PhD student @ CMU's S3D, advised by Claire Le Goues, Vincent Hellendoorn, and Ruben Martins, where I study LLMs fine-tuned on source code and automatic program repair. I also worked at IBM Quantum, studying how quantum algorithms for graph partioning could be used to improve linear solvers. Prior to that, I was a student at Columbia University, where I worked in the ARiSE lab using machine learning to predict the efficiency of programs.
email: sophiakolak@cmu.edu cv: pdf
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Revisiting Unnaturalness for Automated Program Repair in the Era of Large Language Models |
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Evaluating Quantum Algorithms For Linear Solver Workflows |
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Patch Generation with Language Models: Feasibility and Scaling Behavior |
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It Takes a Village to Build a Robot: An Empirical Study of the ROS Ecosystem |
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Detecting Performance Patterns with Deep Learning |
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SHIRLEE: A Sharp-edge Handheld Identifier and Remover in Low-gravity Extravehicular Environments |
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Quantum Algorithms for Linear Solvers |
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Patch Generation with Large Language Models |
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Robotics Software Quality Panelist |
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ROS Developers Podcast |
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It Takes a Village to Build a Robot |
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MLG 10615: Art & Machine Learning Carnegie Mellon University, Spring 2023 |
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COMS W3261: Computer Science Theory Columbia University, Fall 2019-Spring 2021 |