Matt Franchi

Data Scientist

https://talent.gravityer.com/matt-franchi

CS PhD @ Cornell | @IRL-CT & DLI; urban visual analytics & ethical AI

Cornell Tech

Key Strengths

Extensive experience with Python and Jupyter Notebook for data analysis and scientific computing.
Demonstrated ability to apply data science techniques to real-world problems, including urban planning, policing, and environmental modeling.
Experience with high-performance computing (HPC) and parallelized simulations.
Exposure to diverse technical stacks including C++, Shell, Matlab, Swift, and Metal.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects show a strong inclination towards research-oriented and socially impactful data science applications, which could align well with organizations focused on innovation and public good. The diversity of projects suggests adaptability and a broad interest in problem-solving. However, the single listed professional experience as 'Data Scientist' at Cornell Tech starting in the future (2026) with no end date and 'isCurrent: true' is contradictory and raises questions about actual professional experience. This makes it difficult to fully assess cultural fit based on professional context.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The psychometric test score is 0, providing no insight.

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Assessing your cultural and operational fit

Projects

bayflood

June 29, 2024 – Present

Modeling urban street flooding from dense street imagery

View Project

claustrophobic-streets

May 25, 2024 – December 1, 2025

Code and analysis described in NYT Street Wars piece on 'claustrophobic' streets - https://www.nytimes.com/2024/07/29/nyregion/street-wars-crowded-sidewalks-times-square.html

View Project

urban-fingerprinting

September 14, 2023 – July 11, 2024

urban-fingerprinting — GitHub repository

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police-deployment-patterns

March 7, 2023 – December 15, 2023

Code to reproduce results in "Detecting disparities in police deployments using dashcam data" (FAccT 2023)

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InpaintingDataAugmentation

December 19, 2022 – December 23, 2022

Stable Diffusion 2-powered inpainting for synthetic training data generation.

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LIDARDepthCamera

December 5, 2022 – December 21, 2022

LIDARDepthCamera — GitHub repository

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Webots.HPC_RMS

September 24, 2021 – September 29, 2021

Webots.HPC Sample Simulation - Roadway Merging Scenario

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RMDT

September 24, 2021 – September 24, 2021

RMDT — GitHub repository

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Webots.HPC

September 3, 2021 – May 28, 2023

Toolkit to bring Webots to High Performance Computing, with support for parallelized and distributed batches of simulations.

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Kanban

March 29, 2020 – December 22, 2022

Check In System for CUhackit V2

View Project

Key Strengths

Extensive experience with Python and Jupyter Notebook for data analysis and scientific computing.
Demonstrated ability to apply data science techniques to real-world problems, including urban planning, policing, and environmental modeling.
Experience with high-performance computing (HPC) and parallelized simulations.
Exposure to diverse technical stacks including C++, Shell, Matlab, Swift, and Metal.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The psychometric test score is 0, providing no insight.

Matt Franchi

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit