From e6e55cf06b6de1bee5fad7a8e5e421e8c58c3032 Mon Sep 17 00:00:00 2001 From: Renzo DEGIOVANNI Date: Wed, 22 May 2024 18:53:21 +0200 Subject: [PATCH] rpogram and keynote included --- speakers/_posts/2021-04-13-speaker-01.markdown | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/speakers/_posts/2021-04-13-speaker-01.markdown b/speakers/_posts/2021-04-13-speaker-01.markdown index 846693b..04500af 100644 --- a/speakers/_posts/2021-04-13-speaker-01.markdown +++ b/speakers/_posts/2021-04-13-speaker-01.markdown @@ -10,9 +10,9 @@ thumbnail: jie.jpg alt: Jie M. Zhang website: topic: > - Mutation for AI and with AI. + Mutation for AI and with AI. abstract: > - Traditional Mutation Testing applies a fixed set of mutation operators to generate mutants for the purpose of test assessment. However, the potential of mutants extends significantly beyond mere test evaluation. In this talk, I will share my experiences in exploring the power the mutants in testing and improving AI trustworthiness (Mutation for AI) in various AI systems, as well as a recent practice that leverages large language models for more powerful mutants (AI for Mutation). + Traditional Mutation Testing applies a fixed set of mutation operators to generate mutants for the purpose of test assessment. However, the potential of mutants extends significantly beyond mere test evaluation. In this talk, I will share my experiences in exploring the power the mutants in testing and improving AI trustworthiness (Mutation for AI) in various AI systems, as well as a recent practice that leverages large language models for more powerful mutants (AI for Mutation). bio: > Dr. Jie M. Zhang is a lecturer (assistant professor) of computer science at Kings College London, UK. Before joining Kings she was a Research Fellow at University College London and a research consultant for Meta. @@ -22,5 +22,5 @@ bio: > Over the last three years, she has been invited to give over 20 talks at conferences, universities, and IT companies, including four keynote talks. She has also been invited as a panelist for several seminars on large language models. - She has been selected as the top-fifteen 2023 Global Chinese Female Young Scholars in interdisciplinary AI. Her research has won the 2022 Transactions on Software Engineering Best Paper award and the ICLR 2021 spotlight paper award. + She has been selected as the top-fifteen 2023 Global Chinese Female Young Scholars in interdisciplinary AI. Her research has won the 2022 Transactions on Software Engineering Best Paper award and the ICLR 2021 spotlight paper award. --- \ No newline at end of file