ACLAI Lab, part of the Mathematics and Computer Science Department at the University of Ferrara, focuses on studying, designing, and delivering artificial intelligence applications. Our research is focused on the edge between logic and AI and our primary objective is to design mathematically sound and formally certified tools. We are also members of the OVERLAY research group.
Prof. Guido Sciavicco
Dr. Giacomo Piva
Dr. Ionel Eduard Stan
Dr. Giovanni Pagliarini
Dr. Federico Manzella
Foundations of modal symbolic learning
We study the foundations of symbolic learning methods lifted to the case of modal logic. Our purpose it to define a complete symbolic framework that includes data analysis, model learning and evaluation, post-hoc symbolic model analysis, and model visualization. Our framework is the basis on which we develop our applied projects; it is completely open-source, written in the language Julia.
EEG reading and interpreting
Within our symbolic learning framework, we extract, interpret, and test symbolic models to extract information from EEG signals. Examples include neurophysiology trials in which subjects undergo several tasks, including artwork observation and/or simple movements, while their brain activity is being recorded. Our goal is to devise symbolic models that explain and predict the outcomes.
We study predictive maintenance tasks of several kinds of machines, using sensors' data and their behavior in time. For example, we considered a predictive task designed to warn against possible 'trip' event in gas turbines, and designed both general and machine-specific symbolic temporal model, which allow the experts not only to perform preemptive shutdowns but also to study what seems to influence the events insurgence.
Information extraction from audio
In collaboration with the leading experts in conversation automation, we study symbolic temporal models of audio for different purposes. Our models aim to extract information about the speaker(s), their characteristics, sentiment, and other relevant characteristics from human and semi-automatic conversations, using innovative approaches based on the audio rather than on the text.
We design, test, and apply symbolic model for online, real-time data from health monitors and accelerometers/gyroscopes. Such models live on health monitor software/hardware systems, specifically built for emergency situations, and are tested in real cases. Real situations that can be monitored include the movement status of the subjects, possible falls and/or injuries, but also cardiac/respiratory events and/or distress. Models are completely symbolic, and produce verifiable rules that can be analyzed, discussed, and possibly modified by the expert.
Geochemical fingerprinting of food products and water resources
We study, design, and implement protocols for geochemical fingerprinting based on physical, chemical, and isotopic data. We work with the Department of Physics and Earth Sciences of the University of Ferrara (Italy), the University of Còrdoba (Spain), and the Ayesa Foundation (Sevilla, Spain).
Medical data management and decision support system
In collaboration with the Research Center for the Study of Menopause and Osteoporosis of the University of Ferrara, we are designing and maintaining a data processing center equipped with a innovative decision support system.
Time series classification
We design and study new time series classification methods using symbolic, temporal-logic based knowledge extraction methods. At the moment, we are applying our techniques to many tasks; among them, we work with Siemens Europa, and we are trying to build systems that allow one to predict the need of maintenance of gas turbines.
ACLAI promotes an undergraduate research initiative for mathematics and computer science students. The purpose of this initiative is to stimulate undergraduate students to start their research career and enrich their curricula with conference and journal publications. The Bachelor Degree in Computer Science within the University of Ferrara, in particular, includes 21 ECTS credits (12+9) for internship and final project; students joining the undergraduate research initiative spend this amount of credits at the ACLAI laboratory, enjoy the possibility of studying extra-curricular topics, and, in some cases, publish early-stage theoretical and implementation results. Current and past students that have joined the program are:
- Dr. Federico Bulzoni
- Dr. Elisabetta Gentili
- Dr. Arianna Soriani
- Dr. Andrea Bercè
- Dr. Alberto Paparella
- Dr. Gabriele Spina
- Dr. Federico Vancini
- Mr. Patrik Cavina
- Dr. Lorenzo Balboni
- Mr. Pietro Poluzzi
- Mr. Michele Ghiotti
- Mr. Riccardo Pasini
- Mr. Riccardo Monego
- Ms. Denys Carbini
- Mr. Andrea Brigato