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EAPLS distinguished paper at FASE ’25
Our upcoming International Conference on Fundamental Approaches to Software Engineering (FASE ’25) paper, entitled “Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs to Graph Execution,” has been selected as an European Association for Programming Languages and Systems (EAPLS) distinguished paper!
(more…)Multiple fully-funded Ph.D. student positions in combating technical debt in Machine Learning (ML) systems in New York City
I am currently seeking multiple fully-funded Ph.D. students interested in programming languages and software engineering research for an NSF-funded project on combating technical debt in Machine Learning (ML) systems. The project—based in the heart of New York City—focuses on facilitating the long-lived evolution of ML systems through automated refactoring.
Potential research topics explored during the project may include (static/dynamic) program and data analysis and transformation, empirical software engineering, natural language processing (NLP), and Large Language Models (LLMs). 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 and 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. Students wishing to start earlier should speak with the PI.
(more…)Invited to GPCE ’23 PC
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…)Talk at NEPLS at Harvard University
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!
Invited to GPCE ’22 PC
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…)Invited to IEEE SCAM ’21 PC
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…)Invited to GPCE ’21 PC
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…)New student Manal joins the team
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!
