Yinghua Li (李英华)   Doctoral Researcher University of Luxembourg Email: yinghua.li@uni.lu; yinghuali@acm.org Github: yinghuali [LinkedIn][Twitter][ORCID][Google Scholar]

Biography

I am a Doctoral Researcher at University of Luxembourg, supervised by Prof. Tegawendé F. Bissyandé (ERC Fellow), Prof. Jacques Klein and Prof. Lei Ma. Before that, I received my Master degree from Chongqing University, under the supervision of Prof. Jun Zeng. I have worked as a machine learning engineer in the industry for several years.

Research Interests

• Machine Learning Testing
• AI4SE
• Data Mining

Selected Publications

(# Co-First Author, * Corresponding Author)

• Yinghua Li, Xueqi Dang*, Weiguo Pian, Andrew Habib, Jacques Klein, Tegawendé F. Bissyandé.
  Test Input Prioritization for Graph Neural Networks.
  Accepted in IEEE Transactions on Software Engineering, 2024. (TSE, CCF A)
• Yinghua Li, Xueqi Dang*, Lei Ma, Jacques Klein, Yves Le Traon, Tegawendé F. Bissyandé.
  Test Input Prioritization for 3D Point Clouds.
  Accepted in ACM Transactions on Software Engineering and Methodology, 2024. (TOSEM, CCF A)
• Xueqi Dang#, Yinghua Li *#, Mike Papadakis, Jacques Klein, Tegawendé F. Bissyandé, Yves Le Traon.
  Test input prioritization for Machine Learning Classifiers.
  Accepted in IEEE Transactions on Software Engineering, 2024. (TSE, CCF A)
• Xueqi Dang, Yinghua Li*, Mike Papadakis, Jacques Klein, Tegawendé F. Bissyandé, Yves Le Traon.
  GraphPrior: Mutation-based Test Input Prioritization for Graph Neural Networks.
  Accepted in ACM Transactions on Software Engineering and Methodology, 2023. (TOSEM, CCF A)
• Haoye Tian, Yinghua Li, Weiguo Pian, Abdoul Kader Kaboré, Kui Liu*, Andrew Habib, Jacques Klein, Tegawendé F. Bissyandé.
  Predicting Patch Correctness Based on the Similarity of Failing Test Cases.
  Accepted in ACM Transactions on Software Engineering and Methodology, 2022. (TOSEM, CCF A)
• Haoye Tian, Kui Liu*, Yinghua Li, Abdoul Kader Kaboré, Anil Koyuncu, Andrew Habib, Li Li, Junhao Wen, Jacques Klein, Tegawendé F. Bissyandé.
  The Best of Both Worlds: Combining Learned Embeddings with Engineered Features for Accurate Prediction of Correct Patches.
  Accepted in ACM Transactions on Software Engineering and Methodology, 2022. (TOSEM, CCF A)

Honors & Awards

• 2018: National Scholarship (The award rate is 0.2%)
• 2018: IBM China Outstanding Student Scholarship (A total of 50 students are selected in China)

Services

Journal Referee

• 2024 – Now: IEEE Transactions on Industrial Informatics (JCR Q1, SCI-1)
• 2023 – Now: Empirical Software Engineering (JCR Q1, SCI-2)
• 2023 – Now: Soft Computing (JCR Q2)

External Reviewer

• ISSTA 2023, 2024
• FSE 2022
• ASE 2022
• SANER 2022

Work Experience

• BOSS Zhipin, Beijing, October 2020 - November 2020, Machine Learning Engineer.
• Hikvision, Hangzhou, July 2019 - October 2020, Machine Learning Engineer.
• IBM, Beijing, April 2018 - August 2018, Machine Learning Engineer (intern).
• Didi Chuxing, Beijing, November 2017 - April 2018, Machine Learning Engineer (intern).
• Weibo, Beijing, August 2017 - November 2017, Deep Learning Engineer (intern).

© 2024 Yinghua Li