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Best paper award nomination at AISafety

I am happy to announce that our paper entitled, “ReLESS: A framework for assessing safety in Deep Learning systems,” has been nominated for a best paper award at AI Safety ’24! Congrats to Nan and Anita. It’s Nan’s first workshop paper!

Paper on reliably refactoring Deep Learning systems accepted at AISafety ’24

Our paper on reliability refactoring Deep Learning systems has been accepted to the 2024 AISafety workshop at the International Joint Conference on Artificial Intelligence (IJCAI ’24). Congratulations to Nan and Anita!

Preprint of ASE ’23 DL refactoring paper now available

A preprint of our ASE ’23 paper on refactoring imperative Deep Learning programs to graphs is now available.

Paper on refactoring imperative Deep Learning programs to graphs accepted at ASE ’23 NIER

Our paper entitled, “Towards Safe Automated Refactoring of Imperative Deep Learning Programs to Graph Execution” has been accepted to the New Ideas and Emerging Results (NIER) track at the IEEE/ACM 2023 International Conference on Automated Software Engineering (ASE)! Out of 70 papers, 25 were accepted, amounting to a 35.7% acceptance rate. The conference will take place later this year in Kirchberg, Luxembourg.

Congratulations to Tatiana, Mehdi, Nan, and Anita, and thank you for all of your hard work!

Paper on hybridization challenges in imperative Deep Learning programs accepted at MSR ’22

Our paper entitled, “Challenges in migrating imperative Deep Learning programs to graph execution: An empirical study,” has been accepted to the main technical research track at the IEEE/ACM SIGSOFT 2022 International Conference on Mining Software Repositories (MSR)! Out of 138 papers, 45 were accepted, amounting to a 32.6% acceptance rate. The conference will take place later this year in Pittsburgh and is co-located with ICSE 2022.

A special congratulations to Tatiana for publishing her first full conference paper as first-author in the second year of her Ph.D. studies! Also congrats to Mehdi and Anita, and thank you for all of your hard work!

Video of ICSE ’21 talk now available

A video of our ICSE 2021 talk on “An Empirical Study of Refactorings and Technical Debt in Machine Learning Systems” is now available!

Preprint of ICSE ’21 ML systems study paper now available

A preprint of our ICSE ’21 paper on studying refactoring and technical debt in Machine Learning systems is now available.

Paper on refactorings and technical debt in Machine Learning systems accepted at ICSE 2021

Our paper entitled, “An empirical study of refactorings and technical debt in Machine Learning systems,” has been accepted to the main technical research track at the 2021 International Conference on Software Engineering (ICSE)! Out of 602 papers, 138 were accepted, amounting to a 23% acceptance rate. Congrats to Yiming, Mehdi, Rhia, Ajani, and Anita, and thank you for all of your hard work!