Computational models for expression communication can contribute to the definition of innovative human-computer interfaces, based on devices capable of understanding and responding to the user’s affective state and behavior.
Development of innovative techniques for spatial audio synthesis with particular attention to binaural audio synthesis based on Head-Related Transfer Functions (HRTFs) and real-time audio rendering.
Development of the "Mixed Structural Modeling (MSM)" framework for the design of HRTFs, combining synthetic modeling paradigms with HRTF selection techniques.
Customization of HRTFs, based on individual anthropometric data, which are used to either fit model parameters or to select recorded components within a dataset of available responses.
Our modern society is becoming every day more reliant on its capability to store, transmit and process digital data, the goal of cybersecurity is to guarantee both the data and the infrastructures in terms of integrity, availability and confidentiality.
The distributed nature of peer-to-peer and ad-hoc networks makes "securing" them against the activities of even a small fraction of malicious users particularly challenging.
Time coordination in P2P and ad-hoc networks
"Physical" information transport in mobile networks
The proliferation of wideband connections, while opening the market to a large number of innovative web-based applications, also turns any home PC into a target for intrusions and drafting into botnets. Furthermore, the "Connected World" vision at the very base of both the Internet of Things and the Cyber-Physical systems makes every object both a target for an attack and a possible injection point for malware. Thus, the capability to exchange electronic data in a secure framework is a basic requirement of the economy of our modern society, and impacts on several other fields (e.g.
Effective mining and learning from big data require innovative methodologies and modern approaches which go beyond traditional data management systems. In particular, Data Science can provide theoretical frameworks, methodologies and algorithms inspired to other scientific areas such as Statistics to mine data, learn models, and predict new trends and labels.
The research in Information Access and Search Engines is concerned with the design, the integration and the evaluation of advanced, scalable systems based on theoretical statistical and probabilistic methods. The combination of theoretical statistical and probabilistic methods, either classical or not classical (e.g. quantum), aims at evolving search engines to more advanced and complex search machines. The group is currently active in:
Biometric systems, to study novel approaches for biometric encryption, to develop new biometric systems (several biometric characteristics are studied: fingerprint/face/palm/knuckleprint/on-line signature/iris/hand identification).
Bioinformatics, to develop new methods for protein, peptide and gene classification, data mining for medical diagnosis. These tools are very useful for speeding the process of developing new drugs.
