Quinn Perian

Massachusetts Institute of Technology, BSc & Masters in Computer Science

Graduating May 2026

Classes: Natural Language Processing, Crowd Sourced City: Data Activism, Clinical Data Learning, Intro Machine Learning, Intro to Algorithms, Interactive Data Visualization & Society, Statistics, Feminist Thought

GPA: 5.0/5.0

MIT Healthy ML Lab

May 2024 - Ongoing

Undergraduate ML Researcher

• Developing method for decoupled bias reduction in Vision-Language Models by transforming representation vectors, reduced performance gap by 30% and lowered computational/training costs by 100x compared to current literature

• Implementing tests for task-transferability for review of dozens of extant debiasing techniques in vision language models

Class Technologies

May 2024 – Aug. 2024

Data Science and Visualization Specialist

• Redesigned videoconferencing breakout room dashboard to reduce cpu utilization and bandwidth by factor of 1000, implementing language model to flag harassment and visualize activity in each breakout

• Designed & implemented new data portal using React and Python for instructors to predict which students are at risk

Bioinformatics Data Scientist

• Used R and Python on a high-performance computing cluster to analyze and visualize omics data and perform clustering

• Modified orthogroup clustering software written in Python, resulting in >3x speed-up

• Verified differential-equation-based cellular model in Julia & developed ML model to predict variation from transcriptome

The Works, Inc.

Aug. 2023 – Feb. 2024

Data Scientist

• Used Python, R, & Google Sheets to speed up eviction geocoding 100x, and analyze data to classify 100,000+ retaliatory evictions

• Created interactive maps/visualizations of retaliatory evictions using QGIS and ArcGIS StoryMaps, collaborating w/ team of 7

• Successfully used QGIS, Tableau, and R to create visualizations convincing city to give additional $4 million in eviction aid

MIT Justice-Centered Healthy Mobilities Group

Nov. 2022 - May 2023

Undergraduate Researcher

• Used mapping software to analyze and geospatially visualize inequities in transportation and public health, identifying and assessing potential partnerships with >50 community organization

• Interactive dashboard developed to enable lawmakers to show effectiveness of transfer tax and customize tax parameters by region

• Developed in collaboration with and for use by city government (Metropolitan Area Planning Council)

• ArcGIS StoryMap developed in collaboration with The Works, Inc. for the government of city of Memphis to help identify prevalance of illegal evictions

• Developed using QGIS, R, and Python to visualize evictions by region and demographicin Memphis, TN

• Small personal project built to visualize bike traffic in Boston by time of day to understand rush hour dynamcis and typical routes

• [1] “Transcriptome Data Enable Physiological Model Customization and Illumine Phytoplankton Thermal Response,” Ocean Sciences Meeting, 2024.

• [2] “Justice-Centered Participatory Research on Transportation and Health,” Association of Collegiate Schools of Planning, 2023.

• [3] “Counting Nontrivial Equivalence Classes of S_n Under {1234,3412}-Pattern-Replacement,” first author, Online Journal of Integer Sequences, 2020.

• [4] “Analyzing Transit Timing Variations in Transits of TrES-1 b,” Journal of the Korean Astronomical Society, 2022.

• [5] “Utilizing Small Telescopes Operated by Citizen Scientists for Transiting Exoplanet Follow-up,” Publications of the Astronomical Society of the Pacific, 2020.

Python, Typescript/Javascript, R, SQL, Julia, HTML, CSS, LaTeX, C++

PyTorch, Pandas, Numpy, Sklearn, React, GIS, Matplotlib, dplyr, ggplot, High-Performance Computing, Slurm, Bioconductor, DESeq2, Git, Excel/Google Sheets

Data Analysis & Pipelining, Machine Learning (LLMS & VLMs), Distributed Processing on Large Datasets, Data Visualization, Communication, Organizational Leadership/Management, Participatory Action Research (PAR), Critical Race & Gender Theory

MIT EECS - Takeda Undergraduate Research and Innovation Scholar

Oct. 2024

Award prsented by MIT for research in computer science