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Alessandra Russo

From Wikipedia, the free encyclopedia
Alessandra Russo
NationalityItalian, British
Alma materUniversity of Bari
Known forComputational Logic, Symbolic Machine Learning
Scientific career
InstitutionsImperial College London
ThesisModal Labelled Deductive Systems (1996)
Doctoral advisorDov Gabbay and Krysia Broda

Alessandra Russo is a professor in Applied Computational Logic at the Department of Computing, Imperial College London.[1]

Career

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She obtained a Laurea in Computer Science from the University of Bari in 1990 achieving a grade of 110/110 (cum laudae) before completing her PhD at Imperial College London in 1996.[2] From 1997 to 2001 she worked at Imperial as a Research Associate before being appointed a lecturer in 2001.[2] She was appointed Head of the Department of Computing, Imperial College London in 2024.

She leads the Structured and Probabilistic Intelligent Knowledge Engineering (SPIKE) research group which focuses on developing frameworks and algorithms for structured and probabilistic knowledge.[3]

Awards

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She has been awarded the prize for the best application paper at the International Conference on Logic Programming (ICLP) in 2002 and the Imperial College Rector's Award for Excellence in Teaching in 2011.[4] She is also a Fellow of the British Computer Society.[5]

Projects

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References

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  1. ^ "Home - Professor Alessandra Russo". imperial.ac.uk. Retrieved 11 May 2023.
  2. ^ a b "Alessandra Russo - CV" (PDF). Retrieved 11 May 2023.
  3. ^ "SPIKE - Structured and Probabilistic Intelligent Knowledge Engineering". Retrieved 11 May 2023.
  4. ^ "Awards & Invited Talks - Professor Alessandra Russo". Retrieved 11 May 2023.
  5. ^ "Alessandra Russo - Safe & Trusted AI". Retrieved 11 May 2023.
  6. ^ Law, Mark; Russo, Alessandra; Broda, Krysia (2014). "Inductive Learning of Answer Set Programs". Proceedings of the Fourteenth European Conference on Logics in Artificial Intelligence, 2014, Funchal, Madeira, Portugal, September 2426, 2014. Fourteenth European Conference on Logics in Artificial Intelligence. Springer, Berlin, Heidelberg. doi:10.1007/978-3-319-11558-0_22. hdl:10044/1/23794.
  7. ^ Law, Mark; Russo, Alessandra; Broda, Krysia (2016). "Iterative Learning of Answer Set Programs from Context Dependent Examples". Theory and Practice of Logic Programming, Volume 16, Special Issue 5-6: 32nd International Conference on Logic Programming. 32nd International Conference on Logic Programming. Cambridge University Press. arXiv:1608.01946. doi:10.1017/S1471068416000351.
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