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Matheus Dias

Matheus Dias

Building @ Luzid (We're hiring!)

Stanford, California, United States
rocketreach
Joined May 2025
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Summary

Matheus Dias is a co-founder and CTO of Luzid, an AI-powered platform aimed at revolutionizing enterprise software implementation. He previously contributed to the founding team of Orby AI, demonstrating a strong entrepreneurial drive in the AI/ML space. yahoo+1
His academic background at Stanford (MS in Statistics focusing on Interpretability, Causal Inference, Image-To-Text Generation) and internships at Meta AI and Openlayer, along with several personal projects, showcase deep expertise in machine learning, NLP, computer vision, and data science. github+2
Through his work as a Research Assistant at Stanford's NLP Group, his Bass Connections projects at Duke (e.g., 'Spillover Impact of Cash Transfers on Education'), and his role as a Data Analyst at Wildlife Studios, Matheus has demonstrated robust analytical and research capabilities, often involving statistical modeling and data-driven insights. duke+4
His involvement in projects like evaluating growth mindset interventions in Bangladesh and strengthening ecotourism in rural Mexico, along with his publication on the spillover effects of cash transfers on education, highlights a commitment to applying his skills for social good and global development. duke+3
As a Brazilian national, his involvement with BRASA (Brazilian Student Association) as CEO Américas and Board Member, and his comments on a Brazilian film winning an Oscar in the Stanford Daily, demonstrate a strong connection to his cultural roots. stanforddaily

Work

Education

Projects

Writing

Anchor your predictions

March 31, 2022

A blog post by Matheus Dias discussing the use of Anchors for understanding model results and explainability in machine learning.

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Spillover Impact of Cash Transfers on Education

July 1, 2021

An analysis co-authored with Mitchell Ochse, exploring the impact of conditional and unconditional cash transfers on school enrollment rates for younger female respondents in Malawi, based on data from the SIHR survey. This work received High Honors from the Duke Economics department.

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