• The development of computing and its pervasiveness in all areas of society represent fundamental elements for understanding the socioeconomic progress of the second half of the 20th century. Particularly in recent years, artificial intelligence, due to its multidisciplinary nature, in addition to driving scientific and technological advancement in all fields of science, engineering and many other disciplines, has enabled the efficient and effective deciphering of scientific and social data, which has been critical to shaping our understanding of the world around us, living beings, mankind and society in general. Artificial intelligence is now present in nearly all domains of advanced society. Specifically, the financial, industrial, service, public administration, health care, communications, education and research and innovation sectors cannot be conceived without artificial intelligence playing a critical role in the systems that control them.

• The programme’s sphere of influence is Catalonia. As such it looks to attract Catalan students, though the Department also admits students from other parts of Spain and foreign countries. In Catalonia, and in particular, the metropolitan area surrounding Barcelona, industry and services have developed extensively. The financial, insurance, SME, consulting, education and research sectors here are key to the development of the country as a whole. And, as has already been mentioned, artificial intelligence is necessary in all of these fields. Consequently, educating and training well qualified AI researchers has undoubtedly become a strategic factor for growth.

• The doctoral programme in Artificial Intelligence was the first of its kind in Catalonia (1985), and for many years, it was the only one to exist. Since then, artificial intelligence has seen exponential growth and has been the starting point for many lines of research and products that have made their way to the general public, whether in American, Japan or Europe, where a significant number of Framework Programmes have been dedicated to financing projects that have artificial intelligence as a major element. In Catalonia in particular, the UPC’s doctoral programme in Artificial Intelligence has been vital to the creation of a thriving and growing scientific community. Some of the most important public and private research centres in Europe were founded by research graduates from our programme. Various spin-offs (e.g., ISOCO, 3SCALE, Intelligent Pharma and Sisltech) have been created as the result of one or more doctoral theses. Additionally, the Catalan Association for Artificial Intelligence (ACIA) is one of the most important in Europe.

• The doctoral programme in Artificial Intelligence stands out in Europe thanks to the research quality and output produced by its members, who participate in research projects financed with funds from the EU, Spain or other Spanish organisations and companies. Special mention should be given to the coordination of and participation in research projects involved with the Fifth, Sixth and Seventh Framework Programmes (Share-it, Laboranova, Contract, Agencities.RTD, Alive, Superhub, etc.). At the UPC there are three established groups that have been acclaimed by the Government of Catalonia and another by the university itself. These groups are directly related to the programme, ensuring that it remains dynamic and maintains the scientific standards needed to keep it in such high standing. Additionally, as has been previously mentioned, these groups are very active when it comes to obtaining financing through EU calls, which ensures they have continuous contact with national and European businesses and a high level of internationalisation. Furthermore, other groups at the UPC regularly send students to study in the programme. The same is true with students from other universities, such as the URV and the CSIC’s Artificial Intelligence Research Institute.

• The UPC’s doctoral programme in Artificial Intelligence was given the Quality Award in 2003 (MCD2003-00129), which was renewed in the following years: 2004, 2005, 2006, 2007, 2008 and 2009. Among other recent accolades, it is worth noting that some of the programme’s theses have received awards:

• Two recent doctoral theses presented in the programme were given the Artificial Intelligence Dissertation Award (in 2010 and 2003). This is the only programme in all of Spain that has been given such distinctions. In Europe, there are two other examples: the doctoral programmes in artificial intelligence at the École Polytechnique Fédérale de Lausanne (EPFL) and the J. Stefan Institute in Ljubljana.

• Furthermore, some of the programme’s distinguished former students include five ECCAI Fellows. Ours is one of the programmes that has produced the most Fellows in Europe. They are: Prof. Carlos Sierra (IIIA-CSIC), Enric Plaza (1) (IIIA-CSIC), Vicenç Torra (IIIA-CSIC), Pedro Messeguer (IIIA-CSIC) and Lluís Godó (IIIA-CSIC)

• Another of the programme’s theses was given the Best Thesis Award 2009 by the European Association for Machine Translation.

• Another was given the Joan Lluís Vives Prize 2003, the Barcelona City Research Prize 2003 and the Extraordinary Doctorate Prize by the UPC for the 2003-2004 academic year.

• Another was given the Chihuahua Research Prize 2002, by the state of Chihuahua, Mexico.

The doctoral programme in Artificial Intelligence falls into the field of information and communication technology (ICT), as does the research work carried out in the programme, and this represents one of the primary areas of research at the UPC. The education and training provided in the programme is intended to respond to one of the challenges posed by Catalonia’s 2010-2013 Research and Innovation Plan: Excellent and cutting-edge research and technology (see section 8, page 13). It is also intended to respond to the objectives of area 1—production of scientific and technological knowledge and competencies—of the National Scientific Research, Development and Technological Innovation Plan 2008-2011 (PN I+D+I).
From a technical and scientific point of view, some of the programme’s lines of research contribute to tackling other challenges included in Catalonia’s Research and Innovation Plan:
• Efficient flows of people and goods (sustainable mobility) and of information. The programme covers lines dealing with flows of information related to the accessibility and management of information, particularly in the contexts of algorithmics and programming.
• The new service society with consumer “serviproducts”. The programme incorporates lines of research related to the study and analysis of the structural and algorithmic aspects of social networks and heterogeneous computing networks (sensors, robots, mobile phones, etc.) that could play a crucial role in the development of new methodologies in this field. It also deals with the development of computer graphic technologies and those related to virtual and augmented reality.
• Healthcare and risk prevention. The programme incorporates lines of research related to biocomputing and medical visualisation.
With regard to the PN I+D+I and in line with the objectives of Strategic Action 4, the programme’s lines of research include the following: Telecommunications and the information society, with potential contributions to the following sub-lines:
1. Computing technologies
b) Advanced multi-modal interfaces.
c) Distributed and embedded systems.
d) Software engineering and information management.
e) Intelligent systems.
f) Free and open-source software.
8. Sector-specific applications, services and contents
a) Businesses and particularly SMEs. E-business, in its broadest sense.
b) Healthcare, social welfare and social inclusion, including broadband e-inclusion.
c) Security, in its broadest sense.
d) Transport, in its broadest sense.
Regarding the European Community’s Seventh Framework Programme, from topic 3, Information and Communication Technologies, of the 2011-2012 Work Programme, the doctoral programme’s lines of research pertain to the planning, design and analysis of some of the developmental components of the challenges posed:
• Challenge 1: Pervasive and trusted network and service infrastructures
- tools and platforms for novel Internet application development
- key technological developments in networking, digital media and service infrastructures.
• Challenge 3: alternative paths to components and systems
- multicore computing systems
- embedded systems
- monitoring and control
- cooperating complex systems
• Challenge 4: technologies for digital content and languages
- online access and use of content and services
- reliability of retrieval and use of digital resources
- scaling up data analysis to keep pace with extremely large data volumes
• Challenge 5: ICT for health, ageing well, inclusion and governance. ICT for disease prediction, early diagnosis, prevention, minimally invasive treatment
Artificial intelligence is undoubtedly at the core of the technological and scientific development of other emblematic concepts and challenges, including “smart cities”, “greener technologies” and “living labs”.


COORDINATOR

Larrosa Bondia, Francisco Javier

CONTACT

Doctoral Unit
ICT North Campus Management and Support Unit
Universitat Politècnica de Catalunya · BarcelonaTech
C. Jordi Girona, 1-3
Building B4 - 003
08034 Barcelona
doctorat.ia@upc.edu
Tel: 93413 78 36

https://artificialintelligence.phd.upc.edu/en/phd

idPD: 1218 - cp: 920

General information

Access profile

There cannot be a specific profile for applicants to a programme in a discipline that is so horizontal, interdisciplinary and diverse as artificial intelligence. Areas of research and application range from biology and medicine to computational linguistics, artificial vision and robotic intelligence, to name a few of the extremes.

However, to provide an identifiable base of basic knowledge, applicants’ prior education and training should preferably have provided skills and abilities in research equivalent to those provided by the master’s degree programme in Artificial Intelligence, currently offered by the UPC, or to those provided by specialisations in Advanced Computation and Computer Graphics and Virtual Reality in the master’s degree programme in Innovation and Research in Informatics, which stems from the restructuring of master’s-level studies in ICT at the UPC.

The master’s degree programme in Artificial Intelligence also accepts students from a wide range of other scientific disciplines.

Output profile

Doctoral candidates who complete a doctoral degree will have acquired the following competencies, which are needed to carry out quality research (Royal Decree 99/2011, of 28 January, which regulates official doctoral studies):

a) A systematic understanding of the field of study and a mastery of the research skills and methods related to the field.
b) An ability to conceive, design or create, put into practice and adopt a substantial process of research or creation.
c) An ability to contribute to pushing back the frontiers of knowledge through original research.
d) A capacity for critical analysis and an ability to assess and summarise new and complex ideas.
e) An ability to communicate with the academic and scientific community and with society in general as regards their fields of knowledge in the manner and languages that are typical of the international scientific community to which they belong.
f) An ability to foster scientific, technological, social, artistic and cultural progress in academic and professional contexts within a knowledge-based society.

The award of a doctoral degree must equip the graduate for work in a variety of settings, especially those requiring creativity and innovation. Doctoral graduates must have at least acquired the personal skills needed to:

a) Develop in contexts in which there is little specific information.
b) Find the key questions that must be answered to solve a complex problem.
c) Design, create, develop and undertake original, innovative projects in their field.
d) Work as part of a team and independently in an international or multidisciplinary context.
e) Integrate knowledge, deal with complexity and make judgements with limited information.
f) Offer criticism on and intellectually defend solutions.

Finally, with respect to competencies, doctoral students must:
a) have acquired advanced knowledge at the frontier of their discipline and demonstrated, in the context of internationally recognised scientific research, a deep, detailed and well-grounded understanding of theoretical and practical issues and scientific methodology in one or more research fields;
b) have made an original and significant contribution to scientific research in their field of expertise that has been recognised as such by the international scientific community;
c) have demonstrated that they are capable of designing a research project that serves as a framework for carrying out a critical analysis and assessment of imprecise situations, in which they are able to apply their contributions, expertise and working method to synthesise new and complex ideas that yield a deeper knowledge of the research context in which they work;
d) have developed sufficient autonomy to set up, manage and lead innovative research teams and projects and scientific collaborations (both national and international) within their subject area, in multidisciplinary contexts and, where appropriate, with a substantial element of knowledge transfer;
e) have demonstrated that they are able to carry out their research activity in a socially responsible manner and with scientific integrity;
f) have demonstrated, within their specific scientific context, that they are able to make cultural, social or technological advances and promote innovation in all areas within a knowledge-based society;
g) have demonstrated that they are able to participate in scientific discussions at the international level in their field of expertise and disseminate the results of their research activity to audiences of all kinds.

Number of places

10

Duration of studies and dedication regime

Duration
The maximum period of study for full-time doctoral studies is three years, counted from the date of admission to the programme to the date of submission of the doctoral thesis. The academic committee of the doctoral programme may authorise a doctoral candidate to pursue doctoral studies on a part-time basis. In this case, the maximum period of study is five years, counting from the date of admission to the programme to the date of submission of the doctoral thesis. For calculating these periods, the date of admission is considered to be the date of the first enrolment for tutorials, and the date of submission the moment in which the Doctoral School officially deposits the doctoral thesis.

For full-time doctoral candidates, the minimum period of study is two years, counted from the date of an applicant's admission to the programme until the date on which the doctoral thesis is deposited; for part-time doctoral candidates it is four years. When there are justified grounds for doing so, and the thesis supervisor and academic tutor have given their authorisation, doctoral candidates may request that the academic committee of their doctoral programme exempt them from the minimum period of study requirement.

The calculation of periods of study will not include periods of absence due to illness, pregnancy or any other reason provided for in the regulations in force. Students who find themselves in any of these circumstances must notify the academic committee of the doctoral programme, which, where appropriate, must inform the Doctoral School. Doctoral candidates may also temporarily withdraw from the programme for up to one year, and this period may be extended for an additional year. Doctoral candidates who wish to interrupt their studies must submit a justified request to the academic committee of the doctoral programme, which will decide whether or not to approve the request. Each programme will establish conditions for readmission to doctoral studies.

Extension
If full-time doctoral candidates have not applied to deposit their thesis by the end of the three-year period of study, the academic committee of the programme may authorise an extension of up to one year. In exceptional circumstances, a further one-year extension may be granted, subject to the conditions established by the corresponding doctoral programme. In the case of part-time doctoral candidates, an extension of two years may be authorised. In both cases, in exceptional circumstances a further one-year extension may be granted by the Doctoral School's Standing Committee, upon the submission of a reasoned application by the academic committee of the doctoral programme.

Dismissal from the doctoral programme
A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

  • The doctoral candidate submitting a justified application to withdraw from the programme.
  • The maximum period of study and of extensions thereof ending.
  • The doctoral candidate not having enrolled every academic year (unless he or she has been authorised to temporarily withdraw).
  • The doctoral candidate failing two consecutive assessments.
  • The doctoral candidate having disciplinary proceedings filed against him or her that rule that he or she must be dismissed from the UPC.

Dismissal from the programme implies that doctoral candidates cannot continue studying at the UPC and the closing of their academic record. This notwithstanding, they may apply to the academic committee of the programme for readmission and the committee must reevaluate them in accordance with the criteria established in the regulations.

Organization

COORDINATOR:
ACADEMIC COMMISSION OF THE PROGRAM:
STRUCTURAL UNITS:
  • Department of Computer Science (PROMOTORA)
Specific URL of the doctoral program:
https://artificialintelligence.phd.upc.edu/en/phd

CONTACT:
Doctoral Unit
ICT North Campus Management and Support Unit
Universitat Politècnica de Catalunya · BarcelonaTech
C. Jordi Girona, 1-3
Building B4 - 003
08034 Barcelona
doctorat.ia@upc.edu
Tel: 93413 78 36

Agreements with other institutions


Access, admission and registration

Access profile

There cannot be a specific profile for applicants to a programme in a discipline that is so horizontal, interdisciplinary and diverse as artificial intelligence. Areas of research and application range from biology and medicine to computational linguistics, artificial vision and robotic intelligence, to name a few of the extremes.

However, to provide an identifiable base of basic knowledge, applicants’ prior education and training should preferably have provided skills and abilities in research equivalent to those provided by the master’s degree programme in Artificial Intelligence, currently offered by the UPC, or to those provided by specialisations in Advanced Computation and Computer Graphics and Virtual Reality in the master’s degree programme in Innovation and Research in Informatics, which stems from the restructuring of master’s-level studies in ICT at the UPC.

The master’s degree programme in Artificial Intelligence also accepts students from a wide range of other scientific disciplines.

Access requirements

Applicants must hold a Spanish bachelor’s degree or equivalent and a Spanish master’s degree or equivalent, provided they have completed a minimum of 300 ECTS credits on the two degrees (Royal Decree 43/2015, of 2 February)

In addition, the following may apply:

  • Holders of an official degree awarded by a university in Spain or any other country in the European Higher Education Area, pursuant to the provisions of Article 16 of Royal Decree 1393/2007, of 29 October, which establishes official university course regulations, who have completed a minimum of 300 ECTS credits on official university degrees, of which at least 60 must be at the master's degree level.
  • Holders of an official Spanish bachelor’s degree comprising at least 300 credits, as provided for by EU regulations. Holder of degrees of this kind must complete bridging courses unless the curriculum of the bachelor’s degree in question included research training credits equivalent in value to those which would be earned on a master's degree.
  • Holders of an official university qualification who, having passed the entrance examination for specialised medical training, have completed at least two years of a training course leading to an official degree in a health-sciences specialisation.
  • Holders of a degree issued under a foreign education system. In these cases, homologation is not required, but the UPC must verify that the degree certifies a level of training equivalent to an official Spanish master's degree and qualifies the holder for admission to doctoral studies in the country where it was issued. Admission on this basis does not imply homologation of the foreign degree or its recognition for any purpose other than admission to doctoral studies.
  • Holders of a Spanish doctoral qualification issued under previous university regulations.
  • Note 1: Doctoral studies entrance regulations for holders of an undergraduate degree awarded before the introduction of the EHEA (CG 47/02 2014)

    Note 2: Governing Council Decision 64/2014, which approves the procedure and criteria for assessing the fulfilment of academic admission requirements for doctoral studies by holders of non-homologated foreign degrees (CG 25/03 2014)

Admission criteria and merits assessment

Aspiring doctors in Artificial Intelligence should have academic (master’s) and professional backgrounds that show that they have the academic and intellectual capacities and the consistency needed to ensure that they can successfully complete their studies in a timely fashion.

The programme will assess candidates on the following criteria:

 • Academic transcripts for all university degree programmes taken.
 • Publications (if applicable).
 • Research experience (if applicable).
 • CV.
 • Appropriateness of research interests with the programmes lines of research and the applicant’s background.
 • Other merits.

All of those who are admitted to the doctoral programme will be expected to be able to understand technical texts written in English and easily follow courses and conferences in English. Candidates will have to demonstrate that they possess a knowledge of the English language equal to a B1 level as per the Common European Framework of Reference for Languages, both spoken and written, in the timeframes and manners determined by the Academic Committee.

Weighting of criteria:
The Academic Committee of the doctoral programme will be in charge of the process of selecting and admitting candidates. This selection process will be based on a scale that will give priority to the following aspects:

- applicants’ academic transcripts (60%)
- verifiable knowledge of the English language (20%).
- previous experience (20%).

Training complements

The academic committee for the programme may require that doctoral students pass specific bridging courses. In this case, the Committee will monitor the bridging courses and set up appropriate criteria to limit their length.

The courses could involve training in research or transversal education, but in no case will candidates be required to enrol in 60 or more ECTS credits.

Depending on the activities completed by the candidates, the programme’s Academic Committee may propose measures, in addition to those established by current regulations, that would disassociate candidates who do not meet the established requisites.

If necessary, the bridging courses required will be determined by the academic tutors following the recommendations given to each student during the admission process. Recommended courses will be those offered through the joint master’s degree programme in Artificial Intelligence.

Core subjects:

Based on their previous studies, candidates with non-scientific backgrounds will have to pass these courses, in addition to one subject from the following blocks, depending on their chosen line of research.

• Computational Intelligence (CI)
• Computational Vision (CV)
• Intelligent Data Analysis Applications in Business
• Introduction to MultiAgent Systems (IMAS)
• Introduction to Machine Learning (IML)
• Introduction to Natural Language Processing (INLP)
• Planning and Approximate Reasoning (PAR)

Subjects on more specific topics:

For candidates with scientific backgrounds, 1 or 2 blocks of subjects, depending on their chosen line of research.

MultiAgent Systems:
• Multi-Agent Systems Design (MASD)
• Normative and Dynamic Virtual Worlds (NDVW)
• Self-Organising Agent Systems (SOAS)

Human-Computer Interaction:
• Advanced Natural Language Processing (ANLP)
• Cognitive Interaction with Robots (CIR)
• Human-Computer Interaction (HCI)

Advanced Computational Intelligence:
• Advanced Topics in Computational Intelligence (ATCI)
• Complex Networks (CN)
• Intelligent Data Analysis and Data Mining (IDADM)

Knowledge Engineering and Machine Learning:
• Advanced Machine Learning Techniques (AMLT)
• Intelligent Decision Support Systems (IDSS)
• Knowledge Representation and Engineering (KRE)
• Multi-Criteria Decision Support Systems (MCDSS)

Modelling, Reasoning and Problem Solving:
• Constraint Processing and Programming (CPP)
• Logics for Artificial Intelligence (LAI)
• Minds, Brains and Machines (MBM)
• Probabilistic Graphical Models (PGM)

Vision, Perception and Robotics:
• Advanced Artificial Vision (AAV)
• Cooperative Robotics (CR)
• Object Recognition (OR)

Enrolment period for new doctoral students

Students enrolling in the doctoral programme for the first time must do so by the deadline specified in the admission decision.
Unless otherwise expressly indicated, enrolments corresponding to admission decisions issued from the second half of April on must be completed within the ordinary enrolment period for the current academic year.

More information at the registration section for new doctoral students

Enrolment period

Ordinary period for second and successive enrolments: first half of October.

More information at the general registration section

Monitoring and evaluation of the doctoral student

Procedure for the preparation and defense of the research plan

Doctoral candidates must submit a research plan, which will be included in their doctoral student activity report, before the end of the first year. The plan may be improved over the course of the doctoral degree. It must be endorsed by the tutor and the supervisor, and it must include the method that is to be followed and the aims of the research.

At least one of these annual assessments will include a public presentation and defence of the research plan and work done before a committee composed of three doctoral degree holders, which will be conducted in the manner determined by each academic committee. The examination committee awards a Pass or Fail mark. A Pass mark is a prerequisite for continuing on the doctoral programme. Doctoral candidates awarded a Fail mark must submit a new research plan for assessment by the academic committee of the doctoral programme within six months.

The committee assesses the research plan every year, in addition to all of the other activities in the doctoral student activity report. Doctoral candidates who are awarded two consecutive Fail marks for the research plan will be obliged to definitely withdraw from the programme.

If they change the subject of their thesis, they must submit a new research plan.

Formation activities

1. Tutorials (meetings with the supervisor), approximately 288 hours (the exact number and frequency will be defined by the supervisor), mandatory.

2. Artificial Intelligence Seminar, approximately 30 hours (depending on participants’ availability), optional.

3. Theoretical-Scientific Seminar, approximately 30 hours (depending on participants’ availability), optional.

4. Intensive courses, approximately 30 hours (depending on professors’ availability), optional.

5. International scientific meetings (conferences, workshops, schools, etc.), approximately 24 hours, optional.

Procedure for assignment of tutor and thesis director

The academic committee of the doctoral programme assigns a thesis supervisor to each doctoral candidate when they are admitted or enrol for the first time, taking account of the thesis supervision commitment referred to in the admission decision.

The thesis supervisor will ensure that training activities carried out by the doctoral candidate are coherent and suitable, and that the topic of the candidate’s doctoral thesis will have an impact and make a novel contribution to knowledge in the relevant field. The thesis supervisor will also guide the doctoral candidate in planning the thesis and, if necessary, tailoring it to any other projects or activities undertaken. The thesis supervisor will generally be a UPC professor or researcher who holds a doctoral degree and has documented research experience. This includes PhD-holding staff at associated schools (as determined by the Governing Council) and UPC-affiliated research institutes (in accordance with corresponding collaboration and affiliation agreements). When thesis supervisors are UPC staff members, they also act as the doctoral candidate’s tutor.

PhD holders who do not meet these criteria (as a result of their contractual relationship or the nature of the institution to which they are attached) must be approved by the UPC Doctoral School's Standing Committee in order to participate in a doctoral programme as researchers with documented research experience.

The academic committee of the doctoral programme may approve the appointment of a PhD-holding expert who is not a UPC staff member as a candidate’s thesis supervisor. In such cases, the prior authorisation of the UPC Doctoral School's Standing Committee is required. A UPC staff member who holds a doctoral degree and has documented research experience must also be proposed to act as a co-supervisor, or as the doctoral candidate’s tutor if one has not been assigned.

A thesis supervisor may step down from this role if there are justified reasons (recognised as valid by the committee) for doing so. If this occurs, the academic committee of the doctoral programme will assign the doctoral candidate a new thesis supervisor.

Provided there are justified reasons for doing so, and after hearing any relevant input from the doctoral candidate, the academic committee of the doctoral programme may assign a new thesis supervisor at any time during the period of doctoral study.

If there are academic reasons for doing so (an interdisciplinary topic, joint or international programmes, etc.) and the academic committee of the programme gives its approval, an additional thesis supervisor may be assigned. Supervisors and co-supervisors have the same responsibilities and academic recognition.

The maximum number of supervisors of a doctoral thesis is two: a supervisor and a co-supervisor.

For theses carried out under a cotutelle agreement or as part of an Industrial Doctorate, if necessary and if the agreement foresees it this maximum number of supervisors may not apply. This notwithstanding, the maximum number of supervisors belonging to the UPC is two.

More information at the PhD theses section

Permanence

The academic committee of the programme may authorise an extension of up to one year for full-time doctoral candidates who have not applied to deposit their thesis by the end of the three-year period of study, in the terms outlined in the Academic Regulations for Doctoral Studies of the Universitat Politècnica de Catalunya. In the case of part-time candidates, an extension of two years may be authorised. In both cases, in exceptional circumstances a further one-year extension may be granted by the Doctoral School's Standing Committee, upon the submission of a reasoned application by the academic committee of the doctoral programme.

A doctoral candidate may be dismissed from a doctoral programme for the following reasons:

  • The doctoral candidate submitting a justified application to withdraw from the programme.
  • The maximum period of study and of extensions thereof ending.
  • The doctoral candidate not having enrolled every academic year (unless he or she has been authorised to temporarily withdraw).
  • The doctoral candidate failing two consecutive assessments.
  • The doctoral candidate having disciplinary proceedings filed against him or her that rule that he or she must be dismissed from the UPC.

Dismissal from the programme implies that doctoral candidates cannot continue studying at the UPC and the closing of their academic record. This notwithstanding, they may apply to the academic committee of the programme for readmission and the committee must reevaluate them in accordance with the criteria established in the regulations.

International Mention

The doctoral degree certificate may include International Doctorate mention. In this case, the doctoral candidate must meet the following requirements:

a) During the period of study leading to the award of the doctoral degree, the doctoral candidate must have spent at least three months at a respected higher education institution or research centre outside Spain to complete courses or do research work. The stays and activities carried out must be endorsed by the thesis supervisor and authorised by the academic committee of the programme. The candidate must provide a certifying document issued by the person responsible for the research group of the body or bodies where the stay or activity was completed. This information will be added to the doctoral student’s activity report.
b) Part of the thesis (at least the summary and conclusions) must be written and presented in one of the languages commonly used for science communication in the relevant field of knowledge, which must not be an official language of Spain. This rule does not apply to stays and reports in Spanish or to experts from Spanish-speaking countries.
c) At least two PhD-holding experts belonging to a higher education institution or research centre outside Spain must have issued officially certified reports on the thesis.
d) The thesis examination committee must have included at least one PhD-holding expert from a higher education or research institution outside Spain who was not responsible for the candidate’s stay abroad (point a) above).
e) The thesis defence must have taken place on UPC premises or, in the case of joint programmes, at the location specified in the collaboration agreement.

Learning resources

Space for grant holders, study rooms, computing equipment and programmes provided by the Computer Science Department, additional resources provided by research groups participating in the programme.

The Academic Committee of the doctoral programme will encourage candidates to participate in mobility programmes on the regional, country, and European levels and in research groups working on projects at the international level, whether via integrated actions or on European projects. Such participation has been and will continue to be one of the major points of internationalisation in the programme.

Doctoral Theses

List of authorized thesis for defense

No hi ha registres per mostrar.

Last update: 26/11/2020 06:11:22.

List of lodged theses

No hi ha registres per mostrar.

Last update: 26/11/2020 06:10:03.

List of defended theses by year

  • MANERO FONT, JAUME: Deep Learning architectures applied to wind time series multi-step forecasting
    Author: MANERO FONT, JAUME
    Thesis link: http://hdl.handle.net/10803/669283
    Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
    Department: Department of Computer Science (CS)
    Mode: Normal
    Reading date: 14/07/2020
    Thesis director: BÉJAR ALONSO, JAVIER | CORTÉS GARCÍA, CLAUDIO ULISES

    Committee:
         PRESIDENT: LOPEZ DE MANTARAS, RAMON
         SECRETARI: MARTÍN MUÑOZ, MARIO
         VOCAL: CECCARONI, LUIGI
    Thesis abstract: Forecasting is a critical task for the integration of wind-generated energy into electricity grids. Numerical weather models applied to wind prediction, work with grid sizes too large to reproduce all the local features that influence wind, thus making the use of time series with past observations a necessary tool for wind forecasting. This research work is about the application of deep neural networks to multi-step forecasting using multivariate time series as an input, to forecast wind speed at 12 hours ahead.Wind time series are sequences of meteorological observations like wind speed, temperature, pressure, humidity, and direction. Wind series have two statistically relevant properties; non-linearity and non-stationarity, which makes the modellingwith traditional statistical tools very inaccurate.In this thesis we design, test and validate novel deep learning models for the wind energy prediction task, applying new deep architectures to the largest open wind data repository available from the National Renewable Laboratory of the US (NREL) with 126,692 wind sites evenly distributed on the US geography. The heterogeneity of the series, obtained from several data origins, allows us to obtain conclusions about the level of fitness of each model to time series that range from highly stationary locations to variable sites from complex areas.We propose Multi-Layer, Convolutional and recurrent Networks as basic building blocks, and then combined into heterogeneous architectures with different variants, trained with optimisation strategies like drop and skip connections, earlystopping, adaptive learning rates, filters and kernels of different sizes, between others. The architectures are optimised by the use of structured hyper-parameter setting strategies to obtain the best performing model across the whole dataset.The learning capabilities of the architectures applied to the various sites find relationships between the site characteristics (terrain complexity, wind variability, geographical location) and the model accuracy, establishing novel measures of site predictability relating the fit of the models with indexes from time series spectral or stationary analysis. The designed methods offer new, and superior, alternatives to traditional methods.

  • SABIR, AHMED: Enhancing scene text recognition with visual context information.
    Author: SABIR, AHMED
    Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
    Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
    Department: Department of Computer Science (CS)
    Mode: Normal
    Reading date: 10/11/2020
    Thesis director: PADRO CIRERA, LLUIS | MORENO-NOGUER, FRANCESC

    Committee:
         PRESIDENT: AGIRRE BENGOA, ENEKO
         SECRETARI: TURMO BORRÁS, JORGE
         VOCAL: KARATZAS, DIMOSTHENIS
    Thesis abstract: This thesis addresses the problem of improving text spotting systems, whichaim to detect and recognize text in unrestricted images (e.g. a street sign, an advertisement, a bus destination, etc.). The goal is to improve the performance of off-the-shelf vision systems by exploiting the semantic information derivedfrom the image itself. The rationale is that knowing the content of the image or the visual context can help to decide which words are the correct andidatewords.For example, the fact that an image shows a coffee shop makes it more likely that a word on a signboard reads as Dunkin and not unkind.We address this problem by drawing on successful developments in natural language processing and machine learning, in particular, learning to re-rankand neural networks, to present post-process frameworks that improve state-of-the-art text spotting systems without the need for costly data-driven re-training or tuning procedures.Discovering the degree of semantic relatedness of candidate words and their image context is a task related to assessing the semantic similarity betweenwords or text fragments. However, semantic relatedness is more general than similarity (e.g. car, road, and traffic light are related but not similar) and requires certain adaptations. To meet the requirements of these broader perspectives ofsemantic similarity, we develop two approaches to learn the semantic related-ness of the spotted word and its environmental context: word-to-word (object)or word-to-sentence (caption). In the word-to-word approach, word embed-ding based re-rankers are developed. The re-ranker takes the words from the text spotting baseline and re-ranks them based on the visual context from theobject classifier. For the second, an end-to-end neural approach is designed to drive image description (caption) at the sentence-level as well as the word-level (objects) and re-rank them based not only on the visual context but alsoon the co-occurrence between them.As an additional contribution, to meet the requirements of data-driven ap-proaches such as neural networks, we propose a visual context dataset for this task, in which the publicly available COCO-text dataset [Veit et al. 2016] hasbeen extended with information about the scene (including the objects and places appearing in the image) to enable researchers to include the semantic relations between texts and scene in their Text Spotting systems, and to offer a common evaluation baseline for such approaches.

Last update: 26/11/2020 06:08:48.

Theses related publications

AUTHOR:NGUYEN, JENNIFER THANH VAN
Title:Knowledge aggregation in people recommender systems:matching skills to tasks
Reading date:08/11/2019
Director:ANGULO BAHON, CECILIO
Co-director:AGELL JANÉ, NÚRIA
Mention:No
RELATED PUBLICATIONS
Nguyen, J. (2019). Knowledge aggregation in people recommender systems:matching skills to tasks.

Nguyen, J.; Armisen, A.; Sánchez, G.; Casabayó, M.; Agell, N. (2020). An OWA-based hierarchical clustering approach to understanding users’ lifestyles. (JCR Impact Factor-2018: 0.0; Quartil: )

Nguyen, J.; Montserrat, J.; Agell, N.; Sanchez, M.; Ruiz, F. (2020). Fusing hotel ratings and reviews with hesitant terms and consensus measures. (JCR Impact Factor-2018: 4.664; Quartil: Q1)

AUTHOR:GKATZIOURA, ANNA
Title:A Hybrid Approach for Item Collection Recommendations: An Application to Automatic Playlist Continuation
Reading date:23/11/2018
Director:SANCHEZ MARRE, MIQUEL
Mention:Mention de Doctor Internacional
RELATED PUBLICATIONS
Gatzioura, A. (2018). A Hybrid Approach for Item Collection Recommendations: An Application to Automatic Playlist Continuation.

AUTHOR:CORTÉS MARTÍNEZ, ATIA
Title:Human - Smart Rollator Interaction for Gait Analysis and Fall Prevention Using Learning Methods and the i-Walker
Reading date:20/07/2018
Director:BÉJAR ALONSO, JAVIER
Director:MARTÍNEZ VELASCO, ANTONIO-BENITO
Mention:Mention de Doctor Internacional
RELATED PUBLICATIONS
Cortes, A. (2018). Human - Smart Rollator Interaction for Gait Analysis and Fall Prevention Using Learning Methods and the i-Walker.

Cortes, A.; Martinez, A.; Bejar, J. (2019). Spatio-temporal gait analysis based on human-smart rollator interaction. (JCR Impact Factor-2017: 0.17; Quartil: Q3)

Plana, M.; López, M.; Cabré, L.; Lecuona, I.; Villalobos, M.; Mariño, E.; Cortes, A.; Cristea, L.; Biel, M.; Portals, M.; Rey, N.; Navarro, M.; Leyton, F.; Casado, M. (2019). Medicamentos y alimentos online: cuestiones éticas en torno al acceso a alimentos y medicamentos a través de Internet.

Cortes, A.; Ojeda, M.; Bejar, J.; Martinez, A. (2018). An approach to gait analysis from human-rollator interaction: the i-Walker.

Research projects

START DATEEND DATEACTIVITYFINANCING ENTITY
15/07/202014/02/2021Uso de algoritmos de aprendizaje por refuerzo en problemas de planificaciónITHINKUPC, S.L.
01/06/202031/05/2023Colaboración robot-humano para el transporte y entrega de mercancíasAGENCIA ESTATAL DE INVESTIGACION
01/06/202031/05/2023Aprendizaje Automático para la Modelización de la Dinámica Molecular de las Proteinas GPCRAGENCIA ESTATAL DE INVESTIGACION
01/06/202031/05/2023Análisis de texto médico para la assistencia a la predicción de diagnosisAGENCIA ESTATAL DE INVESTIGACION
27/12/201927/06/2021Integrated care for frail older adults in the communityINSTITUT DE CULTURA DE BARCELONA
01/11/201901/04/2020Sistemas recomendadores para el desarrollo de una solución de asignación de evaluadores a proyectos mediante técnicas de Inteligencia Artificial. Proyecto HR2020 de FBLCITHINKUPC, S.L.
01/09/201928/02/2022Artificial Intelligence skills for ICT professionalsCommission of European Communities
01/09/201931/08/2022GAVIUS: from reactive to proactive public administrationsCommission of European Communities
04/04/201931/07/2020Multiparametric MR approaches for non-invasive Gliobastoma therapy response follow-upCommission of European Communities
01/04/201931/03/2022Future human-machine (AI) Interactlon fon in-car/mobility exoerienceAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/03/201928/02/2020Adquisición de datos para optimizar la oferta de servicios, de promoción de la vida sana, entre los habitantes de zonas desfavorables de GuayaquilCentre de Cooperació per al Desenvolupament , UPC
01/01/201931/12/2021A European AI On Demand Platform and EcosystemCommission of European Communities
01/01/201930/06/2019SEAT-SmarT11: Proyecto de optimización de recursos para ajustes de calidadCàtedra SEAT - UPC
01/01/201931/12/2021Razonamiento Formal para Tecnologías Facilitadoras y EmergentesAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/12/2021Evolving towards DIgital Twins in HealthcareAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/12/2021001-P-001643_Agrupació emergent Looming FactoryGENCAT - DEPT. D'EMPRESA I OCUPACIO
01/01/201931/12/2021001-P-001722_ Agrupació emergent Looming FactoryGENCAT - DEPT. D'EMPRESA I OCUPACIO
01/12/201830/06/2019Servicio de soporte a la convocatoriaHR18 d ela Fundación Bancaria La Caixa (asignación de evaluadores a proyectos mediante técnicas de Inteligencia Artificial y cálculo de notas)ITHINKUPC, S.L.
15/10/201820/12/2020Agreement SiemensSIEMENS SA
21/09/201831/10/2018Patrocini 21er Congrés Internacional de l'Associació Catalana d'Intel·ligència ArtificialAIS APLICACIONES DE INTELIGENCIA AR
18/05/201830/06/2019Análisis textual de los documentos de planificación hidrológica de las cuencas hidrográficas del espacio SUDOE en el marco del proyecto AGUAMOD SOE1/P5/F0026 financiado por el programa de cooperaciónUNIVERSIDAD DEL PAIS VASCO
30/04/201828/06/2019EU-LAC cooperation on Digital Single Market in EuropeSA IBF INTERNATIONAL CONSULTING
01/04/201821/12/2018Análisis de las políticas de adaptación al cambio climático en escenarios de sequía a raíz de la Frame Water Directive en las cuencas SUDOEUniversitat del País Basc
01/03/201830/06/2018Desarrollo de una solución de asignación de evaluadores a proyectos mediante inteligencia artificialITHINKUPC, S.L.
01/02/201831/01/2022European Robotics League plus Smart Cities Robot CompetitionsCommission of European Communities
01/01/201831/12/2020Gestión y Análisis de Datos ComplejosAGENCIA ESTATAL DE INVESTIGACION
01/01/201831/12/2019Barcelona Robotic Urban LabAGENCIA ESTATAL DE INVESTIGACION
01/12/201730/11/2021The European Robotics Research Infrastructure NetworkCommission of European Communities
14/11/201731/12/2018FREELING LIBRARY 4.0LANGLITER INC
01/09/201730/09/2020My Travel CompanionCommission of European Communities
31/07/201731/07/2017Computer implemented method for dissimilarity computation between two yarns to be used for setting of a textile machine in a textile process, and computer program product
31/07/201731/07/2017GESCONDA
03/07/201702/01/2021Automatització de la construcció de sistemes intel·ligents de supervisió i control d'estacions depuradores d'aigües residuals (EDARs) mitjançant ús de fluxes de treball i entorns de programació visualAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
03/05/201703/05/2037Llicència Software FreeLing 4.0VERBIO TECHNOLOGIES S.L.
01/04/201730/06/2017Sistema de gestión inteligente de espacios de campus universitariosSIGMA GESTION U AIE
01/01/201731/12/2019Semantic graph extraction from textual health historiesFondos FEDER; MINECO. Secretaria de Estado de Investigación, Desarrollo e Innovación.
30/12/201629/12/2020Inteligencia computacional para el descubrimiento de conocimiento a partir de G protein-coupled receptorsMIN DE ECONOMIA Y COMPETITIVIDAD
30/12/201629/03/2020Colaboración robots-humanos para el transporte de productos en zonas urbanasMIN DE ECONOMIA Y COMPETITIVIDAD
30/12/201629/12/2019Extracción de grafos semánticos a partir de historiales clínicos textualesMIN DE ECONOMIA Y COMPETITIVIDAD
15/10/201615/04/2020La diabetis com accelerador de deteriorament cognitiu i malaltia d'alzheimer: abordatge i adherènciaACC10
15/09/201614/09/2019eHealth EurocampusCommission of European Communities
01/06/201630/11/2016L’H Smart City 2016 (LHSC16)Ajuntament de L'Hospitalet de Llobregat
01/03/201629/02/2020and social engagementCommission of European Communities
01/02/201631/07/2016Análisis de bases de datos y su relación con aspectos físicos y tácticos del deporteFUTBOL CLUB BARCELONA ( FCB)
01/01/201630/04/2019Self-management interventions and mutual assistance community services, helping patients with dementia and caregivers connect with others for evaluation, support and inspiration to improve the care exCommission of European Communities
01/01/201631/12/2020Soluciones Efectivas basadas en la LógicaMIN DE ECONOMIA Y COMPETITIVIDAD
01/12/201530/11/2017Red Temática Española de "Diversificación avanzada de máquinas de aprendizaje"CICYT. MINISTERIO DE ECONOMÍA, INDUSTRIA Y COMPETITIVIDAD (MINECO). AEI. FEDER
01/11/201501/11/2016Detecció i identificació de fallades en turbines de vent mitjançant la metodologia FIRiTesTit
21/09/201521/09/2015VisualBlock-FIR
21/09/201521/09/2015Visual-FIR
01/09/201531/08/2019Secure Management Platform for Shared Process Resources (SHAREBOX)Commission of European Communities
12/06/201512/06/2025Llicència d'ús de software Freeling 4.0INSTITUTO TECNOLOGICO DE ARAGON
01/06/201531/08/2019Aerial robotic system integrating multiple arms and advanced manipulation capabilities for inspection and maintenanceCommission of European Communities
01/06/201501/04/2016Anàlisi del projecte Sommelier Digital TorresMiguel Torres S.A.
12/05/201511/02/2016Casper, cognitive assistive social pet robots for hospitalized childrenAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/05/201501/11/2018Information technologies for shift to railCommission of European Communities
01/01/201531/12/2017Un recomendador inteligente de dietas personalizadas desde la observación integrada de las características, hábitos y condiciones de las personas (Diet4You)MIN DE ECONOMIA Y COMPETITIVIDAD
01/01/201531/12/2017Aprendizaje Computacional y ComunicaciónMIN DE ECONOMIA Y COMPETITIVIDAD
01/01/201531/12/2017Rehabilitación personalizada y adaptativa en tratamientos post-ictus: el i-WalkerMIN DE ECONOMIA Y COMPETITIVIDAD
01/01/201501/01/2016Automatic detection of relevant activities of companies in newspapersSILK - CAIXABANK: Serveis Informàtics La Caixa
09/12/201021/09/2015ALEA-SOFTUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona
23/03/201021/09/2015Fundació Salut i Envelliment UABUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona

Teaching staff and research groups

Research projects

START DATEEND DATEACTIVITYFINANCING ENTITY
15/07/202014/02/2021Uso de algoritmos de aprendizaje por refuerzo en problemas de planificaciónITHINKUPC, S.L.
01/06/202031/05/2023Colaboración robot-humano para el transporte y entrega de mercancíasAGENCIA ESTATAL DE INVESTIGACION
01/06/202031/05/2023Aprendizaje Automático para la Modelización de la Dinámica Molecular de las Proteinas GPCRAGENCIA ESTATAL DE INVESTIGACION
01/06/202031/05/2023Análisis de texto médico para la assistencia a la predicción de diagnosisAGENCIA ESTATAL DE INVESTIGACION
27/12/201927/06/2021Integrated care for frail older adults in the communityINSTITUT DE CULTURA DE BARCELONA
01/11/201901/04/2020Sistemas recomendadores para el desarrollo de una solución de asignación de evaluadores a proyectos mediante técnicas de Inteligencia Artificial. Proyecto HR2020 de FBLCITHINKUPC, S.L.
01/09/201928/02/2022Artificial Intelligence skills for ICT professionalsCommission of European Communities
01/09/201931/08/2022GAVIUS: from reactive to proactive public administrationsCommission of European Communities
04/04/201931/07/2020Multiparametric MR approaches for non-invasive Gliobastoma therapy response follow-upCommission of European Communities
01/04/201931/03/2022Future human-machine (AI) Interactlon fon in-car/mobility exoerienceAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/03/201928/02/2020Adquisición de datos para optimizar la oferta de servicios, de promoción de la vida sana, entre los habitantes de zonas desfavorables de GuayaquilCentre de Cooperació per al Desenvolupament , UPC
01/01/201931/12/2021A European AI On Demand Platform and EcosystemCommission of European Communities
01/01/201930/06/2019SEAT-SmarT11: Proyecto de optimización de recursos para ajustes de calidadCàtedra SEAT - UPC
01/01/201931/12/2021Razonamiento Formal para Tecnologías Facilitadoras y EmergentesAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/12/2021Evolving towards DIgital Twins in HealthcareAGENCIA ESTATAL DE INVESTIGACION
01/01/201931/12/2021001-P-001643_Agrupació emergent Looming FactoryGENCAT - DEPT. D'EMPRESA I OCUPACIO
01/01/201931/12/2021001-P-001722_ Agrupació emergent Looming FactoryGENCAT - DEPT. D'EMPRESA I OCUPACIO
01/12/201830/06/2019Servicio de soporte a la convocatoriaHR18 d ela Fundación Bancaria La Caixa (asignación de evaluadores a proyectos mediante técnicas de Inteligencia Artificial y cálculo de notas)ITHINKUPC, S.L.
15/10/201820/12/2020Agreement SiemensSIEMENS SA
21/09/201831/10/2018Patrocini 21er Congrés Internacional de l'Associació Catalana d'Intel·ligència ArtificialAIS APLICACIONES DE INTELIGENCIA AR
18/05/201830/06/2019Análisis textual de los documentos de planificación hidrológica de las cuencas hidrográficas del espacio SUDOE en el marco del proyecto AGUAMOD SOE1/P5/F0026 financiado por el programa de cooperaciónUNIVERSIDAD DEL PAIS VASCO
30/04/201828/06/2019EU-LAC cooperation on Digital Single Market in EuropeSA IBF INTERNATIONAL CONSULTING
01/04/201821/12/2018Análisis de las políticas de adaptación al cambio climático en escenarios de sequía a raíz de la Frame Water Directive en las cuencas SUDOEUniversitat del País Basc
01/03/201830/06/2018Desarrollo de una solución de asignación de evaluadores a proyectos mediante inteligencia artificialITHINKUPC, S.L.
01/02/201831/01/2022European Robotics League plus Smart Cities Robot CompetitionsCommission of European Communities
01/01/201831/12/2020Gestión y Análisis de Datos ComplejosAGENCIA ESTATAL DE INVESTIGACION
01/01/201831/12/2019Barcelona Robotic Urban LabAGENCIA ESTATAL DE INVESTIGACION
01/12/201730/11/2021The European Robotics Research Infrastructure NetworkCommission of European Communities
14/11/201731/12/2018FREELING LIBRARY 4.0LANGLITER INC
01/09/201730/09/2020My Travel CompanionCommission of European Communities
31/07/201731/07/2017Computer implemented method for dissimilarity computation between two yarns to be used for setting of a textile machine in a textile process, and computer program product
31/07/201731/07/2017GESCONDA
03/07/201702/01/2021Automatització de la construcció de sistemes intel·ligents de supervisió i control d'estacions depuradores d'aigües residuals (EDARs) mitjançant ús de fluxes de treball i entorns de programació visualAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
03/05/201703/05/2037Llicència Software FreeLing 4.0VERBIO TECHNOLOGIES S.L.
01/04/201730/06/2017Sistema de gestión inteligente de espacios de campus universitariosSIGMA GESTION U AIE
01/01/201731/12/2019Semantic graph extraction from textual health historiesFondos FEDER; MINECO. Secretaria de Estado de Investigación, Desarrollo e Innovación.
30/12/201629/12/2020Inteligencia computacional para el descubrimiento de conocimiento a partir de G protein-coupled receptorsMIN DE ECONOMIA Y COMPETITIVIDAD
30/12/201629/03/2020Colaboración robots-humanos para el transporte de productos en zonas urbanasMIN DE ECONOMIA Y COMPETITIVIDAD
30/12/201629/12/2019Extracción de grafos semánticos a partir de historiales clínicos textualesMIN DE ECONOMIA Y COMPETITIVIDAD
15/10/201615/04/2020La diabetis com accelerador de deteriorament cognitiu i malaltia d'alzheimer: abordatge i adherènciaACC10
15/09/201614/09/2019eHealth EurocampusCommission of European Communities
01/06/201630/11/2016L’H Smart City 2016 (LHSC16)Ajuntament de L'Hospitalet de Llobregat
01/03/201629/02/2020and social engagementCommission of European Communities
01/02/201631/07/2016Análisis de bases de datos y su relación con aspectos físicos y tácticos del deporteFUTBOL CLUB BARCELONA ( FCB)
01/01/201630/04/2019Self-management interventions and mutual assistance community services, helping patients with dementia and caregivers connect with others for evaluation, support and inspiration to improve the care exCommission of European Communities
01/01/201631/12/2020Soluciones Efectivas basadas en la LógicaMIN DE ECONOMIA Y COMPETITIVIDAD
01/12/201530/11/2017Red Temática Española de "Diversificación avanzada de máquinas de aprendizaje"CICYT. MINISTERIO DE ECONOMÍA, INDUSTRIA Y COMPETITIVIDAD (MINECO). AEI. FEDER
01/11/201501/11/2016Detecció i identificació de fallades en turbines de vent mitjançant la metodologia FIRiTesTit
21/09/201521/09/2015VisualBlock-FIR
21/09/201521/09/2015Visual-FIR
01/09/201531/08/2019Secure Management Platform for Shared Process Resources (SHAREBOX)Commission of European Communities
12/06/201512/06/2025Llicència d'ús de software Freeling 4.0INSTITUTO TECNOLOGICO DE ARAGON
01/06/201531/08/2019Aerial robotic system integrating multiple arms and advanced manipulation capabilities for inspection and maintenanceCommission of European Communities
01/06/201501/04/2016Anàlisi del projecte Sommelier Digital TorresMiguel Torres S.A.
12/05/201511/02/2016Casper, cognitive assistive social pet robots for hospitalized childrenAGAUR. Agència de Gestió d'Ajuts Universitaris i de Recerca
01/05/201501/11/2018Information technologies for shift to railCommission of European Communities
01/01/201531/12/2017Un recomendador inteligente de dietas personalizadas desde la observación integrada de las características, hábitos y condiciones de las personas (Diet4You)MIN DE ECONOMIA Y COMPETITIVIDAD
01/01/201531/12/2017Aprendizaje Computacional y ComunicaciónMIN DE ECONOMIA Y COMPETITIVIDAD
01/01/201531/12/2017Rehabilitación personalizada y adaptativa en tratamientos post-ictus: el i-WalkerMIN DE ECONOMIA Y COMPETITIVIDAD
01/01/201501/01/2016Automatic detection of relevant activities of companies in newspapersSILK - CAIXABANK: Serveis Informàtics La Caixa
09/12/201021/09/2015ALEA-SOFTUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona
23/03/201021/09/2015Fundació Salut i Envelliment UABUniversitat Politècnica de Catalunya; Universitat Autònoma de Barcelona

Quality

The Validation, Monitoring, Modification and Accreditation Framework (VSMA Framework) for official degrees ties the quality assurance processes (validation, monitoring, modification and accreditation) carried out over the lifetime of a course to two objectives—the goal of establishing coherent links between these processes, and that of achieving greater efficiency in their management—all with the overarching aim of improving programmes.

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Registry of Universities, Centers and Degrees (RUCT)

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