Nicola Di Mauro - Home Page

	Nicola Di Mauro
	Ricercatore (Assistant Professor) Dipartimento di Informatica Università degli Studi di Bari "Aldo Moro" Via Orabona, 4 70126 Bari - Italy phone: +39 080 544 2297 fax: +39 080 544 3196 email: ndm at di.uniba.it	Dipartimento di Informatica

Position : Assistant Professor at the Department of Computer Science, University of Bari "Aldo Moro", Italy.

Research Interests

Statistical Relational Learning: Relational Sequence Learning, Learning LPADs
(Cooperative) Clustering-Grouping problems: Coalition Structure Generation
Inductive Logic Programming (ILP) and Multi-relational Data Mining: Theory Revision, Incremental Learning, Subsumption procedures, Multistrategy Learning, Abstraction and Abduction procedures, Stochastic Propositionalization, Approximate Reasoning, Relational Sequence Mining, Generalization models, Similarity measures, Discretization, Conceptual Clustering, Order Effects in Incremental Learning, Learning by Imitation, Learning Agent Behaviour
Document Image Analysis and Recognition: Machine Learning for Digital Document Processing (document classification, document understanding and layout analysis), Content-based Indexing of Digital Documents
Bioinformatics: Machine Learning for Modeling Metabolic Networks, Mining Biologically Active Patterns in Metabolic Pathways, Protein Fold Recognition

From 2005: Assistant Professor at the Department of Computer Science, University of Bari, Italy
From 2008: Member of "Centro interdipartimentale di logica e applicazioni", University of Bari, Italy
2005 Got the PhD in Computer Science defending a Thesis titled First Order Incremental Theory Refinement
April, 2001: Laurea degree in Computer Science, Department of Computer Science, University of Bari

Session Chair: High Performance Algorithms in Artificial Intelligence and Machine Learning @ International Workshop on INTELLIGENT COMPUTING IN LARGE-SCALE SYSTEMS - ICLS 2011

BIO-LOGICAL09 Logic-based approaches in Bioinformatics Workshop - 12 December 2009, Reggio Emilia (Italy)
ISMIS06 - 16th International Symposium on Methodologies for Intelligent Systems - Bari, Italy, September 27-29, 2006

ADMA - International Conference on Advanced Data Mining and Applications (11)
ACML - Asian Conference on Machine Learning (11)
CASoN - International Conference on Computational Aspects of Social Networks (11)
CACS - International Congress on Computer Applications and Computational Science (10, 11)
HAIS - International Workshop on Hybrid Artificial Intelligence Systems (09, 10, 11)
ICAART - International Conference on Agents and Artificial Intelligence (09, 10, 11, 12)
IRCDL - Italian Research Conference on Digital Libraries (12)
ISMIS - International Symposium on Methodologies for Intelligent Systems (08, 09, 11)
MIND - Workshop on Mining Complex Entities from Network and Biomedical Data (11)
NaBIC - World Congress on Nature and Biologically Inspired Computing (11)
S&IIS - International Joint Conference Security and Intelligent Information Systems (11)

KDD11, AIA11, SSCI11, WILF11, PAKDD10-11, CISIS11, CCCT10, ICDM09-10, IEA/AIE05-07,09,11, ECML/PKDD02-06,08,11, ICPR08, SUM08, AIMSA08, ICDAR07, ILP02,04-06,ILP11, ISMIS03-06, ICDM05-06, AI*IA03-05, CCCT05, ECAI04, ISPE/CE03, ECDL02
The Journal of Intelligent Information Systems (JIIS), Data & Knowledge Engineering Journal (DKE), Applied Intelligence Journal (AIJ), Fundamenta Informaticae (FI), International Journal of Data Mining and Bioinformatics (IJDMB), International Journal of Social Network Mining (IJSNM)

Mining Networked Data, togheter with Donato Malerba at CIDM11 (IEEE Symposium on Computational Intelligence and Data Mining), Paris, France - April 11-15, 2011

EC 6th FP Integrated Project VIKEF IP - 507173 (Virtual Information and Knowledge Environment Framework)
NoE-G038-507618 DELOS, a Network of Excellence on Digital Libraries.
EU IST-1999-20882 Project COLLATE "Collaboratory for Annotation, Indexing and Retrieval of Digitized Historical Archive Materials"

COFIN project 2003Tecniche di intelligenza artificiale per il reperimento di informazione di qualità sul Web
COFIN project 2005 Sintesi automatica di modelli astratti a partire da dati temporali o spaziali
Progetto MIUR FAR CHAT - Cultural Heritage fruition & e-learning applications of new Advanced (multimodal) Technologies
Progetto MIUR FAR Laboratorio di Biologia Computazionale per la Biodiversità Molecolare
MURST 2006, Modelli computazionali di Apprendimento Automatico per formalismi ibridi del primo ordine
MURST 2005, Apprendimento induttivo per la annotazione automatica su base semantica di documenti
MURST 2004 Astrazione e Logica descrittiva in Apprendimento Automatico
MURST 2003 Metodi di apprendimento automatico e di data mining per sistemi di conoscenza basati sulla semantica
MURST 2002 Metodi di apprendimento Automatico e Tecniche di interazione per il Semantic Web

POR Puglia - DDTA: Digitalizzazione dei Distretti a supporto della filiera produttiva del Tessile/Abbigliamento

Statistical Relational Learning

RIB: Relational Information Bottleneck: Applying the Information Bottleneck Approach to SRL: Learning LPAD Parameters
Lynx: Probabilistic Models for Relational (Sequence) Learning

Clustering-Grouping Problem

ELK: Algorithms for cooperative grouping (partitioning) problem: ELK is a system implementing some algorithms for solving the coalition structure formation (CSF) (and/or set partitioning) problem.

Inductive Logic Programming

MDLS: An Inductive Logic Programming (ILP) algorithm for discovering first-order (DATALOG) maximal frequent patterns in multi-dimensional relational sequences.
INTHELEX: INcremental THeory Learner from EXamples: An incremental learning system for the induction of hierarchical logic theories expressed as sets of Datalog clauses under Object Identity from positive and negative examples.
A matching procedure for theta-subsumption: A procedure for the complete computation of all solutions to theta-subsumption between Horn clauses
SPROL: Learner of relational concepts based on a stochastic propositionalization technique.
RBK (Random Backtracking Depth First Search): A randomization strategy for ILP, similar to a restart strategy, able to randomly jump in the clause lattice to skip some portion of it.
MILE (Mode-Declarations Incremental Learner from Examples): An incremental algorithm that induces mode declarations from instances of relational concept.

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