Project Specific Grants / Reserved topic scholarships 2013 - 2nd call

Computer Science Area - Second call 2/2013

Telecommunications Area - Call 2013

 

Computer Science

Project Specific Grants - Department of Information Engineering and Computer Science

CSTV1 - Empirical Studies of Vulnerabilities and attack surfaces (1)
The goal is to provide a unified framework for statistical analysis of vulnerabilities and exploits and for correlating the various metrics in order to deduce findings and claims on certain pieces of code or to serve as evidence on viability of the vulnerability models. For example an analysis of the correlations between security patching behavior of software vendors and vulnerabilities exploitation by attackers. This would allow to obtain a better understanding of the cost/benefit trade-off automatic patching mechanisms for critical infrastructure protection.
Contact: Fabio.Massacci [at] unitn.it; angeli [at] disi.unitn.it

CSTV2 - Technologies for physical and emotional wellbeing (1)
The candidate is expected to research within a project aiming at the intersection of physical wellbeing, emotional wellbeing, and social interaction. The goal is to design a system and a set of persuasion techniques to motivate all these three aspects, tacking in particular their intersection and exploiting the causal relationship that exists among them. For more information on the research group and topics see www.lifeparticipation.org. Please feel free to contact the principal investigators for any clarification on the research.
Contact: fabio.casati [at] unitn.it

CSTV3 - Fine-grained Opinion Minining for Reputation Analysis(1)
For more information about the research activity conducted by the University of Trento please visit http://limosine-project.eu/about#WP3:_Information_extraction_through_deep_linguistic_analysis
Contact: moschitti [at] disi.unitn.it

CSTV4 -Advanced SMT Techniques for Word-level Formal Verification - (WOLF) (1)
The research activity will aim at investigating and developing novel techniques, methodologies and support tools for Satisfiability Modulo Theories (SMT) for the formal verification of systems. This work will be part of the "Advanced SMT Techniques for Word-level Formal Verification - (WOLF)" project, a three-year research project supported by SRC/GRC (http://www.src.org/compete/s201113/).
Contact: rseba [at] disi.unitn.it

 

Project Specific Grants – Telecom Italia S.p.A.

CSTV5 - Data distillation from Social Big Data stream (1)
We are experiencing an enormous growth of data generation from Social Media (e.g., Twitter) and this trend is going to increase the next years due to the proliferation of the smartphones. Social Big Data analysis has been intensely stressed at global level (e.g., in the last US president election) but may have an extraordinary impact at local level to analyze or predict localized phenomena or events. This is even amplified if the Social Big Data analysis is merged with other Big Data sources, such as telecommunication data. The PhD candidate will focus on one or more issues related to the problem of extracting relevant information from segmented and unstructured Social Media Big Data streams to be used for explaining or predict local events or trends. The PhD candidate will first acquire expertise in different topics of natural language processing and machine learning such as information extraction, supervised and semi-supervised learning. The candidate is then expected to contribute to the advancement of the literature on this problem along many different lines: entity linking, event detection and recognition, and opinion mining.
Academic contact: Claudio Giuliano (giuliano [at] fbk.eu)
Company contact:Silvana Bernaola (silvanamarianela.bernaolabiggio [at] telecomitalia.it)

CSTV6 - A Predictive modeling by multilevel networks of wearable sensors and cell phone data (1)
Developments in sensor technologies have enabled wearable sensors to become effective tools for monitoring and interpreting complex human activities. In particular, fitness and healthcare devices (e.g. sensors for heart variability, accelerometers, skin conductance) have an explosive potential for a digitalization of how environment is perceived and response behaviors activated, individually and socially. We propose to develop a data intensive multilevel network approach based on the integration of wearable sensor data with patterns of mobile life from cell phone data, and to apply this approach to quantitatively evaluate human emotional and behavioral patterns. Novel machine-learning methods for time series and network analysis will be applied on multilevel structure networks representing the different information layers. A prototype framework will be developed as a first scientific framework for studying the real-time forecast of complex incoming (macro) situations in experimental setups. The framework will be validated in an application for modeling urban safety perception of individuals and crowds based on integrated patterns (e.g. heart rate variation, trajectory, anomalous call or data packets).
Academic contact: Cesare Furlanello (furlan [at] fbk.eu)
Company contact: Roberto Larcher (roberto.larcher [at] telecomitalia.it)

NOTE Doctoral students awarded cycle 29 scholarships financed by Telecom are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with Telecom.

 

Extra grants - project-specific grant made available AFTER the publication of this Call

If you are interested in a applying for a project-specific grant made available AFTER the publication of this Call you must fill in the field "Other" of the Application online with the exact code/s and title/s of the project-specific grant

Project Specific Grants - Department of Information Engineering and Computer Science

CSTV7 - Protecting Sotware Infrastructure from Malware Attacks (1)
We will investigate the possibility to detect attacks and anomaly behaviour at an higher level of abstraction. The aim is to investigate new techniques of malware detection or adapt existing techniques to detect anomalous business transactions and or anomalous data, rather than packet, flows.
Contact: crispo [at] disi.unitn.it

Project Specific Grants – Trento Rise

CSTV8 - Smart Campus (1)
The Smart Campus project (www.smartcampuslab.it) aims at providing advanced ICT solutions to catalyze the creativity and enthusiasm of all people involved in a University campus, leading them to become active producers of innovative services designed to support their lives. We are seeking for talented students with experience in interaction design, community design and/or in mobile service applications, and who are interested in pursuing research in these fields within the Smart Campus project.
For more information: http://www.smartcampuslab.it/join-us/
Contact: marco.pistore [at] trentorise.eu; antonella.deangeli [at] disi.unitn.it

Project Specific Grants - FBK

CSTV9 - Security testing of mobile applications (1)
In order to win the race against competitors, mobile applications for tablets and smart-phones are often developed with fast time-to-market approach. For this reason, development effort is often committed to deliver novel and engaging features and less attention is devoted in reviewing the quality of the code. As a result applications are released that still contain defects, faults and potential security problem. Novel approaches need to be elaborated to automate the testing phase of mobile applications, with a particular attention to security aspects, as a fundamental support to ensure both high quality and fast development model. This includes the elaboration of novel techniques for identification of potential security defects, for automatic test case generation and for developing an oracle to assess whether the system under analysis passes all the brand new test cases.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
Contact: ceccato [at] fbk.eu

CSTV10 - Machine Learning for Neuroscience (1)
The PhD research program aims at carrying out research activity on machine learning methodologies for neuroscientific data analysis. The main goal is the design and the deployment of machine learning algorithms for neuroimaging-based neuroscience investigations. The research focuses on three specific tasks: brain decoding, brain mapping and brain connectivity. The challenge is to design effective computational methods for multivariate pattern analysis. The PhD research program will take place at NILab, the Neuroinformatics Laboratory raised as a joint initiative of the Bruno Kessler Foundation and the Center for Mind/Brain Sciences (CIMeC) of the University of Trento.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: http://nilab.fbk.eu/en/open-positions
Contact: avesani [at] fbk.eu

CSTV11 - Semantic Textual Inferences (1)
This PhD grant will explore novel approaches for textual semantic inferences, with specific interest on Textual Entailment. The goal is to advance the state of the art in general entailment algorithms (e.g. graph transformations, tree edit distance), and to define a framework where both knowledge resources (e.g. WordNet, Wikipedia) and specific inference components (e.g. temporal, causal) interact each other while trying to establish an entailment relation between two portions of text.We intend to take advantage of the Textual Entailment Open Platform under development within the EU project Excitement, (http://www.excitement-project.eu) where FBK participates as the Scientific Coordinator.
URL: http://hlt.fbk.eu/en/openpositions/phd-ict
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
Contact: magnini [at] fbk.eu

CSTV12 - Personalized Machine Translation (1)
The translation industry is rapidly converging to the adoption of Machine Translation (MT) into companies daily workflow thanks to the tremendous progress made by research on statistical MT (SMT) in recent years. At this stage, further progress towards producing high-quality MT output suitable for publication with little or no human intervention seems to call for innovation along two directions: correctness and utility. The candidate will team up a world-class research effort developing new MT technologies, which are capable to learn from (and evolve through) the interaction with users and adapt to their preferences at runtime. Objectives are to advance the state-of-the-art by making statistical MT technology aware of its use, personalising the MT output to individual translators, personalising quality estimation modules to different users perceive MT quality and automatic post-editing the MT output leveraging the user-feedback.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: http://hlt.fbk.eu/en/openpositions/phd-ict
Contact: turchi [at] fbk.eu

CSTV13 - Distributed wireless networking for smart spaces (1)
Smart spaces are characterized by a large, complex set of devices and people interacting to enhance the user experience in a well-defined space. The goal of this thesis is to study elements of reliable wireless communication of sensor networks that form one of the core elements of the smart space. The candidate will work as part of a multi-disciplinary team working to develop a novel architecture for smart spaces.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: https://es.fbk.eu/people/murphy/
Contact: murphy [at] fbk.eu

CSTV14 - Aesthetics in interaction (1)
Aesthetics has been recently recognized as having an important role in how people perceive the interaction with artifacts. Moving beyond the narrow focus on usability, the work of this thesis aims at better understanding the role of beauty and body experience in the human-computer interaction and computer-mediated human-human interaction. In particular, the focus of the study will be on ambient intelligence systems. The thesis will take both a qualitative and a quantitative stance with the aim of providing a reference framework as well as new tools for evaluation and design of new technologies.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
Contact: zancana [at] fbk.eu

CSTV15 - Knowledge extraction for ontology engineering (1)
Albeit the growing maturity of ontological engineering tools, ontology knowledge acquisition remains a highly manual and complex task, that can easily hinder the ontology building process. In spite of the efforts and progresses made in automatic ontology learning, stateof the art methods and tools still mainly focus on the extraction of terms, with few exceptions addressing more complex tasks such as the extraction of (possibly hierarchical) relations, and axioms. Thus the performances of the current algorithms appear to be more suitable to support the construction of light-weight medium-quality ontologies, rather than good quality conceptualizations of a domain according to the good practices in ontology modeling. The aim of this thesis is to investigate how to combine work in automatic ontology learning, which is mainly based on Natural Language processing, information extraction, statistics, and machine learning techniques, and work in methodologies and tools for manual knowledge engineering to produce (semi)-automatic services for ontology learning better supporting the construction of rich and good quality ontologies. The work will start from an investigation of the current techniques available in the field of Natural Language processing and their comparison with the requirements coming from the ontology design methodologies in the ontology engineering field, and will then research how to tailor those techniques in order to fulfill these requirements and to produce services able not only to extract individuals, concepts, relations, hierarchies, and axioms, but to ground them in good ontology practices. The work will address key research challenges in both Natural language processing and ontology engineering. It will have strong algorithmic and methodological aspects, together with implementation-oriented tasks. The activities will be conducted in the Data and Knowledge Management research unit, Fondazione Bruno Kessler (FBK).
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: https://dkm.fbk.eu/index.php/PhD_thesis
Contact: rospocher [at] fbk.eu

CSTV16 - Reasoning-based Process Mining (1)
Background
Process mining is a recent and rapidly emerging research field, aiming at discovering, monitoring and improving real processes by extracting knowledge from event logs readily available in today's (information) systems [1]. The growing diffusion of information systems able to trace, monitor and store process executions, indeed, has made more and more concrete the possibility to provide powerful process analyses, making thus possible to identify bottlenecks in the process execution or misalignments between executions and existing models, to offer aggregated and statistical analyses as well as to predict future problems and suggest model improvements (e.g., pruning no more executed flows). However, despite the several enormous steps carried on in the last decade, as witnessed by the Process Mining Manifesto [1], still a number of open challenges waits to be addressed in this field, as for example, the run-time operational support for processes (i.e., the on-line detection and prediction of problems, and the run-time provision of recommendations towards their resolution), or the management of complex event logs with different characteristics (e.g., too many, too few or too abstract data).
Objective
The aim of this thesis is investigating how to exploit, adapt and combine techniques and approaches borrowed from different research fields, ranging from logic to artificial intelligence, from model checking to statistics, to advance the existing services for process analysis and process model (re-)design from monitoring data. The reasoning-based services provided as output can be for example the verification of complex requirements, constraining the control flow or other dimensions as time or data, or the definition and provision of new metrics and key performance indicators (KPIs). To this purpose, several are the challenges to be faced in the work as, for example, (i) the capability to represent and reason about secondary aspects for business processes such as data, time, resources; (ii) the capability to align execution information with models, when they exist, or to discover models from traces, when they do not exist; (iii) the capability to manage and reason on extremely large quantity of data (big data); (iv) the capability to realize the abovementioned analyses at run-time.
The work will put together theoretical and methodological aspects, including for example the problem conceptualization and representation, as well as implementation and optimization ones, aimed at the development of process analysis services and tools.
[1] Wil M. P. van der Aalst et al., Process Mining Manifesto. Business Process Management Workshops (1) 2011: 169-194
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: https://shell.fbk.eu/index.php/PhD_thesis
Contact: ghidini [at] fbk.eu

CSTV17 - Integrating logical and statistical reasoning (1)
In the last decade, automated reasoning techniques have reached a high level of complexity able to support reasoning on large knowledge repositories expressed in different logical languages. In the meanwhile, complex statistical methods such as support vector machines, kernel methods, and graphical models have been studied and developed whith the objective of automatic learning knowledge from large data-set and of synthesizing the result in a model that supports stochastic inference. one of the most important research direction that started in the last years has the objective of investigating on how the two approaches can be profitably combined. Examples of approaches arebMarkov Logic Networks, Fuzzy Logics, and inductive logic programming.
With this thesis we would like to define a formal framework that integrates in a uniform model reasoning and learning. In this new framework it should be possible to define the following two general tasks:
Learning from data in presence of background knowledge. This task is quite important as it implements what can be seen as incremental learning, where the learning is performed in successive steps, and at each step the system can reuse the knowledge acquired in the previous steps.
Logical reasoning in presence of real observed data. In this task logical reasoning is performed by taking also into account the statistical regularities observable in data. This allows implementing "plausible reasoning" i.e., inference which are not logically fully correct but that are in fact acceptable because some extreme cases never happen (according to the data), and are therefore irrelevant from the statistical point of view.
This new framework should combine one of the standard statistical models, such as graphical models or regularization methods, with automatic reasoning techniques such as SAT based or tableaux based or resolution based reasoning. other semantic web languages, and resolution based theorem provers.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: < ahref="http://dkm.fbk.eu/PhD_thesis" target="_blank">http://dkm.fbk.eu/PhD_thesis
Contact: serafini [at] fbk.eu

CSTV18 - Formal Design and Verification of Complex Systems (2)
Embedded Systems (ES) are computer-based systems interacting with an external environment, usually by means of sensors and actuators, to carry out possibly complex and/or critical functions. Relevant domains include trains, cars, air- and space craft, industrial plants and production machines, exploration rovers.
The doctoral activity will address key problems in the design of complex ES, developing tecniques and tools to ensure the correctness. More specifically, the research activity will be based on the use of techniques from the field of formal verification, including temporal logic, model checking, and Satisfiability Modulo Theories. The objectives include the development of a formal contract-based design framework, where components are associated with formal descriptions of the expected behaviour. Contracts specify the input-output behaviour of a component by defining what the component guarantees, provided that the its environment obeys some given assumptions.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: https://es.fbk.eu/recruit/phd-es-2013.txt
Contact: cimatti [at] fbk.eu

CSTV19 - Engineering for Social and Economic Development (1)
ICTs have demonstrated their capability to foster economic and social development in highly constrained environments, that is, environments in which capabilities, resources, and infrastructure are scarce. The term ICT4D (ICT for development) is often used to denote the development and application of ICT solutions in such situations.
One big challenge in ICT4D is identifying adequate models to support system evolution and operations. Only when these models are found, in fact, the benefits brought by the introduction of new technologies can have a long lasting impact on the beneficiaries.
The goal of the PhD thesis is investigating and defining development processes and technologies which can lower maintenance and operations costs. With a focus on Agile and component-based development techniques, the work will explore aspects related to software engineering economics in the ICT4D context.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: http://ict4g.org/home
Contact: adolfo.villafiorita [at] fbk.eu

CSTV20 - Risk-based Access Control (1)
The goal is to develop an access control model and enforcement mechanisms that support the automatic tuning of authentication, authorization and auditing based on the risk value computed from the result of the transaction.  While most of the existing approaches to risk-based access control evaluate the risk of granting access when the risk threshold is within a bearable interval based on the request, here the goal is to take into account different types of risks (e.g. compliance with  policies or regulations, IPR, fraud), the relation between risk value and the data (e.g. personal information) or processes (e.g. payment) as well as the data volume/precision that a (coalition of) user can access.
URL: http://st.fbk.eu
Contact: armando [at] fbk.eu

 

CSTV21 - Computational Analysis of Historical Texts (1)
The phd position is offered in the newly founded group of digital humanities (DH). Since one of the main topics of DH is the study of historical texts, the candidate will develop tools and methodologies to study major historical transitions based on different information sources. He/she will also investigate how computational techniques can be applied to the treatment of cultural content. The focus of the candidate's research will be in particular the application of temporal processing methodologies to documents in the historical domain.
URL: http://dh.fbk.eu
Email: satonelli [at] fbk.eu


Telecommunications

Project Specific Grants – Department of Information Engineering and Computer Science

TLCTV1 - Innovative Strategies for Robust Antenna Array Analysis and Design (1)
The objective of the research activity will be the study, development, and analysis of innovative strategies for the robust analysis and synthesis of antenna arrays when tolerances are present on the antenna control points
Contact: andrea.massa [at] ing.unitn.it

TLCTV2 -Analysis of multispectral and SAR remote sensing images for environmental monitoring (1)
This activity is related to the the development of advanced image processing and pattern recognition techniques for the analysis of remote sensing images acquired by satellite systems. Images acquired by passives sensors (i.e. multispectral and hyperspectral images) and by active sensors (i.e. Synthetic Aperture Radar) will be considered in the research activity. The developed methods will be applied to different test cases related to environmental monitoring and climate change analysis.
Contact: lorenzo.bruzzone [at] ing.unitn.it

 

Extra grants - project-specific grant made available AFTER the publication of this Call

If you are interested in a applying for a project-specific grant made available AFTER the publication of this Call you must fill in the field "Other" of the Application online with the exact code/s and title/s of the project-specific grant

Project Specific Grants - FBK

TLCTV3 - Acoustic scene analysis and distant-speech recognition (2)
The research focus is in the context of using distant multiple microphones as an input device for acoustic scene analysis and automatic speech recognition. The study investigates various approaches in which the microphone array, or network, can act as front-end of a speech recognizer. Acoustic scene analysis aims to derive automatically information regarding the position of the speaker, to classify the nature of a sound source event, to separate simultaneously active sound sources, and to enhance the signal corresponding to the source of interest. Speech recognition is then fed with the resulting enhanced signal. The research will aim to progress beyond the state-of-the-art in the given scientific areas.
The targeted scenario is the same of DIRHA project (see http://dirha.fbk.eu).
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
URL: http://shine.fbk.eu/en/positions
Contact: omologo [at] fbk.eu

 

TLCTV4 - Remote sensing techniques for digital Earth applications (1)
The candidate will be asked to develop research activities in the field of remote sensing and pattern recognition focusing on different application domains. The output of this activity should be devoted to support a digital monitoring, analysis and sustainable management of the Earth. Remote sensing and pattern recognition have been widely used in specific applications. Particular attention will be devoted to the exploitation of the capabilities of remote sensing and pattern recognition within the large database of a Digital Earth repository.
NOTE Doctoral students awarded cycle 29 scholarships financed by FBK are obliged to maintain confidentiality in regard to the disclosure and use of any information, data, software, discovery, invention, idea, method, process (in any format including the source code) or other knowledge discovered, conceived, developed and/or implemented within the research activities financed relatively not only to the object of the doctorate grant awarded to the doctoral student but also to possible changes made to the object of the grant as agreed with FBK.
Contact: francesca.bovolo@.unitn.it