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Fully-funded Ph.D. student position(s) in analysis and transformations of Deep Learning programs in New York City
I am currently seeking (potentially multiple, fully-funded) Ph.D. students interested in programming languages and software engineering research for an NSF-funded project on analysis and transformations for (imperative) Deep Learning (DL) programs. The project—based in the heart of New York City—focuses on enhancing the robustness, increasing run-time performance, and facilitating the long-lived evolution of DL systems, particularly, large, industrial DL systems. For more information on the project, please see the project announcement.
Potential research topics explored during the project may include (static/dynamic) program analysis and transformation (e.g., automated refactoring) and empirical software engineering. Successful candidates will be expected to work on projects that generally yield open-source developer tool research prototypes, plug-ins to popular IDEs, build systems, or static analyzers. Applicants may find additional information on the PI’s web page. They should also apply to the City University of New York (CUNY) Graduate Center (GC) Ph.D. program in Computer Science (deadline January 15) following a discussion with the PI.
Please see below for additional details on applying. Again, the Ph.D. program deadline is January 15.
(more…)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!
“Migrating Imperative Deep Learning Programs to Graph Execution” guest lecture on YouTube
Thanks to Stevens Institute of Technology for posting my guest lecture on imperative Deep Learning program execution to YouTube!
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!
Slides for SANER ’22 talk now available
Slides for our SANER 2022 talk on “Automated Evolution of Feature Logging Statement Levels Using Git Histories and Degree of Interest” are now available!
Video of SANER ’22 talk now available
A video of our IEEE SANER 2022 journal-first track talk on “Automated Evolution of Feature Logging Statement Levels Using Git Histories and Degree of Interest” is now available!
Tool demo paper on feature logging accepted at ICSE ’22
Our paper entitled, “A tool for rejuvenating feature logging levels via Git histories and degree of interest,” has been accepted to the formal tool demonstration track at the 2022 International Conference on Software Engineering (ICSE)! Out of 98 papers, 49 were accepted, amounting to a 50% acceptance rate. Congrats to Yiming, Allan, and Mehdi!
Tatiana selected to 2022 CRA-WP Grad Cohort for Women
Congratulations to Tatiana for being selected to participate in the 2022 CRA-WP Grad Cohort for Women! The NSF-funded workshop, which “aims to increase the ranks of senior women in computing-related studies and research by building and mentoring nationwide communities of women through their graduate studies,” will take place later this year in New Orleans. More information can be found on the event page. Congrats, Tatiana!
