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Tag Archives: 2022
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Highlights of “Challenges in Migrating Imperative Deep Learning Programs to Graph Execution: An Empirical Study”
We summarize, using code examples, our recent empirical study on challenges in migrating imperative Deep Learning programs to graph execution. Continue reading
NYU GSTEM students visit during the summer of 2022
Medha Belwadi and Pranavi Gollanapalli will be joining our research group this summer through the NYU GSTEM program. Continue reading
Program Committee (PC) member for ICSME ’22 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 ’22) Doctoral Symposium! Please consider submitting! Full paper submissions are due July 8, 2022.
Program Committee (PC) member for ESEC/FSE ’22 demonstrations
I am excited and honored to serve as a program committee member for the ESEC/FSE 2022 formal tool demonstrations track. Please consider submitting! The deadline is June 20.
Student mentor at ICSE ’22
Excited and honored to be listed as one of the mentors for the upcoming ICSE ’22 Student Mentoring Workshop (SMeW)!
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" was accepted at MSR 2022. Continue reading
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!
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).
