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Dino Pedreschi’s cv
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Dino PEDRESCHI Bio sketch Dino Pedreschi is a Professor of
Computer Science at the University of Pisa, and a pioneering
scientist in mobility data mining, social network mining and
privacy-preserving data mining. He co-leads with Fosca Giannotti
the Pisa KDD Lab – Knowledge Discovery and Data Mining Laboratory
http://kdd.isti.cnr.it, a joint research initiative of the
University of Pisa and the Information Science and Technology
Institute of the Italian National Research Council, one of the
earliest research lab centered on data mining. His research focus
is on big data analytics and mining and their impact on society. He
is a founder of the Business Informatics MSc program at Univ. Pisa,
a course targeted at the education of interdisciplinary data
scientists. Dino has been a visiting scientist at Barabasi Lab
(Center for Complex Network Research) of Northeastern University,
Boston (2009-2010), and earlier at the University of Texas at
Austin (1989-90), at CWI Amsterdam (1993) and at UCLA (1995). In
2009, Dino received a Google Research Award for his research on
privacy-preserving data mining. Research activity D. P. is the
(co-)author of more than 200 publications on the following topics:
- Big Data Analytics & Social Mining: Analysis of human
mobility, Social Network Analysis and
Mining, Privacy-by-design and ethical data mining, Nowcasting of
socio-economic indicators, Complex Network Dynamics.
- Data Mining and Knowledge Discovery in Databases:
Privacy-preserving Data Mining, Spatio-temporal Data Mining,
Constraint-based Pattern Discovery, Data Mining Query Languages,
Knowledge Discovery Support Environments, Mobility data mining,
Market Basket Analysis, Fraud Detection.
- Databases and Knowledge-bases: Logic in Databases,
Expressiveness Analysis of Logic Query Languages, Non monotonic Non
Deterministic Temporal Reasoning, Deductive and Object-oriented
Databases
- Formal Methods: Partial (symbolic) Evaluation in Functional
Programming, Termination of Logic Programs, Verification of Logic
Programs, Type Systems in Logic Languages and Databases
- Logic Programming: Foundations, Semantics of negation,
Integration with functional programming, Modular programming
The Computer Science Bibliography server dblp.uni-trier.de
records 160 papers from 1985 until today (see complete list at
http://www.informatik.uni-trier.de/~ley/db/indices/a-tree/p/Pedreschi:Dino.html)
Among D.P.’s publications, 44 journal publications are reported in
the ISI repository. Google Scholar reports 200+ publications, which
received 4225 citations. His h-index at Oct 17, 2013 is 33. 75
papers co-authored by DP received more than 10 citations. The
figure shows the temporal distribution of citations in DP’s career
at Oct 17, 2014. D.P. is the co-editor (with Fosca Giannotti) of
the book “Mobility, Data Mining and Privacy”, Springer, 2008, which
settles the ground of the novel interdisciplinary area of research
of privacy-aware spatio-temporal data mining of mobility data. D.
P. co-leads (with Fosca Giannotti) the Pisa KDD Lab - Knowledge
Discovery and Delivery Lab - a joint research initiative of the
University of Pisa and the Information Science and Technology
Institute of the Italian National Research Council, the earliest
Italian research group specifically targeted at data mining, and
one of first in Europe http://kdd.isti.cnr.it D. P. is a member of
the program committee of the main international conferences on data
mining and knowledge discovery. He has been a co-chair of ECML/PKDD
2004, the European conference on
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Machine Learning and Knowledge Discovery in Databases, and a
vice-chair of ICDM 2005, the IEEE Int. Conf. on Data Mining, and
ICDE 2014, the IEEE Int. Conf. on Data Engineering. Main current
research lines Mining mobility data: spatio-temporal data mining
techniques for trajectories of moving objects reconstructed from
telecommunication logs, especially from mobile phones, GPS and
other location-aware devices. Main results: methods for trajectory
pattern discovery and clustering of trajectory data, analytical
platform for urban mobility. Privacy-preserving data mining:
privacy-aware data mining techniques for the discovery of patterns
and models that do not disclose sensitive information of the source
data. Main results: methods for privacy-aware pattern discovery and
clustering of trajectory data, anonymization of mobility data.
Complex network analysis and data mining: data mining techniques
for the discovery of patterns and models for network (graph) data.
Main results: network analytics for multi-dimensional networks,
discovery of eras in evolving social networks, analysis of dynamic
mobile social networks and the interplay between mobility and
social ties, analysis of economic complexity of consumers and
products based on transaction data. Main projects D.P. and the KDD
LAB Pisa have led a stream of FET-Open projects that, since 2004,
pioneered the area of mobility data mining, privacy-preserving data
mining and privacy-by-design. The pioneer project has been GeoPKDD
(Geographic Privacy-aware Geographic Knowledge Discovery and
Delivery, 2004-2009, www.geopkdd.eu), who delivered a privacy-aware
analytical platform for the mining of movement data (mobile phone
data and GPS trajectories from navigation devices). The results
have been selected for showcase at the European Parliament in April
2010
(http://kdd.isti.cnr.it/content/geopkdd-exhibition-european-parliament).
The resulting system has unprecedented capabilities to unveil the
complexity of human mobility by querying and mining massive
trajectory data. Successors of GeoPKDD within the FET-Open program
are: − LIFT – Using Local Inference in Massively Distributed
Systems (2009-2013, http://lift-eu.org/),
where privacy-by-design is adopted in highly distributed
techno-social systems for the analysis of collective behavior
− DATASIM – A Data Science for Simulating the Era of Electric
Vehicles (2012-2016, http://www.datasim-fp7.eu) where mobility data
mining, network science and agent-based simulation are merged to
achieve realistic forecasts of the impact on mobility and power
demand of a massive switch to electric cars.
D.P. is the coordinator of the Privacy Observatory
(http://privacyobservatory.org/) of the FET-Open Coordination
Action MODAP – Mobility, Data Mining and Privacy (2008-2012,
www.modap.org). Project coordination activity Since 1993, DP has
been a member and a PI in 20+ projects funded by Italian, European
and international funding agencies, including EC FET-Open and US
NSF. Teaching activity D. P. has taught classes on programming
languages, databases, data mining, web mining and social network
analysis in universities in Italy and abroad, both at undergraduate
and at graduate/doctoral level. Currently, he teaches Databases at
the undergraduate program of Humanities Computing, and Data Mining
and Social Network Analysis at the graduate program of Computer
Science and Business Informatics. D. P. has been the advisor of
more than 80 master theses and 12 PhD theses. Currently, he is
supervising five doctoral candidates in the PhD schools of Computer
Science and Computer Engineering. He served as the coordinator of
the program of studies in Computer Science at the University of
Pisa (1997-2000), and as a vice-rector of the same university, with
responsibility in teaching affairs and the implementation of the
two-tier curriculum of studies, according to the Bologna process
(2000-2002).
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D.P. has been one of the ten Italian Bologna Promoters in
2004-2005. He is currently a member of the Commission for Big Data
and Official Statistics of ISTAT, the Italian national statistical
institute.
Scientific Leadership Profile Dino Pedreschi is an active
researcher in computer science for 25+ years. In the first part of
his career, the focus of his activity was on formal methods in
programming, especially logic programming; progressively, he
shifted towards logic and formal methods in databases and,
eventually, to data mining and knowledge discovery. His path,
essentially, is from computing to data to knowledge, with a
progression tied up with logic and formal methods, and a natural
taste for combining theory with empirical evidence. The most
important shift in D.P.’s scientific career takes place around
1995, when, together with colleagues Fosca Giannotti of the
National Research Council (CNR) and Franco Turini of Univ. Pisa, he
starts the Pisa Knowledge Discovery and Delivery Laboratory – KDD
LAB – a joint initiative of the two research institutions (CNR and
Univ. Pisa) aimed at research in the emerging field of Data Mining
and Knowledge Discovery in Databases. Since then, when KDD LAB was
the earliest research lab in data mining in Italy and one of the
earliest in Europe, it has grown as an established joint,
interdisciplinary initiative, and gained a solid international
reputation in the highly competitive area of data mining. Today,
KDD LAB can count on 5 senior researchers, 4 junior researchers, 5
postdoc, 7 PhD students, 4 technicians, and a variable number of
international visitors. Data mining, i.e., the process of
automatically discovering useful information in large data
repositories, turned out as a natural docking, where theoretical
and empirical investigation are intertwined and interdisciplinarity
is the rule. Early results were application oriented, e.g., a
logic-based data mining methodology for market basket analysis in
the retail industry, and the development of a predictive model for
identifying tax evaders starting from the fiscal data warehouse of
the Italian Ministry of Finance – the results of the fiscal fraud
detection study were published at the ACM KDD Conf. in 1999
(acceptance rate 10%). The most recognized scientific results
arrived after 2000: a brand new interdisciplinary direction was
started, at the crossroads of mobility, data mining and privacy,
i.e., privacy-aware spatio-temporal data mining from mobility data,
such as the data gathered by wireless networks and location-aware
devices. This is the subject of the European FP6 project GeoPKDD –
Geographic Privacy-aware Knowledge Discovery and Delivery – started
in 2005 and co-coordinated with Fosca Giannotti, who is also
co-editor of the book “Mobility, Data Mining and Privacy”,
published by Springer in 2007. This new area of research, started
by D.P. and his colleagues, emerged later as a hot topic, with
plenty of activity in many diverse areas. The early results by D.P.
in trajectory pattern discovery, trajectory clustering and
anonymity-preserving pattern discovering, presented at major data
mining conferences and highly cited, contributed to forge the newly
emergent area, and influenced the research of many young
researchers within and outside the GeoPKDD community. One of the
seminal papers, “Trajectory patterns mining”, presented in the 2007
edition of the top-ranked data mining conference, ACM SIGKDD,
received more than 500 citations in a few years. The impact may
also be witnessed by the many invitations to D.P. to participate in
symposia aimed at discussing the future directions of data mining,
including the 2007 NSF Symposium on Next Generation Data Mining
(Baltimore, US), the IEEE Data Mining Forum 2008 (Hong Kong), and
the Int. Conf. on Network Science (NetSci2010, Boston). Together
with colleagues F. Turini and S. Ruggieri, D.P. is also the
initiator of discrimination-aware data mining, aimed at analyzing
the risks of unfair, discriminatory decision making based on data
mining rules. Given the many interfaces and open problems among
privacy-aware data mining, the data protection laws and
regulations, and the active research of jurists on the right to
anonymity, a Privacy Observatory was created by the GeoPKDD project
in 2006, as a forum of discussion among researchers in data mining,
law, geography, social sciences, statistics, telecommunication and
transportation engineering. The liaisons established by the
Observatory and its workshops created a follow-up coordination
action within the FET program, called MODAP – Mobility, Data Mining
and Privacy, where the Privacy Observatory is continuing to grow.
D.P. is the editor of the online magazine of the PO,
http://www.privacyobservatory.org/, and a consultant to the Italian
Data Protection Commission (Garante Privacy) on the topics of
anonymity, data retention and personal data.
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Currently, D.P. and F. Giannotti are frontrunners in shaping the
BIG DATA frontier, where data mining meets the science of complex
networks and the quantitative approaches to socio-economic
sciences. During the sabbatical year 2009-2010 spent at the Center
for Complex Network Research at Northeastern University in Boston,
collaborating with Albert-Laszlo Barabasi and his group, D.P. has
laid the basis for a fruitful convergence of the methods of
statistical physics and complex systems with data mining, aimed at
understanding and forecasting aspects of the socio-economic
complexity, such as epidemic spreading, opinion and sentiment
analysis, shopping behavior, mobility patterns. A recent result,
published again at SIGKDD in 2011, jointly with Barabasi and
colleagues, show how society-wide data from mobile call records can
be analyzed to show the correlations between social ties and mobile
behavior, and to predict with surprising accuracy the formation of
novel social links. D.P. is collaborating with many other European
colleagues in ICT, complex systems and socio-economic sciences to
shape FuturICT, an ambitious interdisciplinary research program
(www.futurict.eu). DP is the co-author of several vision papers on
big data analytics and social mining, on the planetary nervous
system idea. Among the PhD’s that have been supervised by D.P. in
the past, two are now members of KDD LAB (Salvatore Ruggieri, Univ.
Pisa, and Mirco Nanni, CNR), one is now a researcher at Yahoo!
Research in Barcelona, Spain (Francesco Bonchi), one is a
researcher at CNR in Cosenza, Italy (Giuseppe Manco), one is a
researcher at University of Cagliari (Maurizio Atzori), two are
researchers at the IBM Research center on Smart Cities in Dublin
(Michele Berlingerio and Fabio Pinelli), one is a senior researcher
at JRC (Joint Research Center) of the European Commission (Laura
Spinsanti) and one is a post-doc at the Harvard Kennedy School in
Cambridge, MA (Michele Coscia). In the period 1997-2002, D.P. also
served as a coordinator of courses of study, first as the head of
the CS curriculum, and next as a vice-rector of the overall
University of Pisa. His responsibility was the implementation of
the two-tier curriculum structure of the Bologna process, aimed at
creating a coherent European Higher-Education Area. In this
context, D.P. pushed the creation of multi-disciplinary and
inter-disciplinary degrees: in the CS sector, he promoted the
creation of a curriculum in Informatica Umanistica (Humanities
Computing, BSc and MSc level) and one in Business Informatics (MSc
level). Nowadays, both curricula have brilliantly passed quality
evaluation procedures, and are attracting highly motivated and
skilled students from anywhere in Italy. At the end of 2002, D.P.
quit his service as a vice-rector, and resumed full time (and
happily) his research work.
10-Year-Track-Record Top selected publications in scientific
journals - A Monreale, S Rinzivillo, F Pratesi, F Giannotti, D
Pedreschi. Privacy-by-design in big data analytics
and social mining. EPJ Data Science 3 (1), 1-26 Springer (2014).
Available open access at
http://link.springer.com/article/10.1140/epjds/s13688-014-0010-4
- A Monreale, D Pedreschi, RG Pensa, F Pinelli. Anonymity
preserving sequential pattern mining. Artificial Intelligence and
Law 22 (2), 141-173 (2014)
- Michele Coscia, Giulio Rossetti, Fosca Giannotti, Dino
Pedreschi: Uncovering Hierarchical and Overlapping Communities with
a Local-First Approach. ACM Trans. On Knowledge Discovery from Data
9(1): 6 (2014)
- M Berlingerio, M Coscia, F Giannotti, A Monreale, D Pedreschi.
Multidimensional networks: foundations of structural analysis.
World Wide Web 16 (5-6), 567-593 (2013)
- F Giannotti, LVS Lakshmanan, A Monreale, D Pedreschi, H Wang.
Privacy-preserving mining of association rules from outsourced
transaction databases. IEEE Systems Journal, 7 (3), 385-395
(2013)
- Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna
Monreale, Dino Pedreschi: Evolving networks: Eras and turning
points. Intelligent Data Analysis 17(1): 27-48 (2013)
- L Pappalardo, S Rinzivillo, Z Qu, D Pedreschi, F Giannotti.
Understanding the patterns of car travel. The European Physical
Journal Special Topics 215 (1), 61-73 (2013)
- F Giannotti, D Pedreschi, A Pentland, P Lukowicz, D Kossmann,
J Crowley, D Helbing. A planetary nervous system for social mining
and collective awareness. The European Physical Journal Special
Topics 214(1) p. 49-75. Springer (2012). Available open access at
http://link.springer.com/article/10.1140/epjst/e2012-01688-9
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- Jeroen van den Hoven, Dirk Helbing, Dino Pedreschi, Josep
Domingo-Ferrer, Fosca Giannotti, Markus Christen. FuturICT – The
road towards ethical ICT. The European Physical Journal Special
Topics 214, 153-181. Springer (2012).
- S Rinzivillo, S Mainardi, F Pezzoni, M Coscia, D Pedreschi, F
Giannotti. Discovering the geographical borders of human mobility.
KI-Künstliche Intelligenz 26 (3), 253-260 (2012)
- Fosca Giannotti, Mirco Nanni, Dino Pedreschi, Fabio Pinelli,
Chiara Renso, Salvatore Rinzivillo, Roberto Trasarti: Unveiling the
complexity of human mobility by querying and mining massive
trajectory data. The VLDB Journal 20(5): 695-719 (2011)
- Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna
Monreale, Dino Pedreschi: The pursuit of hubbiness: Analysis of
hubs in large multidimensional networks. Journal of Computational
Science 2(3): 223-237 (2011)
- Roberto Trasarti, Fosca Giannotti, Mirco Nanni, Dino
Pedreschi, Chiara Renso: A Query Language for Mobility Data Mining.
Int. Journal on Data Warehousing and Mining 7(1): 24-45 (2011)
- Aris Gkoulalas-Divanis, Yücel Saygin, Dino Pedreschi: Privacy
in mobility data mining. SIGKDD Explorations 13(1): 4-5 (2011)
- Michele Coscia, Fosca Giannotti, Dino Pedreschi: A
classification for community discovery methods in complex networks.
Statistical Analysis and Data Mining 4(5): 512-546 (2011)
- Anna Monreale, Roberto Trasarti, Dino Pedreschi, Chiara Renso,
Vania Bogorny: C-safety: a framework for the anonymization of
semantic trajectories. Transactions on Data Privacy 4(2): 73-101
(2011)
- Salvatore Ruggieri, Dino Pedreschi, Franco Turini: Integrating
induction and deduction for finding evidence of discrimination.
Artif. Intell. Law 18(1): 1-43 (2010)
- Salvatore Ruggieri, Dino Pedreschi, Franco Turini: Data mining
for discrimination discovery. TKDD 4(2): (2010)
- Anna Monreale, Gennady L. Andrienko, Natalia V. Andrienko,
Fosca Giannotti, Dino Pedreschi, Salvatore Rinzivillo, Stefan
Wrobel: Movement Data Anonymity through Generalization.
Transactions on Data Privacy 3(2): 91-121 (2010)
- M. Atzori, F. Bonchi, F. Giannotti, D. Pedreschi. Anonymity
preserving pattern discovery. VLDB J. 17(4): 703-727 (2008)
- S. Rinzivillo, D. Pedreschi, M. Nanni, F. Giannotti, N.
Andrienko, G. Amdrienko: Visually driven analysis of movement data
by progressive clustering. INFORMATION VISUALIZATION 7: 225-239
(2008)
- M. Nanni, D. Pedreschi. Time-focused clustering of
trajectories of moving objects. J. OF INTELLIGENT INFORMATION
SYSTEMS 27(3): 267-289 (2006)
- F. Bonchi, F. Giannotti, A. Mazzanti, D. Pedreschi. Efficient
breadth-first mining of frequent pattern with monotone constraints.
KNOWLEDGE AND INFORMATION SYSTEMS 2005 8(2) 131-153
- M. Atzori, F. Bonchi, F. Giannotti, D. Pedreschi. Anonymity
and data mining. COMPUTER SYSTEMS SCIENCE AND ENGINEERING 2005
20(5)
- F. Bonchi, F. Giannotti, A. Mazzanti, D. Pedreschi. Exante: A
Preprocessing Method for Frequent Pattern Mining IEEE INTELLIGENT
SYSTEMS 2005 20(3) 25-31
Publications of monographs and editors of conference proceedings
- (F. Giannotti, D. Pedreschi, Eds.) Mobility, Data Mining and
Privacy. Springer, ISBN 978-3-540-
75176-2, December 2007 Top recent publications in peer-reviewed
conference proceedings - Anirban Basu, Anna Monreale, Juan Camilo
Corena, Fosca Giannotti, Dino Pedreschi, Shinsaku
Kiyomoto, Yutaka Miyake, Tadashi Yanagihara, Roberto Trasarti: A
Privacy Risk Model for Trajectory Data. IFIPTM 2014: 125-140
(2014)
- L Milli, A Monreale, G Rossetti, F Giannotti, D Pedreschi, F
Sebastiani. Quantification trees. Data Mining (ICDM), 2013 IEEE
13th International Conference on, 528-536 (2013)
- D Pennacchioli, M Coscia, S Rinzivillo, D Pedreschi, F
Giannotti. Explaining the product range effect in purchase data.
Big Data, 2013 IEEE International Conference on, 648-656 (2013)
- D Pennacchioli, G Rossetti, L Pappalardo, D Pedreschi, F
Giannotti, M Coscia. The Three Dimensions of Social Prominence.
Social Informatics, 319-332 (2013)
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- Michele Coscia, Giulio Rossetti, Fosca Giannotti, Dino
Pedreschi: DEMON: a local-first discovery method for overlapping
communities. 18th ACM SIGKDD Int. Conf. on Knowledge Discovery and
Data Mining KDD 2012: 615-623.
- Dashun Wang, Dino Pedreschi, Chaoming Song, Fosca Giannotti,
Albert-László Barabási: Human mobility, social ties, and link
prediction. 17th ACM SIGKDD Int. Conf. on Knowledge Discovery and
Data Mining KDD 2011: 1100-1108
- Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna
Monreale, Dino Pedreschi: Foundations of Multidimensional Network
Analysis. IEEE Int. Conf. on Advances in Social Networks Analysis
and Mining ASONAM 2011: 485-489
- Fosca Giannotti, Mirco Nanni, Dino Pedreschi, Fabio Pinelli,
Chiara Renso, Salvatore Rinzivillo, Roberto Trasarti: Mobility data
mining: discovering movement patterns from trajectory data.
Computational Transportation Science 2010: 7-10
- Roberto Trasarti, Salvatore Rinzivillo, Fabio Pinelli, Mirco
Nanni, Anna Monreale, Chiara Renso, Dino Pedreschi, Fosca
Giannotti: Exploring Real Mobility Data with M-Atlas. ECML/PKDD (3)
2010: 624-627
- Mirco Nanni, Roberto Trasarti, Chiara Renso, Fosca Giannotti,
Dino Pedreschi: Advanced knowledge discovery on movement data with
the GeoPKDD system. EDBT 2010: 693-696
- Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna
Monreale, Dino Pedreschi: Towards discovery of eras in social
networks. ICDE Workshops 2010: 278-281
- Michele Berlingerio, Michele Coscia, Fosca Giannotti, Anna
Monreale, Dino Pedreschi: As Time Goes by: Discovering Eras in
Evolving Social Networks. PAKDD (1) 2010: 81-90
- Giannotti, F., Lakshmanan, L. V. S., Monreale, A., Pedreschi,
D., Wang, W. (H.). Privacy-preserving Mining of Association Rules
from Outsourced Transaction Databases. In Proc. 3rd International
Conference, Computers, Privacy & Data Protection An Element of
Choice, 2010.
- Salvatore Ruggieri, Dino Pedreschi, Franco Turini: DCUBE:
discrimination discovery in databases. SIGMOD Conference 2010:
1127-1130
- Anna Monreale, Roberto Trasarti, Chiara Renso, Dino Pedreschi,
Vania Bogorny: Preserving privacy in semantic-rich trajectories of
human mobility. SPRINGL 2010: 47-54
- D. Pedreschi, S. Ruggieri, F. Turini: Measuring Discrimination
in Socially-Sensitive Decision Records. Proc. SIAM International
Conference on Data Mining, SDM 2009, p. 582-591
- D. Pedreschi, S. Ruggieri, F. Turini: Discrimination-aware
data mining.14th ACM SIGKDD 2008: 560-568
- F. Giannotti, M. Nanni, F. Pinelli, D. Pedreschi: Trajectory
pattern mining. 13th ACM SIGKDD Int. Conf. on Knowledge Discovery
and Data Mining KDD 2007: 330-339
- M. Atzori, F. Bonchi, F. Giannotti, D. Pedreschi: Towards
Low-Perturbation Anonymity Preserving Pattern Discovery. 21st ACM
SAC 2006 588-592
- F. Giannotti, M. Nanni, D. Pedreschi: Efficient Mining of
Temporally Annotated Sequences. 6th SIAM DM 2006 346-357
