Jie Zhang

AI + SE Seminar Series (December 13, 2024. 10 am -11 pm EST).

Mutation for Assessing and Improving AI Systems

Traditional Mutation Testing in software testing applies a fixed set of mutation operators to generate mutants for the purpose of test assessment. However, the power of mutants extends significantly beyond test evaluation. In this talk, I will share my experiences in exploring the power the mutants in testing and improving AI systems, such as using mutations for improving machine translators, validating ML classifiers, as well as benchmarking and mitigating LLM bias and hallucinations.

Bio

Dr. Jie M. Zhang is a lecturer (assistant professor) at King’s College London. Before joining King’s she was a Research Fellow at University College London and a research consultant for Meta. She got her PHD degree at Peking University in 2018 with an outstanding graduation award. Her main research interests are AI and software trustworthiness and LLMs4Code. She is a steering committee member of IEEE ICST and ACM AIware. She is a Program co-chair of AIware 2024, Internetware 2024, ASE 2023 NIER track, SANER 2023 Journal-First Track, PRDC 2023 Fast Abstract Track, SBST 2021, Mutation 2021&2020, and ASE 2019 Student Research Competition. Over the last three years, she has been invited to give over 20 talks at conferences, universities, and IT companies, including five keynote talks. She has been selected as the top-fifteen 2023 Global Chinese Female Young Scholars in interdisciplinary AI. Her research on machine learning testing has won the 2022 Transactions on Software Engineering Best Paper award.

For more details, please visit: https://www.kcl.ac.uk/people/jie-zhang

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