Claire Schlesinger

Graduate Research Assistant At Geometric Learning Lab

Boston, Massachusetts, United States
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Summary

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Senior
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Top School
Claire Schlesinger is a machine learning-focused software engineer and graduate research assistant at Northeastern University with eight years of research and engineering experience across graph neural networks, robotics, and LLM-driven code generation. She has contributed to multi-institutional projects—publishing work cited over 1,000 times—that apply steerable equivariant networks and information-theoretic methods to materials discovery, fluid simulation, and crystal property prediction. Proficient in Python, Java, and TypeScript, she routinely builds experiments in TensorFlow and PyTorch and has extended evaluation tooling for code-generating models (including work on MultiPL-E and language-model metrics). Her work blends theoretical tools like spherical harmonic tensor decomposition with practical systems engineering—e.g., robot recovery-code generation and deployable ML APIs—revealing a knack for turning mathematical insight into robust, reusable software. Based in Boston and pursuing a PhD in Computer Science, she combines deep academic rigor with hands-on implementation across research labs and industry internships.
code8 years of coding experience
bookHigh School Diploma General Studies, High School Diploma General Studies at St. Stephen's Episcopal School
bookDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Northeastern University
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Stackoverflow

Stats
33reputation
821reached
2answers
2questions
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Github Skills (31)

python10
machine-learning10
deep-learning10
data-science9
tensorflow9
neural-network9
refactoring8
documentation8
deep-neural-networks8
ml8
evaluation8
benchmark7
benchmarking7
code-generation7
nlp7

Programming languages (4)

C++JavaScriptJupyter NotebookPython

Github contributions (5)

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Contributions:27 commits, 73 pushes, 6 branches in 7 months
esslushy/MultiPL-E

Nov 2022 - Jun 2023

A multi-programming language benchmark for evaluating the performance of large language model of code.
Contributions:13 PRs, 164 pushes, 13 branches in 6 months
language-modelbenchmarkingevaluationbenchmarkperformance
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