University of Latvia will award Honorary Doctoral degree to two distinct computer scientists:
· prof. Juris Hartmanis (born in Riga). He is a prominent computer scientist and computational theorist who received the 1993 ACM Turing Award "in recognition of their seminal paper which established the foundations for the field of computational complexity theory". At Cornell University in 1965, he was one of founders and the first chairman of its computer science department (which was one of the first computer science departments in the world).
· prof. Jozef Gruska (Czech Republic). For development of Computer Science field in Eastern Europe. He is an expert in Theoretical Informatics (Book "Foundations in computing", Thomson Learning, 730 pages, 1997) and Quantum Information Processing (Book "Quantum computing", Mcgraw Hill Book, 430 pages, 1999). Over 150 publications.
Both professors will give a short talk during the Award Ceremony.
EACTS will award two scientific awards.
2013 EATCS Presburger Award: Erik Demaine (MIT, USA)
Erik Demaine, born in 1981, has made outstanding contributions in several fields of algorithms, namely computational geometry, data structures, graph algorithms and recreational algorithms. In computational geometry and data structures he has solved or made significant progress on classic problems such as the carpenter’s rule problem, the hinged-dissection problem, the prefix-sum problem, and the dynamic optimality conjecture. In graph algorithms he used the powerful theory of graph minors to develop a suite of algorithms for approximately solving a general family of intractable problems. He also started the new field of computational origami, where his book is the leading authority in the field. His work has shown promising applications to computer graphics, sensor networks, molecular biology, programmable matter, and manufacturing and engineering.
2013 EATCS Award: Martin Dyer (University of Leeds, UK)
Martin Dyer’s scientific contributions span a wide range of topics within Theoretical Computer Science, including the following.
· Pioneering the development of linear-time algorithms for linear programming in a fixed number of dimensions.
· Developing probabilistic analysis of algorithms.
· Discovering the first polynomial-time algorithm for estimating the volume of a high-dimensional convex body.
· Introducing the elegant and useful path-coupling technique for bounding the mixing time of Markov chains.
· Discovering fast algorithms for approximate counting.
· Classifying the complexity of counting problems.