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Program Committee (PC) member for ICSME ’26 RENE
I am honored to be invited to serve on the Program Committee (PC) for the IEEE International Conference on Software Maintenance and Evolution (ICSME ’26) Replication and Negative Results (RENE) track!
Continue Reading →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. Additional information may be found on the PI’s web page.
Interested prospective students should apply to the City University of New York (CUNY) Graduate Center (GC) Ph.D. program in Computer Science (deadline January 15; please list “Raffi Khatchadourian” as a potential faculty mentor on your application). Prospective students may inquire with the PI by completing the below form. Prospective students wishing to start earlier should also speak with the PI.
Continue Reading →Program Committee (PC) member for ICSME ’26 registered reports
I am honored to be invited to serve on the Program Committee (PC) for the IEEE International Conference on Software Maintenance and Evolution (ICSME ’26) Registered Reports!
Continue Reading →Ad hoc reviewer for ACM Transactions on Software Engineering and Methodology (TOSEM)
Honored to be an ad hoc reviewer of the ACM Transactions on Software Engineering and Methodology (TOSEM) journal.
Received EAPLS distinguished paper award 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,” with Tatiana Castro Vélez, Mehdi Beherdezeh, Nan Jia, and Anita Raja, has been selected as an European Association for Programming Languages and Systems (EAPLS) distinguished paper!
Continue Reading →Program Committee (PC) member for ICSME ’23 doctoral symposium
I am honored to be invited to serve on the Program Committee (PC) for the IEEE International Conference on Software Maintenance and Evolution (ICSME ’23) Doctoral Symposium! The conference will be held in Bogotá, Colombia, from October 1st – 6th, 2023. The Doctoral Symposium track provides an excellent opportunity for Ph.D. students to present and receive feedback on their research work. Please consider submitting! Paper submissions are due July 6, 2023.
Alexi Turcotte from Northeastern visits CUNY
Alexi Turcotte (website) from Northeastern University visited CUNY last week and gave a talk on asynchronous JavaScript at our graduate student event at the CUNY Graduate center. Alexi is a 5th year Ph.D. candidate at Northeastern University. Frank Tip and Jan Vitek advise him; with Frank, he works on optimizing asynchronous JavaScript programs; with Jan, he works on fuzzing and type system design for the R programming language. He is interested in anything related to dynamic and data science languages.
The talk, entitled “Detecting and Repairing Anti-Patterns in Asynchronous JavaScript,” was the keynote that kicked off a series of lightning talks by other graduate students. An abstract and photos from the event may be found below. Thank you, Alexi, for visiting CUNY!
Continue Reading →Reviewer for Empirical Software Engineering (EMSE)
I am pleased to announce that I have been asked to review for the Empirical Software Engineering (EMSE) international journal!
Continue Reading →Highlights of “Challenges in Migrating Imperative Deep Learning Programs to Graph Execution: An Empirical Study”
In this blog post, we summarize, using code examples, our recent empirical study on challenges in migrating imperative Deep Learning programs to graph execution.
Continue Reading →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.
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