Research

I'm interested in machine learning and its applications. In particular I've been working on recurrent and recursive neural networks, kernel methods, and graphical models for learning with structured/relational data. I'm also interested in bridging statistical learning and symbolic (logic-based) approaches. These ideas have led to systems such as kFOIL (Landwher et al. 2006; 2010), type extension trees (Frasconi et al. 2008; Jaeger et al. in preparation), and more recently kLog (Frasconi et al. 2012). Application areas of my interest include bioinformatics (in particular protein structure and function, molecular activity), natural language processing, computer vision.

Servers & software

Brain cell finder
is a tool for fully automated localization of soma in 3D mouse brain images acquired by confocal light sheet microscopy
kLog
is a logical and relational language for kernel-based learning embedded in Prolog.
MLOCSR
converts bitmap images of chemical structural formulae into machine readable vector formats (such as MOL and SDF).
MetalDetector
A predictor of protein metal binding state. Source code, Dataset
DISULFIND
A predictor of cysteines bonding state and disulfide bridges.
Disulfinder
A standalone version of DISULFIND, available on Ubuntu 12.04+ and Debian Sid+
kFOIL
Learning simple relational kernels (written by Niels Landwehr and Andrea Passerini)
Type Extension Trees
a powerful representation language for "count-of-count" features characterizing the combinatorial structure of neighborhoods of entities in relational domains (written by M. Lippi).
MLNGTS
Markov Logic Networks with Grounding-Specific Weights, a mod of the Alchemy system (written by M. Lippi).
3DDK
3D and 2D Decomposition Kernels for classification of small molecules (written by A. Ceroni and F. Costa).
WDK
Weighted Decomposition Kernels (C++ Implementation; written by F. Costa).

Funding

PRIN 09
Statistical Relational Learning: Algorithms and Applications. Ministero dell'Istruzione dell'Università e della Ricerca (2011-2013).
SSAMM
Tools supporting the Mobility Metropolitan Agency. Funded by the Foundation for Research and Innovation of the University of Florence.
APrIL II
Applications of Probabilistic Logic Representations. FET funded by the European Commission.
BIOPATTERN
Computational Intelligence for Biopattern analysis in Support of eHealthcare. Network of excellence funded by the European Commission.
BIOPTRAIN
Bioinformatics Optimization Training. A Marie Curie Early Stage Training Programme funded by the European Commission.
PRIN 03
Machine learning tools for text analysis and retrieval. Ministero dell'Istruzione dell'Università e della Ricerca.
PRIN 02
Machine learning tools for structural and functional genomics. Ministero dell'Istruzione dell'Università e della Ricerca.
PRIN 01
Machine learning techniques for quantitative analysis of chemichal compounds. Ministero dell'Istruzione dell'Università e della Ricerca.

Some talks

CoLISD 11
kLog: A Language for Logical and Relational Learning with Kernels. Invited talk at CoLISD 2011 (ECML/PKDD Workshop on Collective Learning and Inference on Structured Data), Athens
IASI 10
Statistical relational learning: some applications to bioinformatics. Colloquia@IASI, Roma, Jan 2010
Dagstuhl 09
Learning protein metal binding Dagstuhl Seminar on Similarity-based learning on structures, Feb. 2009
ILP'07
Learning with Kernels and Logical Representations Invited keynote at the 17th Int. Conference on Inductive Logic Programming (ILP'07)
Fluffy 05
Neural Networks and Kernels for Learning Discrete Data Structures Invited keynote at Freiburg, Leuven & Friends, 2005.
WAML 03
Learning Structured Data: Theory and Applications Invited keynote at the Workshop on Advances in Machine Learning, Montreal June 2003.