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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!
I am excited to announce that I have received $1,500 from the Amazon Web Services (AWS) Cloud Credits for Research Program. (more…)
I am pleased to announce that I have recently received a PSC-CUNY Enhanced Research Award for a project entitled, “Analyses and Automated Refactorings for Imperative Programs that Use Functional Features.” The award amount is $12,000 and will help support students and travel. The award program is an internal funding mechanism to help promote research at CUNY. A brief abstract of the proposal is listed below:
Imperative programming uses statements to alter a program’s state, whereas functional programming avoids mutating existing data. With the recent popularity rise of functional programming, imperative languages are increasingly incorporating new functional features, enabling developers not previously familiar with functional programming to enjoy many of its benefits. Despite the advantages, however, issues arise from the interplay between the two paradigms, particular regarding involving MapReduce-style operations. This project will address these problems by formulating a theoretical foundation for the analysis and refactoring of hybrid functional/imperative programs and subsequently used to identify code that may safely be refactored for performance gains. Based on typestate analysis, it will determine when it is advantageous and safe to run hybrid code in parallel via a novel ordering inference approach that the PI will introduce. This work will advance the state-of-the-art in program analysis and automated refactoring for this mixed paradigm.
I am excited to announce that I have received a grant in the amount of $800 from the Amazon Web Services (AWS) Cloud Credits for Research Program as the sole investigator of a project entitled, “Analyses and Automated Refactorings for Imperative Programs that Use Functional Features.”
I am pleased to announce that I have received a grant from Women in Technology and Entrepreneurship in New York (WiTNY) as co-principal investigator, along with Dr. Saptarshi Debroy, for the project entitled “Project Khaleesi–Mentoring Tomorrow’s Cybersecurity Queen of Dragons.” The grant amount, backed by the Verizon Foundation, is $125,000 US. The project will aim to promote cybersecurity and secure software engineering education and research to women students entering CUNY as freshmen with an interest in STEM. WiTNY is an initiative to facilitate, encourage, and enable increased participation of women in technology fields, both as entrepreneurs and academics, in New York.
I am pleased to announce that I have recently received a PSC-CUNY Research Award (Traditional A) for research in software analysis and transformation.
I am pleased to announce that I have been awarded a PSC-CUNY Research Award (Traditional A) for research in software refactoring.