Research laboratories

Artificial Intelligence (LINTAR)
Artificial Intelligence

The Laboratory of Artificial Intelligence is focused on the the development and experimentation of models, methods, instruments, and technologies of Artificial Intelligence, including discrete dynamical systems (Cellular Automata and Multi-Agent Systems), and knowledge representation and engineering

Head: Stefania Bandini

Rooms: 1035

Bicocca Security Lab (BiSLab)
Bicocca Security Lab

Bicocca Security Lab is an interdepartmental laboratory that combines the experience in the field of cybersecurity of the Department of Informatics, Systems and Communication and the Department of Law at the University of Milano – Bicocca.

Head: Claudio Ferretti

Rooms: T006, T007

Bioinformatics and Experimental Algorithmics (BIAS)
Experimental Algorithmics

AlgoLab focuses on the study, design, theoretical and experimental analysis of algorithms and data structures for several applications that require paying special attention to computational efficiency.

Head: Paola Bonizzoni

Rooms: 1001

Computational Systems Biology (CSB)

The Computational Systems Biology Lab deals with the development and application of novel mathematical frameworks and computational methods for the analysis of biological systems, with the purpose of identifying and controlling the intracellular and intercellular mechanisms that cause the onset of complex diseases.

Head: Daniela Besozzi

Rooms: 1046, 1004

Data and Computational Biology (DCB)

The research activities of the Data and Computational Biology Laboratory (DCB) focus of genomic and molecular data analysis, especially in conjunction with “Cancer Research”, and on modeling and simulation of biological phenomena tied to therapy control.  In these contexts, the DCB Lab activities concentrated on the reconstruction of tumor progression models, on the more general study of cancer evolution, on optimal therapy design (e.g., for chronic myeloid leukemia – CML) by means of Control Theory methods and on the study of different metabolic regimes and “metabolic rewiring” in various organisms and in cancer.
The DCB Lab developed tools and algorithms for the data analysis of patient’s populations and of individual patients’ Bulk-sequencing and Single-cells data (cfr., TRONCO).  These tools were also integrated in the metabolic regimes’ applications and analysis methods always developed by the DCB Lab (cfr., MAREA).

Head: Marco Antoniotti

Rooms: 1046, 1047

Imaging and Vision (IVL)
Imaging and Vision

The main research areas of the Imaging and Vision Laboratory (IVL) include Color Imaging, Image, Video and Audio Processing, Analysis and Classification; Visual Information Systems; Machine Learning; Image quality; HCI and Biometrics.

Head: Raimondo Schettini

Rooms: 1038, 1048

Informatics and Robotics for Automation (IRA)
Informatics and Robotics for Automation

IRALab was founded in 1999, when Università degli Studi di Milano - Bicocca began its activity. The main research topic in IRALab is Machine Perception and Mobile Robotics.

We are a small and committed group, consisting of an associate professor, a research associate, 2 PhD students, and 2 research assistants. A few master (laurea magistrale) and undergraduate (laurea) students use to participate to our research activities.

Head: Domenico Giorgio Sorrenti

Rooms: 1020, U9-1i117

Information Discovery and Application (ID&A)
information Discovery and Application Laboratory

Research topics: study of algorithms for data management; analysis and presentation of data from elearning platforms; collaborative learning methodologies in educational thematic platforms.

Head: Matteo Dominoni

Rooms: T036

Information & Knowledge Representation, Retrieval, and Reasoning (IKR3)
Logo IKR3 Lab

The laboratory deals with the definition of models and techniques to information and knowledge representation, retrieval and reasoning. In particular, the research activities of the lab focus on the realization of systems for information access, on the analysis of data and information from social media, and on the representation and management of knowledge.

Head: Gabriella Pasi

Rooms: T037, 1003

Laboratorio di Sistemi Complessi
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Le ricerche riguardano il trattamento formale di Sistemi Complessi e Incerti, loro modellazione e applicazioni e la rappresentazione e gestione di conoscenza incerta, tramite logiche non-classiche

Head: Alberto Dennunzio

Rooms: T032

INteraction and SemantIcs for Innovation with Data & Services (INSID&S)
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The INSID&S laboratory develops models based on semantic and human-machine interaction techniques to support the management of large data and value-added services.

Head: Flavio De Paoli

Rooms: 1021, 1022, 1033, T035

Modelling Uncertainty, Decision and Interaction (MUDI)
MUDILogo

The lab hosts training activities (bachelor and master degree theses, internships) and research activities in the field of the representation and management of different forms of uncertainty, with application to machine learning and the development of predictive and discriminatory models and decision support systems, of which the socio-technical component is also studied, as well as the dimensions related to the human-machine interaction and the computer-supported collaboration, particularly in the medical field.

Head: Federico Cabitza

Room: T023

Models and Algorithms for Data and Text Mining (MAD)
Models and Algorithms for Data and Text Mining

Artificial intelligence, Machine learning, Data and Text Mining are the keywords to adequately describe the research activities of the MAD laboratory. The main research topics are; Bayesian networks, causal networks, continuous time Bayesian networks and topic models. In particular, we study and develop algorithms for structural learning from observational data. The main application domains are biology, medicine, finance and recommendation systems.

Head: Fabio Stella

Rooms: T04, T05

Models in decision making and data analysis (MIND)
mind

The laboratory is focused on design, analysis and implementation of algorithms for data analysis, machine learning, modeling and optimization under uncertainty.

Head: Enza Messina

Rooms: 1041, 1042

Models of Concurrency, Communication and Computation (MC3)
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Research subjects include formal models of concurrent and distributed systems, and related techniques for analysis and synthesis.

Head: Pomello Lucia

Rooms: 1034

Multimedia Signal Processing (MMSP)
Gasparini

 The Multimedia Signal Processing Laboratory is headed by Prof. Francesca Gasparini. The group is active in research and teaching in the field of multimedia signal processing and applications.  The main research activities are based on the development of algorithms and methods to process digital signals, from multimedia (audio, images and video), to physiological ones (EEG, Galvanic Skin Response, Heart rate). Machine learning, genetic programming and optimization algorithms are the main techniques used to process and analyze the data.

The analysis of heterogeneous and multimodal signals can be useful in several interdisciplinary fields of research, and the MMSP group is mainly focused in:

  • Multimedia data  processing, analysis, and interpretation. The MMSP group has a strong experience in the field of image quality and image complexity assessment. Several psychophysical experiments were conducted and the subjective data are available on line to the research community.
  • Social networks and multimedia content processing and analysis. Taking advantage of the huge multimedia data available on social networks, MMSP integrates  information coming from multimodal data to understand user behaviors, mood and emotional states.
  • Brain-Computer Interface and Affective Computing. MMSP studies  the problem of detecting and modeling emotions in the context of human-computer interaction, aiming to bridge the gap between human emotions and computational technology. The research of the group is mainly devoted to study the emotions and the stress and relaxation states induced  by visual and acoustic stimuli.

Head: Francesca Gasparini

Rooms: 1013

Natural Computing Lab
NatCompLogo

The research activity of the Natural Computing Lab focuses on the study of innovative computing models, inspired from different natural phenomena or using natural materials (such as, for instance, biomolecules) to store information and compute.

Head: Claudio Zandron

Rooms: 1047

Real time Events and Decision Support (REDS)
Real time Events and Decision Support

The “Real time Events analysis and Decision Support” (REDS) Laboratory is dedicated to the research in the field of software systems, aimed at understanding and controlling the behavior of complex environments evolving in real time.

Head: Fabio Sartori

Rooms: T009

Software Architecture Laboratory (SAL)
Software Architecture Laboratory

The main objective of SAL is to define, develop and experiment architectural models, methodologies, and tools facing the challenges of emerging application domains.

Head: Daniela Micucci

Rooms: 1039, 1040

Software Evolution and Reverse Engineering (ESSeRE)
Software Evolution and Reverse Engineering

ESSeRE Lab research interests focus on the area of reverse engineering, software maintenance, software quality assessment, managing technical debt, software architecture reconstruction, by exploiting traditional approaches and soft computing ones.al software quality assessment

Head: Francesca Arcelli

Room: 1040

Software Test and Analysis (LTA)
LTA

The laboratory of software testing and analysis actively works on the definition of novel methods, techniques, and approaches for the verification and validation of software systems, for the automation of the testing process, for the static and dynamic analysis of software programs, for the design of self-healing mechanisms, and for implementation of automatic program repair solutions.

Head: Leonardo Mariani

Rooms: T033, T034