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I have been invited to serve as a program committee (PC) member for the 2023 ACM SIGPLAN International Conference on Generative Programming: Concepts & Experiences (GPCE).(more…)
I gave a talk at the New England Programming Languages and Systems (NEPLS) symposium at Harvard University earlier this month.
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!
I have been invited to serve as a program committee (PC) member for the 2022 ACM SIGPLAN International Conference on Generative Programming: Concepts & Experiences (GPCE).(more…)
I have been invited to serve on the research track program committee (PC) of the 2021 IEEE International Working Conference on Source Code Analysis and Manipulation (IEEE SCAM), colocated with ICSME 2021.(more…)
I have been invited to serve as a program committee (PC) member for the 2021 ACM SIGPLAN International Conference on Generative Programming: Concepts & Experiences (GPCE).(more…)
We have a new master’s student, Manal Zneit, joining us! Manal has a background in Mathematics, and she is now pursuing a degree in Computer Science. Manal is also an adjunct lecturer at CUNY Lehman College, where she teaches various introductory programming classes. She will be working on research at the intersection of Software Engineering, Programming Languages, and Data Science. Welcome, Manal!
We are honored to receive the 2020 European Association for Programming Languages and Systems (EAPLS) best paper award at the 2020 International Conference on Fundamental Approaches to Software Engineering (FASE ’20) for our paper entitled, “An Empirical Study on the Use and Misuse of Java 8 Streams” with Yiming Tang, Mehdi Beherdezeh, and Baishakhi Ray. (more…)
Graduate Research Assistant Position in Programming Languages and Software Engineering
I am currently seeking a graduate student interested in programming languages and software engineering research to commence at the Fall 2020 semester. While the topic is open, potential research topics may include (static/dynamic) program analysis and/or transformation (e.g., refactoring) with a focus on helping to maintain and/or evolve large and complex software efficiently, effectively, and securely. Potential topics may also include automated bug finding approaches and empirical studies. The successful candidate will be expected to work on projects that normally yield open source developer tool research prototypes, typically plug-ins to popular IDEs, build systems, or static analyzers. More information can be found on the main supervisor’s web page.
Of particular interest are students interested in applying to the City University of New York – CUNY’s Graduate Center Ph.D. program in Computer Science concurrently with the research assistantship.
Please see below for additional details on applying. (more…)