Shibbir Ahmed is a Ph.D. candidate in the Department of Computer Science at Iowa State University (ISU). He is currently working as a research assistant in the Laboratory for Software Design under the supervision of Professor Dr. Hridesh Rajan. Shibbir's research focuses on improving state-of-the-art research in the aspect of Artificial Intelligence, Data Science, and Software Engineering, analyzing data science software faults, and designing novel techniques to improve the reliability and trustworthiness of Artificial Intelligence and Data Science software in real life.
RECENT PEER-REVIEWED CONFERENCE PAPERS
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Shibbir Ahmed , Hongyang Gao, and Hridesh Rajan, "Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment," In Proceedings of the 46th International Conference on Software Engineering, April, 2024, (ICSE 2024), Lisbon, Portugal.
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Shibbir Ahmed , Sayem Mohammad Imtiaz, Breno Dantas Cruz, Samantha Syeda Khairunnesa, and Hridesh Rajan, "Design by Contract for Deep Learning APIs," In Proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, December, 2023, (ESEC/FSE 2023), San Francisco, CA, USA.
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RECENT PEER-REVIEWED JOURNAL PAPERS
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Samantha Syeda Khairunnesa, Shibbir Ahmed , Sayem Mohammad Imtiaz, Hridesh Rajan, and Gary Leavens "What Contracts Do ML APIs Need? An Empirical Study," Empirical Software Engineering Journal, (EMSE 2023), 28(6), pp.142. Springer, 2023.
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Shibbir Ahmed, Md Johirul Islam, and Hridesh Rajan, "Semantics and Anomaly Preserving Sampling Strategy for Large-Scale Time Series Data," ACM/IMS Transactions on Data Science (TDS 2022), , Volume 2 issue 4, Article 41, pp. 1-25, ACM, 2022.
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RECENT PEER-REVIEWED WORKSHOP PAPERS
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Shibbir Ahmed "Towards Deep Learning Specification," In Proceedings of the ACM SIGPLAN conference on Systems, Programming, Languages, and Applications: Software for Humanity (SPLASH), Doctoral Symposium, ACM, October, 2021.
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