Leonardo VanneschiUniversidade Nova de Lisboa, Portugal

Information Management School, Universidade Nova de Lisboa, Portugal

Featured Talk

Geometric Semantic Genetic Programming

Abstract

Bio

Education

Leonardo Vanneschi was born in Florence (Italy) on October 3rd, 1970. He took his University degree (Laurea) in Computer Science by the University of Studies of Pisa (Italy) in 1996 (110/110 summa cum Laude) and his PhD in Computer Science by the University of Lausanne (Switzerland) in 2004 (PhD thesis honoured with the Excellence Award of the Science Faculty of the University of Lausanne). He is an Associate Professor at NOVA Information Management School (NOVA IMS) of the Universidade Nova of Lisbon, Portugal.

Research Interests

His main research interests are: Machine Learning, study of Complex Systems, Data Mining, and in particular Evolutionary Computation.

Research scope

His theoretical studies on the foundations of Evolutionary Computation, as well as his applicative works, covering several fields among which Computational Biology and Image Processing, have been consistently recognized and appreciated by the international community from 2000 to nowadays. He is a member of the editorial board of two international scientific journals. He is a member of the steering committee and program committee of various international conferences. He has been the editor of several international conference proceedings and of two scientific journals special issues. In 2015 he has received an Award for Outstanding Contributions in Evolutionary Computation from a panel of internationally renowned experts. He has about 150 scientific publications, among which 11 have been honoured with international awards.

Honors and awards
  • April 2015: Award for Outstanding Contributions in Evolutionary Computation.
  • April 2014: EuroGP 2014 Best Paper Award [1].
  • April 2013: EuroGP 2013 Best Paper Award [2].
  • April 2011: EvoBIO 2011 Best Paper Award [3].
  • September 2009: ICEC 2009 Best Paper Award [4].
  • June 2007: GECCO 2007 Best Paper Award, Genetic Algorithms track [5].
  • June 2006: GECCO 2006 Best Paper Award, Biological applications track [6].
  • April 2006: EuroGP 2006 Best Paper Award [7].
  • April 2005: EuroGP 2005 Best Paper Award [8].
  • September 2002: PPSN 2002 Best Poster Award [9].
  • July 2002: GECCO 2002 Best Graduate Student Paper Award [10].
  • June 2005: Excellence Award from the Science Faculty of the University of Lausanne [11].
Publications

[1] S. Ruberto, L. Vanneschi, M. Castelli, and S. Silva, "ESAGP – A semantic GP framework based on alignment in the error space," in 17th European Conference on Genetic Programming (M. Nicolau, K. Krawiec, M. I. Heywood, M. Castelli, P. Garci-Sanchez, J. J. Merelo, V. M. R. Santos, and K. Sim, eds.), vol. 8599 of LNCS, (Granada, Spain), pp. 150–161, Springer, 23-25 Apr. 2014.

[2] L. Vanneschi, M. Castelli, L. Manzoni, and S. Silva. A new implementation of geometric semantic gp and its application to problems in pharmacokinetics. In Genetic Programming (K. Krawiec, A. Moraglio, T. Hu, A. Etaner-Uyar, and B. Hu, eds.), vol. 7831 of Lecture Notes in Computer Science, pp. 205–216, Springer Berlin Heidelberg, 2013.

[3] A. Farinaccio, L. Vanneschi, P. Provero, G. Mauri, and M. Giacobini. A new evolutionary gene regulatory network reverse engineering tool. In C. Pizzuti, et al., editors, EvoBio, volume 6623 of Lecture Notes in Computer Science, pages 13–24. Springer, 2011.

[4] L. Vanneschi and G. Cuccu. A study of genetic programming variable population size for dynamic optimization problems. In A. Rosa et al., editor, Proceedings of the 2009 International Conference on Evolutionary Computation (ICEC 2009), part of the International Joint Conference on Computational Intelligence (IJCCI 2009), 2009.

[5] R. Poli and L. Vanneschi. fitness-proportional negative slope coefficient as a hardness measure for genetic algorithms. In D. Thierens et al., editor, Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2007, volume 2, pages 1335 – 1342. ACM Press, 2007.

[6] F. Archetti, S. Lanzeni, E. Messina, and L. Vanneschi. Genetic programming for human oral bioavailability of drugs. In M. Keijzer et al., editor, Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2006, volume 1, pages 255–262. ACM Press, 2006.

[7] L. Vanneschi, S. Gustafson, and G. Mauri. Using subtree crossover distance to investigate genetic programming dynamics. In Collet, P., et al., editor, Genetic Programming, 9th European Conference, EuroGP2006, Lecture Notes in Computer Science, LNCS 3905, pages 238–249. Springer, Berlin, Heidelberg, New York, 2006.

[8] S. Gustafson and L. Vanneschi. Operator-based distance for genetic programming: Subtree crossover distance. In Keijzer, M., et al., editor, Genetic Programming, 8th European Conference, EuroGP2005, Lecture Notes in Computer Science, LNCS 3447, pages 178–189. Springer-Verlag, Heidelberg, 2005.

[9] M. Tomassini, L. Vanneschi, F. Fernández, and G. Galeano. Experimental investigation of three distributed genetic programming models. In J. J. Merelo, P. Adamidis, H. G. Beyer, J.-L. Fernández-Villacanas, and H.-P. Schwefel, editors, Parallel Problem Solving from Nature PPSN VII, volume 2439 of Lecture Notes in Computer Science, pages 641–650. Springer-Verlag, Heidelberg, 2002.

[10] L. Vanneschi and M. Tomassini. A study on fitness distance correlation and problem difficulty for genetic programming. In Alwyn Barry, editor, 2002 Genetic and Evolutionary Computation Conference, Workshop Program Proceedings, GECCO'02, pages 307–310, New York City, USA, 2002.

[11] L. Vanneschi. Theory and Practice for Efficient Genetic Programming. Ph.D. thesis, Faculty of Science, University of Lausanne, Switzerland, 2004.

More in this category: « Jian-Qiao Sun David Romero »