Professor, Umeå University, Sweden
Personal web page here
A NEW book:
V. Torra (2022) Guide to Data Privacy: Models, Technologies, Solutions, Springer.
Introductory text to the field of data privacy, based on my lectures and my own research. It described privacy models (e.g., differential privacy, k-anonymity, privacy from re-identification, homomorphic encryption, secure multiparty computation), and devoted chapters to implementations for these privacy models (e.g., algorithms for differential privacy and k-anonymity, and examples of secure multiparty computation). This book belongs to Springer series title Undergraduate Topics in Computer Science (UTICS).
Two postdoc positions are expected during the academic year 2022-2023 (PrivAcy-AWare traNSparent deCIsions research group, Dept. Computing Science, Umeå University, Sweden).
If you are planning to invite me to review a paper the following is of your interest:
I am over-committed with reviews. So, I tend to decline reviews unless I am in the editorial board of the journal, the program committee of the conference, or it is an invitation from a journal in which I regularly publish. In particular, I decline by default all papers on hesitant fuzzy sets (I am very sorry but I have no time to read them all). Naturally, if a paper seems very interesting to me I may override these rules.
MIT-huset, Umeå universitet,
Umeå universitet, 901 87 Umeå, Sweden.
Plenary talk at INFUS 2022 (İzmir, -- online -- 2022).
Alan Said, Vicenç Torra (2019) Data Science in Practice, Springer.
"Data science is the science of data. Its goal is to explain processes and objects through the available data. The explanation is expected to be objective and accurate enough to make predictions. The ultimate goal of the explanations is to make informed decisions based on the knowledge extracted from the underlying data" (Chapter 1). This book approaches big data, artificial intelligence, machine learning, and business intelligence through the lens of Data Science. The book is structured into three parts: (i) the core concepts of data science, (ii) application domains, and (iii) specific tools for data science.
Note that my old email address vt**ra@ii*a.c*ic.** does not work any more.
V. Torra (2016) Scala: from a functional programming perspective, Springer. (LNCS 9980)
Text based on my lectures in the course Advanced Programming in the Master of Data Science (University of Skövde)
Transactions on Data Privacy
Indexed at DBLP, ACM Digital Library, MathSciNet, DOAJ, Elsevier (Scopus, EI)
FORTE project: "Appropriate automation: Toward and understanding of robots and AI in the social services from an organizational and user perspective" (FORTE 2021-01422, 2021-2027).
Vetenskapsrådet project: "Disclosure risk and transparency in big data privacy" (VR 2016-03346, 2017-2021).
6 Recent papers:
- Big data privacy and anonymization:
K. S. Adewole, V. Torra (2022) Privacy Issues in Smart Grid Data: From Energy Disaggregation to Disclosure Risk, in DEXA 2022 71-84.
- Privacy-preserving ML model selection: (download)
V. Torra, M. Taha, G. Navarro-Arribas, The space of models in machine learning: using Markov chains to model transitions, Progress in Artificial Intelligence 10:3 (2021) 321-332.
- Integral privacy: (download)
V. Torra, Towards integrally private clustering: overlapping clusters for high privacy guarantees, Proc. PSD 2022.
- ML, record linkage, and disclosure risk: (download)
N. Senavirathne, V. Torra (2021) Dissecting Membership Inference Risk in Machine Learning, Proc. CSS 2021: 36-54.
- Decision making and aggregation: (download)
J. Dujmovic, V. Torra (2021) Properties and comparison of andness-characterized aggregators, Int. J. Intell. Syst. 36 1366-1385.
- Non-additive measures and integrals: (download, open access)
S. S. Negi, V. Torra (2022) Delta-Choquet integral on time scales with applications, Chaos, Solitons and Fractals 157 (2022) 111969.
I have written the following books (selection):
I am busy organizing
| Selected activities
Recent invited talks:
(INFUS 2022); Non-additive measures, set distances and cost functions on sets: A Fr\'echet-Nikodym-Aronszajn distance and cost function (IUKM 2019); Big Data Privacy and Anonymization (IFIP Summer School 2016 on Privacy and Identity Management for Life); Choquet integral: distributions and decisions (83rd EWG-MCDA 2016); Transparency and Disclosure Risk in Data Privacy (PAIS 2015)
Editor: Transactions on Data Privacy
Editorial board: Fuzzy Sets and Systems (2004-), IEEE Transactions on Fuzzy Systems (2019-2022), Progress in Artificial Intelligence (2011-), J. of Advanced Computational Intelligence and Intel. Informatics (2007-), Int. J. of Computational Intelligence System (2008-), Information Sciences (2009-2019), Mathware and Soft Computing (2001-2010), EUSFLAT newsletter (Editor, 2005-2009), ACIA Newsletter (Butlletí de l'Associació Catalana d'Intel·ligència Artificial; NODES), Journal of Privacy Technology (2004-2007), Intelligent Decision Technologies (2007-2009?)
Conferences (organization): MDAI 2004-2023 (PC co-chair); AGOP 2017 (chair); SweDS 2016 (chair); PST 2015 and (Privacy track PC co-chair); PSD 2004 (PC co-chair); CCIA 1998 (General chair)
Scientific associations: EUSFLAT (European Soc. for Fuzzy Logic and Techn.) (board 2001-2009; 2013-2017). ACIA (AI Catalan Assoc.) (Founding member, board 1996-2000; president 2010-2014). IEEE Institute of Electrical and Electronics Engineers (member 1996-, senior 2003-, fellow 2017-).
My research interests are between computer science and applied mathematics. I am interested in approximate reasoning, data privacy, machine learning (data mining and statistical learning), decision making, data aggregation and information fusion, fuzzy set theory.
My specialization is in data privacy and in approximate reasoning.
In more details:
|Brief biographical history||
1991. B. Sc. in Computer Science,
Universitat Politècnica de Catalunya (UPC) |
1992. M. Sc. in Computer Science, UPC
1994. Ph. D. in Computer Science (Ph.D. Program on AI), UPC
1994. Assistant Professor (tenured), Universitat Rovira i Virgili (URV)
1994-1995. Deputy Dean of the School of Engineering, URV
1997. Associate Professor (tenured), URV
1999. Tenured Scientist (Associate Professor - Research Track), IIIA-CSIC
2004. Acreditation for Full Professorship
2008. Research Scientist (Senior Associate Professor - Research Track), IIIA-CSIC
2010. EurAI Fellow (former ECCAI)
2013. ISI Elected member
2014. Professor in Informatics, University of Skövde, Sweden
2016. IEEE Fellow.
2018. Professor, Hamilton Institute, Maynooth University, Ireland.
2020. Professor, Department of Computing Science, Umeå University, Sweden.
Books (monographs, selected): (see above)
Data privacy: (More detailed information and papers on data privacy here )
- N. Senavirathne, V. Torra, Integrally Private Model Selection For Decision Trees, Computers \& Security 83 (2019) 167-181. (here: open access)
- V. Torra, G. Navarro-Arribas, Integral Privacy, Proc. CANS 2016 661-669. (here)
- V. Torra, Constrained Microaggregation: Adding Constraints for Data Editing, Transactions on Data Privacy 1:2 (2008) 86-104. (here)
- J. Nin, J. Herranz, V. Torra, Rethinking rank swapping to decrease disclosure risk, Data & Knowledge Engineering, 64:1 (2008) 346-364. (here)
- J. Domingo-Ferrer, V. Torra, Ordinal, Continuous and Heterogeneous k-Anonymity Through Microaggregation, Data Mining and Knowledge Discovery, 11:2 (2005) 195-212. (here)
- J. Domingo-Ferrer, V. Torra, Disclosure control methods and information loss for microdata, in P. Doyle, J. I. Lane, J. J. M. Theeuwes, L. V. Zayatz (Eds), Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies, (ISBN:0-444-50761-2, North-Holland, 2001), 91-110. (here)
- J. Domingo-Ferrer, V. Torra, A quantitative comparison of disclosure methods for microdata, in P. Doyle, J. I. Lane, J. J. M. Theeuwes, L. V. Zayatz (Eds), Confidentiality, Disclosure and Data Access: Theory and Practical Applications for Statistical Agencies, (ISBN:0-444-50761-2, North-Holland, 2001), 111-133. (here)
Graphs (data protection and analysis):
- V. Torra, Y. Narukawa, On network analysis using non-additive integrals: extending the game-theoretic network centrality, Soft Computing 23:7 (2019) 2321-2329. (here)
- V. Torra, A. Jonsson, G. Navarro-Arribas, J. Salas, Synthetic generation of spatial graphs, Int. J. of Intel. Systems 33:12 (2018) 2364-2378. (here)
Information fusion / aggregation:
- V. Torra, Y. Narukawa, Numerical integration for the Choquet integral, Information Fusion 31 (2016) 137-145. (here)
- D. Abril, V. Torra, G. Navarro-Arribas, Supervised learning using a symmetric bilinear form for record linkage, Information Fusion 26 (2015) 144-153. (here)
- V. Torra, Y. Narukawa, M. Sugeno, On the f-divergence for non-additive measures. Fuzzy Sets and Systems 292 (2016) 364-379. (here)
- Y. Narukawa, V. Torra, Fuzzy measure and probability distributions: distorted probabilities, IEEE Trans. on Fuzzy Systems, 13:5 (2005) 617 - 629.
- V. Torra, The Weighted OWA operator, Intl. J. of Intel. Syst., 12 (1997) 153-166. (here)
Information retrieval and clustering:
- V. Torra, S. Miyamoto, S. Lanau, Exploration of textual databases using a fuzzy hierarchical clustering algorithm in the GAMBAL system, Information Processing and Management, 41:3 (2005) 587-598.
- V. Torra, K. Stokes, A formalization of record linkage and its application to data protection, Int. J. of Uncertainty, Fuzziness and Knowledge-Based Systems 20:6 (2012) 907-919. (here)
- V. Torra, A review on the construction of hierarchical fuzzy systems, Int. J. of Intelligent Systems, 17:5 (2002) 531-543.
|Other||Information on projects, research stays, teaching activities, etc. :|
Last modified: 09 : 43; August 13, 2022.