Welcome to my webpage! My name is Kyla.
I am from a town a little ways outside of Philadelphia and left in 2019 to get my B.S. in Chemical Engineering at Tufts University's School of Engineering. There, I took introductory computer science courses where I first fell in love with computer science, and eventually added it as a second major. During this time, I researched computational biology under Lenore Cowen as a Laidlaw Scholar during the summer of my sophomore year and co-authored my first paper. Later, I joined my advisor, Jeffrey Foster, in researching path-sensitive programming languages and type-inferencing for dynamic programming languages.
In 2023, I graduated from Tufts and enrolled in my current M.S./Ph.D. Computer Science program at the University of Massachusetts Amherst under my advisor, Emery Berger. Here, I conduct systems research that primarily focuses on the intersection of software engineering and programming languages, in particular how LLMs can be applied to programming challenges. Some of my projects include ChatDBG, an AI-powered debugging assistant, and Pythoness, a program synthesis tool for Python.
When I have it, I enjoy spending my free time ballroom dancing, rock climbing, and cooking with my partner.

ChatDBG / UMass Amherst

Sep 2023 - Current

At UMass Amherst's PLASMA Lab, I work with Emery Berger to investigate the use of LLMs such as ChatGPT as debugging tools. ChatDBG and CWhy are two such projects, and my research focuses on modifying the former to take snapshots of the heap during program crashes and having ChatGPT converse with the debugger in order to suggest possible solutions to the user. Currently, ChatGDB is usable through a GDB, LLDB, and PDB interface with limited WinDBG extension capabilities. Our paper on ChatDBG is available on Arxiv: https://arxiv.org/abs/2403.16354

REST_π / Tufts University

May 2022 - May 2023

Under my advisor, Jeffrey Foster, and alongside Ph.D. student Mark Aldrich, I worked on building REST_π, a type inference engine that could automatically generate REST API specifications using path-sensitive type inference. Implemented for Ruby, REST_π could generate API specifications with more exact and complete types by considering each distinct path through an endpoint implementation. I was involved in the early work for REST_π, helping to develop the formalism behind the path-sensitive type inferencing, and later on, running some of the evaluation benchmarks for it as well.

ADAGIO / Tufts University

June 2021 - Sep 2021

In the Cowen Lab under Lenore Cowen, I worked as an undergraduate research assistant as part of the Laidlaw Scholarship program, where I assisted Ph.D. student Mert Erden on developing ADAGIO, a graph-searching algorithm for protein-protein-interaction (PPI) networks to identify possible unidentified disease genes. This used known disease modules for neurological diseases such as Alzheimer's and Parkinsons's to identify clusters of genes possibly linked to symptoms of these diseases. Our findings were later presented at the 2022 ACM BCB conference and can be found here: https://dl.acm.org/doi/abs/10.1145/3535508.3545542

Amazon Web Services Applied Scientist Intern

May 2025 - Current

Currently working on a research internship with AWS as part of the Automated Reasoning team under Mike Hicks.

UMass Amherst / Tufts University / Teaching Assistant

Aug 2020 - Dec 2023

I have been a teaching assistant for seven semesters, at both UMass Amherst and Tufts. At Tufts, I taught Discrete Mathematics under Prof. Karen Edwards and Cryptography under Prof. David Wittenberg, and at UMass Amherst, I was a TA for the Introduction to Computation course with Prof. David Barrington. This involved grading homework and exams, hosting office hours, and leading discussions, reviews, and workshops for hundreds of students.

Harvard University Widener Library / Student Programmer

May 2023 - Aug 2023

At Harvard University, in the Wiedner Library Judaica Division, I helped develop new programming scripts and interfaces in FileMaker to make the library's digital collection both easier to navigate and faster to index. Many of my scripts made it easier to digitalize records and compile the collection into visualized statistics and graphs.

Varsity Tutor / Academic Tutor

May 2022 - Jan 2023

I tutored remotely through Varsity Tutors in a wide array of subjects, such as programming in C, C++, and Python, web development, theory and mathematics, chemistry, engineering, and standardized test review. These were one-on-one private online sessions with students from all over the country, anywhere from 8th grade to adult learners, and usually involved reviewing course materials or creating and testing on my own custom materials.

Tortoise Media / Intelligence Team Intern

July 2022 - Sep 2022

I interned at Tortoise Media with their Intelligence Team as part of the Laidlaw Scholars program. This involved collecting research and information for the company's stories and website pages, specifically a project to compile MP financial transactions into an interactive graph that could be queried. I analyzed this data and wrote a clustering algorithm to help the program distinguish MPs and donors with similar names.