Vicenç Torra

Vicenç Torra
Professor, Umeå University, Sweden
Personal web page here

Address: Umeå University
Department of Computing Science
MIT-Building
901 87 Umeå
Sweden
Tel: +46 xxxxxxxxx
Email:
vtorra (at) cs (dot) umu (dot) se
tot (at) natana (dot) cat

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). Slides and code related to the book here
Positions:	Open postdoc positions -- a position is planned in 2024 (PrivAcy-AWare traNSparent deCIsions research group, Dept. Computing Science, Umeå University, Sweden). Information will be posted at University web site and I usually also post it at LinkedIn. Links: Link to my papers in MathSciNet for "Measure and integration" PrivAcy-AWare traNSparent deCIsions group Department of Computing Science, Umeå University Research will be supported by our WASP project. Wallenberg AI, Autonomous Systems and Software Program (WASP), Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. Umeå University Research directions on data privacy; Research on modeling decisions and aggregation; Lecture notes on AI; Scala book.
Code	Code of some of my papers here
Reviews	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.
Project:	Vetenskapsrådet -- Swedish Research Council-- project: Privacy-aware secure explainable data-driven models in federated learning (VR 2023-05531, period 2024-2028). Call: VR Project grant for research into cyber and information security.
Project:	WASP NET project: CyberSecIT: Security and privacy of software-driven IoT systems. (WASP-NEST, 2022-2027).
Project:	Vetenskapsrådet -- Swedish Research Council-- project: Privacy for complex data (VR 2022-04645, period 2023-2027).
Project:	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).
Project:	Kempe project: Identification and analysis of non-additive measures (JCSMK22-0147, 2023-2024). Topics of interest: distances and derivatives for measures, measure identification. Some papers in this area: SS Negi, V Torra (2022) Choquet integral in time scales. Chaos, Solitrons and Fractals SS Negi, V Torra (2022) Existence and Uniqueness of solutions of differential equations w.r.t. non-additive measures. Math Methods in the Applied Sciences V Torra, Y Narukawa, M Sugeno (2020) On the f-divergence for discrete non-additive measures. Inf. Sci. V Torra (2017) Entropy for non-additive measures in continuous domains. Fuzzy Sets Syst. V Torra (2022) The transport problem for non-additive measures, European Journal of Operational Research 311:2 (2023) 679-689.
Plenary:	Plenary talks at INFUS 2024 (Turkey), and FSTA 2024 (Slovak Republic)
Edited book:	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.
Address:	MIT-huset, Umeå universitet, Umeå universitet, 901 87 Umeå, Sweden.
Email:	Note that my old email address vt*ra@iia.cic.* does not work any more.
Editor:	Transactions on Data Privacy Indexed at DBLP, ACM Digital Library, MathSciNet, DOAJ, Elsevier (Scopus, EI)
6 Recent papers:	- Big data privacy and anonymization: K. S. Adewole, V. Torra (2022) DFTMicroagg: a dual-level anonymization algorithm for smart grid data. Int. J. Inf. Sec. 21 1299-1321. (download) - Privacy-preserving ML model selection: 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: V. Torra, Towards integrally private clustering: overlapping clusters for high privacy guarantees, Proc. PSD 2022. - ML, record linkage, and disclosure risk: N. Senavirathne, V. Torra (2021) Dissecting Membership Inference Risk in Machine Learning, Proc. CSS 2021: 36-54. (download) - Decision making and aggregation: J. Dujmovic, V. Torra (2021) Properties and comparison of andness-characterized aggregators, Int. J. Intell. Syst. 36 1366-1385. (download) - Non-additive measures and integrals: S. S. Negi, V. Torra (2022) Delta-Choquet integral on time scales with applications, Chaos, Solitons and Fractals 157 (2022) 111969. (download, open access)
Books:	I have written the following books (selection): Data privacy V. Torra (2022) Guide to Data Privacy: Models, Technologies, Solutions, Springer. Undergraduate course V. Torra (2020) Data protection and differential privacy (in Spanish), RBA. Translated to Italian. Popular science or introductory text V. Torra (2017) Data Privacy: Foundations, New Developments and the Big Data Challenge, Springer. Undergraduate course Artificial intelligence and computer science V. Torra (2021) Genetic algorithms (in Spanish), RBA. Translated to Italian (Gli algoritmi genetici e il futuro della diagnostica medica). Popular science or introductory text V. Torra (2016) Scala: from a functional programming perspective, Springer. Undergraduate course V. Torra (2010) From the abacus to the digital revolution (in Spanish), RBA. Translated to English, Portuguese, French, Italian, Polish, Russian. Popular science or introductory text V. Torra (2007) Fundamentals of artificial intelligence (in Catalan), UOC Press. Undergraduate course Decision making and aggregation operators V. Torra, Y. Narukawa (2007) Modeling Decisions: Information Fusion and Aggregation Operators, Springer. ( Slides and software here) Catalan translation: V. Torra, Y. Narukawa (2007) Modelització de decisions: fusió d'informació i operadors d'agregació, UAB Press Undergraduate course V. Torra (2014) The mathematics go to the ballot box (in Spanish), RBA. Translated into Russian. Popular science or introductory text Edited books (selected): A. Said, V. Torra (2019) Data Science in Practice, Springer. V. Torra, Y. Narukawa, M. Sugeno (Eds.) (2013) Non-additive measures, Springer
I am busy organizing	PC co-chair: 20th Intl. Conf on Modeling Decisions for Artificial Intelligence (MDAI 2023, Umeå, Sweden)
Selected activities	Recent invited talks: (INFUS 2022); Non-additive measures, set distances and cost functions on sets: A Fréchet-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-).
Research interests	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: Approximate reasoning: Some more specialized keywords include: fuzzy sets and systems, fuzzy measures and integrals, measure theory, decision making, belief functions. I am interested in mathematical properties of these models, and on their application. In the last years we are studying measures in time scales, and distances for measures (KL-divergences, Wasserstein). Data privacy: Keywords: disclosure risk, masking methods, record linkage, transparency and disclosure risk. I have worked on data privacy for matrices and standard databases, search logs, texts and documents, and social networks. Information fusion and integration: My research is focused on the integration of information at large, from particular aggregation operators as e.g. WOWA (Weighted OWA) and fuzzy integrals to software for database integration (e.g. record linkage). I have studied formal aspects (e.g. non-additive (fuzzy) measures, modeling capabilities, data in ordinal scales) as well as algorithms for parameter selection/determination. Applications include data privacy and decision making. Two papers at RIMS Kokyuroku: Research Institute for Mathematical Sciences in Kyoto University:1630-02, 1683-06 Clustering: I have applied clustering and fuzzy clustering to a variety of problems in data privacy (microaggregation and information loss assessment) and information retrieval. GAMBAL, a tool for information retrieval, is one of the tools developed. See: Probability distribution: I introduced a new probability distribution based on the Choquet integral. There are a significant number of problems that can be solved effectively using the Choquet integral. Applications range from computer vision to decision making. I propose this type of distributions to represent the type of data that we encounter in these problems. See: here (first definition, Information Sciences) and here (ACUTM).
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.
Papers (selected)	Links to: DBLP, MathSciNet, Scholar Google Books (monographs, selected): (see above) Papers: 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. Approximate reasoning: - 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: 12 : 09; January 17, 2024.