Hi, I'm Claire Schlesinger
I am an experienced undergraduate researcher specializing in machine learning, artificial intelligence, and neural networks. I have contributed to cutting-edge research at Northeastern University and the University of Texas, working on graph neural networks, robotics, and large language models (LLMs) resulting in several papers with over 1000 citations. I am proficient in Python, Java, and Typescript, and have experience with frameworks such as TensorFlow and PyTorch.
Education
Northeastern University, Boston, MA September 2021 – Present
Khoury College of Computer Sciences Expected May 2025
Candidate for a Bachelor of Science in Computer Science GPA 3.98/4.0
Computer Knowledge
Languages: Proficient With: Python, Java, C, JavaScript, TypeScript
Familiar With: ARM Assembly, Risc-V Assembly, F#, OCaml
Frameworks: Torch, Tensorflow, Sklearn, Numpy, Pandas, SciKitLearn, React.js, Node.js
Techniques: Machine Learning, NLP, LLMs, Data Processing, Data Analysis
IDEs: VSCode, Jupyter Notebook, IntelliJ Idea, Eclipse
Software/Tools: Github, Excel, Word, Vim, Docker
Professional Experience
Data Driven Renewables Research Lab | Boston, Massachusetts September 2024 – Ongoing
Undergraduate Research Assistant at Northeastern University
● Tested a variety of equivariant graph neural networks to determine their performance on predicting the cleavage energy of slab data.
● Participated in a joint research project with the geometric learning lab utilizing generative AI to produce new slab candidates with desired properties.
Autonomous Mobile Robotics Labratory | Austin, Texas May – August 2024
Undergraduate Research Assistant at University of Texas
● Utilized Code LLMs to generate recovery code for robots when they encountered an error or received new instructions to their task.
● Created a website which allowed a user to generate code and recovery code for a robot.
● Performed case studies to analyze the effectiveness of the recovery system in real world situations.
Qimin Yan Group | Boston, Massachusetts July – December 2023
Undergraduate Research Assistant at Northeastern University
● Developed graph neural networks to predict properties of various crystal structures.
● Utilized spherical harmonic decomposition to improve prediction of elastic tensors through the prediction of spherical harmonic coefficients by steerable equivariant graph neural networks.
● Developed transfer learning techniques to improve prediction of other tensorial properties of crystals.
Programming Research Lab | Boston, Massachusetts January 2023 – Ongoing
Undergraduate Research Assistant at Northeastern University
● Developed a benchmark to test Code LLMs performance on context-based tasks.
● Tested ChatGPT’s ability to write code in a variety of languages to solve HumanEval questions.
● Researched an improved method of fine tuning using a modified form of self-instruct for StarCoder.
● Worked in partnership with UT Austin robotics on a language model for conversion of human commands into robot code.
Data Initiative Research Lab | Boston, Massachusetts September – December 2022
Data Science Consultant at Northeastern University
● Identified features with InnSure Corporation that increase or decrease a company’s susceptibility to be hacked utilizing the Veris Dataset.
● Analyzed data, identified correlations, and presented findings with a team to InnSure management.
Cybersecurity and Machine Learning Project | San Antonio, Texas Summer 2019 – 2021
Machine Learning Intern at Denim Group (acquired by Coalfire)
● Constructed and maintained a Python API which handled requests to a ThreadFix instance.
● Created and optimized a classifier that could detect false positives at a 98% F1 Score.
● Built an end-to-end training pipeline for the classifier to work on any ThreadFix instance.
● Developed a website in React.js with an intuitive interface to use the classifier.