Faculty research lines


- Addressing the cognitive and language learning needs of children with hearing loss. An early auditory deprivation may have consequences on the development of cognitive processes that are critical for verbal language learning, such as verbal memory and the ability to process and learn temporal sequences. In my research I explore these cognitive deficits and try to develop adaptive learning tools and technologies that support deaf children in developing these cognitive functions.
-Text simplification for readers with special needs. Text simplification (manual or automatic) consists of procedures that allow to rewrite texts so that they become appropriate to the lingusitic or cognitive skills of readers with language or cognitive deficits (e.g. second language learners, readers with deafness, aphasia, or cognitive impairment). In my research I develop methods of text simplication which could better address the needs of these readers.
-Learning and rehabilitative tools for children with frontal brain deficits. In children, frontal brain dysfunctions can follow from diseases causing strokes to frontal brain areas or chronic cerebrovasculopathy. Children affected by these diseases suffer from a broad-spectrum executive dysfunction, which causes a significant cognitive decline. I am exploring and developing interventions that could contrast this cognitive decline.

Research topics are focused on sensory and perceptual processes in vision, and the underlying neural bases. More in particular:
- Serial effects in perception (the way previously encountered stimuli influence our future perception): priming and adaptation
- Perceptual learning (improving sensory/perceptual functions with practice)
- Modulation of cortical excitability with non-invasive brain stimulation techniques: transcranial electrical stimulation (tES) and transcranial magnetic stimulation (TMS)
- Visual motion perception (and neural bases)
- Improvement of perceptual and cognitive functions with training coupled with transcranial electrical stimulation (tES) in different types of patients

- Evolutionary Psychology, sexual strategies, sexual orientation. Infanticide, pedofilia, sexual abuse.
- Environmental monitoring , conservation and demography of wild Macaca sylvanus, desertification processes.
- Sustainable development and ecology of nomadic tribal populations.
- Evolution of Personality, adaptive value of human psychopatologies.
- Evolutionary forensic psychology, profiling, sexual crimes, risk factors etc.

My research interests and teaching activities are in the field of Health Psychology with a focus on illness experience, caregiving, interactions, healthcare system, and eHealth. Those experiences (e.g. birth, death, and illness) that motivated the use of medical treatment or led to hospitalization are considered within a psycho-social perspective. More specifically, a systemic and constructivist approach is used in order to consider personal experience within a network of social relationships. A specific interest is toward the use of electronic communication and information technologies in the health sector. Research methods include interviews, focus groups, repertory grids, and the analysis of online communities. The method of choice is qualitative approach.

My lab (http://www.dpg.unipd.it/en/deconelab) is engaged in several research projects related to psychobiology, i.e. developmental neuropsychology and rehabilitation. In particular, our principal interests are regarding the sensory, perceptual and attentional functioning and their disorders in specific learning disabilities (e.g., developmental dyslexia and dyscalculia), language impairment, autism spectrum disorder, down syndrome and ADHD. Our recent projects regard neuropsychological rehabilitation by using perceptual learning, action video games and transcranial electrical stimulation. In collaboration with “E. Medea” Scientific Institute we study the genetic bases of specific learning disabilities.

- human-computer interaction, interaction design, ergonomics
- work psychology, distributed cognition and user studies
- smart city and communities
- symbiotic systems
- persuasive technology

My research is focused on sensory perception and in particular in auditory and audiovisual perception. It unfolds along two lines of research. On the one side there is the fundamental research on auditory and audiovisual perception. The goal is to understand how the auditory system works and how it communicates with vision. The second line of research is applied and aims to understand whether it is possible to improve our sensory performance and whether an improvement in the sensory performance reverberates its benefits to the cognitive performance (i.e., relationship between sensation and cognition). Several data suggest that musicians have improved auditory performance in comparison to nonmusicians and that this improvement transfers to the cognitive performance too. I aim to understand whether and why musicians have better sensory and cognitive performance than nonmusicians and whether the benefits of the musical training can be implemented in ad hoc short-duration musical trainings that can be used with people with poor auditory performance (e.g., hearing impaired listeners, cochlear implantees) or specific cognitive impairments.

My main research interests include: neighborhood social capital, civic engagement, generalized trust and cooperation, risk behaviors in adolescence, income inequalities and well-being.

- Neuropsychology
- Neuropsychological rehabilitation
- Cognitive neuroscience, aging, executive functions, decision making,
- Non invasive brain stimulation (TMS, tdcs)

My field of research covers topics in clinical neuropsychology and any issues about cognitive processing in pathological populations. Of particular interest to me are patients with any neurodegenerative disorders, oncologic patients (pre- and post-surgery), vascular patients, patients in pre- and post-transplantation of organs (heart, kidney, etc.), and also patients with respiratory disorders (e.g., OSAS). The assumption is that any clinical condition could affect cognitive functioning.
A research goal is to understand the characteristics of different pathologies and identify which neuropsychological test can better predict cognitive profile and which test can be useful to detect mild cognitive impairment.
Another goal is to evaluate how cognitive/brain reserve interacts with executive functions and how it could predict the outcomes of neuro-rehabilitation or neuro-surgery.
A current project is being developed in collaboration with the Schuhfried Company to devise new computerized tools to measure different patterns of cognitive abilities, for example those needed to drive competently and in safety.

- Emotional reactivity and Hoarding Disorder
- CBT interventions in anxiety disorders and OCD spectrum
- Reinforcement contingencies and internet addiction

My research lines focus mainly on Fake Data Analysis and on the standardized measure of Cognitive Reserve. Lately I concentrated on Bayesian modeling.

My research interests are focused on the relations between the mental representation of space and the representation of various types of quantities/magnitudes (number, time, pitch, etc.). To this aim, I conduct cognitive psychology studies on healthy participants to investigate how space interacts with the abovementioned quantities/magnitudes and to clarify the nature of this interaction. Another research field, consists in the design and standardization of sensitive and specific neuropsychological tests for assessing spatial disorders (such as spatial neglect) following right-hemisphere brain damage. Finally, I am involved in neuropsychological studies, mainly by means of single cases, regarding disorders of object, space, and numerical processing. 

- interaction between diet and excercise on the metabolism of scheletal muscles
- molecular basis of "exercise training adaptation";
- biomechanics of sport activity.

- Aggression, Self Control, internalizing/externalizing symptoms in Adolescence. Living on-line
Aggression is a destructive behaviour not only adverse to adolescents’ development but also to social security. Recent literature has suggested that there was great construct stability of self-control and deviance over the 6-year period and self-control at initial status reduced the unexplained deviance variance; self-control could negatively predict problem behavior, showing significant effects of self-control on emotional and behavioral problems in adolescents. Within the cyber-culture, it occurs problem behaviors among adolescents: online gaming, communicational Internet use, and playing first-person shooters were predictive of externalizing behavior problems (aggression, delinquency) while playing online role-playing games was predictive of internalizing problem behavior (including withdrawal and anxiety). In the current research line, we will focus on the internet use leading to problem behavior (e.g. Internet Addiction Disorder; Internet Dependency; Problematic Internet Use), considering both interpersonal and individual factors, ad assessing quality of self-control, aggression, and other psychological functioning characteristics (e.g. internalizing/externalizing symptoms, alexithymia, rumination, attachment style,…). Cross-cultural differences, as well as a comparison between clinical and non-clinical samples, can be considered.
- Research in psychotherapy. Psychotherapy, a form of therapeutic conversation, is characterized by a differentiated and asymmetric dyadic relationship between patient and therapist. Conversation in psychotherapy is a reciprocal research and exploration through dialogue in which co-constructed meanings continually evolve. Within the micro-processes domain of communicative exchange, researchers indicate early therapeutic alliance like one of the most important predictors of outcome in psychotherapy. Many studies have considered the role of factors mediating alliance construction. As yet, no one has analyzed this process in the case of specific personality (e.g. depressive; narcissistic; dependent…) disorder through the use of a mixed method (observational and selective methods), considering together communicative exchanges (verbal and nonverbal) and psychological features (es. defensive mechanisms). This research project is aimed to explore how the order of the previously described factors influences the therapeutic process. This project will shed light on the efficacy and the specific communicative patterns that emerged during psychotherapeutic interventions. Moreover, could be interesting to compare how the therapeutic process unfolds within a standard vs. on-line setting; this last is increasingly popular, particularly among people who live in rural areas and cannot easily get to a therapist’s office or who are concerned about the costs of in-person therapy.

The research line of my team deal with issues concerning the detection of deception in a great number of forensic fields. We analyse different aspects of the human functioning and behaviour related to a situation of cheating, exploiting a large number of technologies. These include keystroke analysis and mouse/touch kinematic analysis, combined with machine learning techniques.
We are involved in experiments covering the following topics:
-        Online techniques of lie detection
-        Identification of false self-declared identity
-        Identification of false self-declared statements, specially about crimes
-        Identification of malingering
-        Identification of violent social networks users from their activity (posts, likes etc.)
Other research topics of interest are:
-        Cognitive neuroscience
-        Forensic neuroscience
-        Model of eyewitness
The team's strength is the interdisciplinary nature of our research works. In fact, we merge the knowledge derived from cognitive neuroscience with the use of computer technologies. Particularly we apply machine learning to functional and structural neuroimaging and to behavioural and cognitive data.

- Models and study methods of the parental function: biological and psychological aspects.
- Psychopathology of the developmental age.
- Evaluation methods.

- Mediated interaction practices
- Social and ethical aspects of technology usage
- Telepresence and virtual reality
- Persuasive technology

The main lines of research are related to the study of attention, executive functions, prospective memory and time perception. Studies often involved aging and clinical populations.  The research methodology utilizes specially designed experimental tasks and neuropsychological tests. Following some projects: 1. Assessment and rehabilitation of executive functions in traumatic brain injury patients 2. Assessment and rehabilitation of prospective memory in the aging population 3. Assessment tools to detect mild cognitive impairment in the aging population 4. Time perception in normal and clinical populations (traumatic brain injury and Parkinson's disease patients).

My main research interests are: Perception and memory for odours, Environmental odours, Neuropsychology of olfaction, Olfaction in Neurodegenerative disorders, Memory, Mental retardation.


- Machine learning, pattern recognition, kernel learning, transfer learning, bioinformatics, learning in games, time series prediction, information and document retrieval, recommender systems and collaborative filtering.

In order to support software engineers and programmers in the development of correct and reliable software, solidly grounded, mathematical techniques are required allowing for the specification, testing and analysis of system properties. My research focuses on the study of formalisms for the specification and analysis of distributed and concurrent systems, and on their application to the design and analysis of programming languages. More specifically, I am interested in:
- Foundational aspects concerning the semantics of concurrency, with special interest for the so-called true concurrent approach.
- Analysis techniques for concurrent and distributed systems, relying on their truly concurrent semantics. These includes logics for expressing behavioural properties of the modelled systems and verification techniques for such logics.
- Applications of the above analysis techniques in various settings, including weak memory models, program security and information flow analysis, mining and analysis of process models, model-based diagnosis, modelling of biological and ecological systems.

My primary research area is computer vision, closely integrated with applied machine learning and multimedia, specifically focused on exploiting big data for visual recognition problems. The main focus of my current research is on designing learning algorithms that make the most effective use of prior and contextual knowledge in presence of sparse and noisy data.
These are my main research topics:
- Image/video indexing, matching and retrieval.
- Applied machine learning and cognitive computing; pattern recognition; deep learning.
- Computer vision and language; multimedia and multimodal representations.
- Large-scale object recognition and scene understanding.
- Human activity recognition, analysis and tracking; predictive vision.
- Web-vision, social media analysis and visual data mining.
- Human and machine vision

My research activity concerns the development of control algorithms in many different application areas, with particular emphasis on the development of industrial grade solutions. In the framework of the BMCS doctoral program, I teach part of the course on IoT scenarios, in particular, I discuss the Industrial IoT vision, and the impact of IoT on the society. My interest in these topics translates in some of my research lines, namely, those dedicated to the introduction of automated systems in Smart Environments (Smart factories and Smart Communities). Also, I am very interested in studying human-in-the-loop control systems. In particular, I am interested in developing cooperative control strategies between humans and automatic control systems for autonomous and semi-autonomous cars. To this aim, I am involved in the design of advanced motion simulator platforms, that provide a safe, repeatable, and easy to characterize proving ground for testing the control strategies.

- hybrid automata
- finite automata
- temporal representation and reasoning
- spatial and temporal logics

- Security and Privacy in Computer and Network Systems, such as: Mobile
Devices, IoT (Internet of Things), 5G, Cloud Computing, Wireless
Networks, Novel Internet Architectures (e.g., Information Centric
Networks and Software Defined Networks), and Social Networks.
- Machine Learning applications to Security: Traffic Analysis, Side
Channels, Adversarial Machine Learning.
- Usable Security

Main research topics:
• Gamification. Technologies and tools for the definition and operation of gameful persuasive applications in complex socio-technical systems promoting active participation and behavioral change.
• Internet of Services.  User-centric service composition approaches that exploit real world services (not only software services, but also services provided by smart objects, sensors, and people) to provide value added services that are composed, contextualized and customized at run time for a specific situation and user’s needs.
• Collective Systems. Advanced methodologies and techniques for the development of large-scale, collective, socio-technical systems where the adaptations are resolved in a decentralized, yet coordinated, fashion and with a distributed knowledge.

- Pervasive and mobile computing, web technologies, multimedia applications for serious games.

- Information extraction (entity recognition, relation extraction, ...) from biomedical texts, in particular scientific publications in the life science;
- Exploitation of manually curated resources as training material for Machine Learning (ML) approaches;
- Development of tools that can extract key pieces of knowledge from scientific publications and connect them to existing knowledge repositories;
- Use of the most recent ML and NLP techniques (such as word embeddings, neural networks, deep learning);
- Adoption of strong evaluation methodologies, relying on IR/ML/NLP metrics, for experimentally validating the effectiveness of the proposed approaches. In particular, factorial combinations of alternative solutions in order to estimate individual components contributions and to devise predictive performance models.

- Wired/Wireless Networks;
- Distributed Sensing;
- Multimedia Entertainment.


Francesco Ranzato's research work is mainly concerned with abstract interpretation and static analysis of software/hardware systems. Abstract interpretation is a general methodology - invented by French scientists Patrick and Radhia Cousot, who received the 2013 ACM SIGPLAN Programming Languages Achievement Award for this achievement - for designing and formally proving the correctness of approximations of computing systems. This technique provides generic and powerful tools for designing, e.g., static program analyzers, automatic verifiers of software/hardware systems, type systems, security protocol analyzers, etc. Abstract interpretation is a lively research area with a wide active community of European (in particular Italian), American and Asian researchers. Abstract interpretation had a remarkable industrial impact. We can mention a couple of noteworthy examples: (1) the Polyspace static analyzer for C/C++ and Ada programs has been fully conceived and designed by abstract interpretation and is successfully commercialized by MathWorks: https://www.mathworks.com/products/polyspace.html; (2) Infer is a static analysis tool developed by Facebook which automatically detectes null pointer exceptions and memory leak problems in Java/C/C++/Objective-C code: http://fbinfer.com

- constraint reasoning,
- preferences,
- multi-agent systems,
- computational social choice
- artificial intelligence

- Machine learning, pattern recognition, neural networks and kernel methods for structured data, bioinformatics, learning in games, data and business process mining, QSAR studies, time series prediction, information and document retrieval.

My research activities are mainly focused on three areas:
- Activity and Gesture Recognition for wearable devices; the development of Machine Learning-based approaches to characterize the human behavior for health care, home automation and sport applications from sensors such as Inertial Measurement Units;
- Natural Language Processing for Sentiment Analysis; Sentiment analysis is the process of identifying and extracting subjective information from text. Sentiment analysis is widely applied in web-related applications, for the monitoring of social media and, in general, for the monitoring of all contents where people/consumers express and opinion;
- Machine Learning and Deep Learning for industrial applications; the extraction of knowledge from data in industrial processes and products is used to increase productivity and performance. In particular, Machine Learning-based approaches could be used to: provide estimations for quality indicators that are costly or impossible to be measured (Soft Sensors), monitor systems and identify the presence of faults (Fault Detection) and to optimize maintenance actions and related costs (Predictive Maintenance).

1. Elastic scalability and service orientation in the Cloud:
- Exploration and evaluation of software architectures and technology solutions
2. Time-predictable concurrency and parallelism for advanced heterogeneous many-core processors
- Model-driven contract-based specifications to assist software development with property-preserving automated code generation
- Low-overhead high-performance low-jitter run-time implementations
- Hardware enhancements that increase observability or defeat jitter
3. Learning methods
- Leaner-centered and problem-based approaches
- Computational thinking.