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Received three-year NSF research grant on imperative Deep Learning program robustness and evolution as PI
I am pleased to announce that I, along with co-PI Anita Raja, have received a three-year standard research grant from the National Science Foundation (NSF) Software & Hardware Foundations (SHF) program as principal investigator (PI) for a project entitled “Practical Analyses and Safe Transformations for Imperative Deep Learning Programs.” The total grant amount is $600K.
The project will facilitate the robustness and automated evolution and maintenance of large, industrial Deep Learning (DL) software systems that use imperative style programming. More information may be found on NSF’s website; stay tuned for more details and funded research opportunities!
We are honored to receive a best paper award at the 2018 IEEE International Working Conference on Source Code Analysis and Transformation (SCAM ’18) for our paper entitled, “A Tool for Optimizing Java 8 Stream Software via Automated Refactoring” with Yiming Tang, Mehdi Beherdezeh, and Syed Ahmed. (more…)
I am currently seeking the assistance of a developer(s) with WALA expertise to help fix several WALA bugs that would greatly improve the progress of our current research project. Compensation is negotiable. There is also a possibility to participate in the research project once the bugs have been fixed. We will also encourage the engineer to integrate the bug fixes into the main WALA branch. Please, direct inquiries to the PI, Raffi Khatchadourian.
Slides for our talk on default method refactoring at ICSE 2017 are now available on slideshare. (more…)