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Santiago Escobar
Universitat Politècnica de València
Valencia, Spain

Santiago Escobar is an associate professor at the Universitat Politècnica de València (UPV) and also holds a PhD in computer science from there. He has been a visiting scholar at the University of Illinois at Urbana-Champaign (UIUC) for more than ten years.

His research interests include programming languages, formal methods, security, verification, model checking, rewriting, narrowing, and evaluation strategies. He has worked on many multi-paradigm declarative languages, including Prolog, Haskell, Curry, and Maude. He is especially interested in the integration of functional and logic programming, as well as symbolic computation. His works on narrowing have become crucial for narrowing-based applications such as equational unification, model checking, protocol analysis, partial evaluation, debugging, and several other program analysis techniques.

In the security area, and in collaboration with Catherine Meadows from the US Naval Research Laboratory and Jose Meseguer from UIUC, he helped develop the Maude-NPA cryptographic protocol.

In the modeling and verification areas, he is a member of the Maude development team—Maude is a high-performance logical framework based on term rewriting that is used as a declarative programming language, an executable formal specification language, and a formal verification system.

Escobar’s publications cover formal methods, programming languages, verification, and protocol analysis. He has given invited talks at different conferences and schools, has served on several program committees and PhD committees, and has been program chair of several workshops on specialized areas. He also serves as a reviewer for several journals.

He has been a reviewer for Computing Reviews since 2017.


Computer security and the Internet
van Oorschot P.,  Springer International Publishing, New York, NY, 2020. 387 pp. Type: Book (978-3-030336-48-6), Reviews: (1 of 2)

Security is a hot, yet tough, topic these days. Computer security, in a broad sense, spans several interdisciplinary areas. It is sometimes difficult to identify good literature, both to grasp the essential ideas and to be able to teach them. This...


Model selection and error estimation in a nutshell
Oneto L.,  Springer International Publishing, New York, NY, 2020. 132 pp. Type: Book (978-3-030243-58-6)

The “learning” in machine learning involves the acquisition of a model that reflects the behavior or the functionality behind some dataset. Since there are so many techniques (called classifiers) to process data and extract some behavi...


Symbolic checking of fuzzy CTL on fuzzy program graph
Ebrahimi M., Sotudeh G., Movaghar A.  Acta Informatica 56(1): 1-33, 2019. Type: Article

This paper presents a new temporal logic for fuzzy logic systems, fuzzy computation tree logic (FzCTL), based on previous work on Kripke structures for fuzzy logic systems, that is, fuzzy program graph (FzPG) [1]. The motivation for providing a ne...


A primer on quantum computing
de Lima Marquezino F., Portugal R., Lavor C.,  Springer International Publishing, New York, NY, 2019. 109 pp. Type: Book (978-3-030190-65-1)

This simple yet practical first contact with quantum computing is well written, easy to read, and well structured. The authors state from the very beginning that they cannot cover all relevant topics of quantum computing, so instead they explain i...


 A domain theory for statistical probabilistic programming
Vákár M., Kammar O., Staton S.  Proceedings of the ACM on Programming Languages 3(POPL): 1-29, 2019. Type: Article

On the one hand, a statistical programming language is similar to a traditional programming language, but with libraries providing statistical functions. Examples are Mathematica, MATLAB, and the omnipresent R. On the other hand, probabilistic pro...


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