About

About Me

Hi, I’m Vedant Mehta. I’m a Computer Science student at Stanford University (Class of 2030), pursuing a CS + Mathematics co-terminal master’s with a focus on Artificial Intelligence. I’m the founder of Vigil, an AI safety-focused company. [one to two sentences on what Vigil does and why].

Before Stanford, I spent my high school years doing independent research at the intersection of machine learning and medicine: building models to segment polyps during colonoscopy (published and presented at IEEE BIBE 2023), classifying chest radiographs for lung disease detection during a summer at Stanford’s AIMI Center, and using EEG data to help people with neurological disorders manage their emotions. Outside of research, I was an officer in Future Business Leaders of America (FBLA) and President of Students Against Destructive Decisions (SADD) at Lambert High School.

These days, that same interest in using technology for real, structural good has carried over into my focus on AI safety — making sure the systems we’re building at Stanford and through Vigil stay trustworthy as they get more capable.

Programming Skills

Python         [=========-] 90%
TensorFlow     [=========-] 95%
NumPy          [=========-] 90%
JavaScript     [========--] 80%
React          [========--] 80%
Java           [=======---] 70%

Other Skills

Microsoft Excel [=========-] 90%
Canva          [========--] 80%

Timeline

Stanford & Vigil

2026–Present

Founder, Vigil

Founded Vigil, an AI safety-focused company [add one-line mission and funding detail here].

2026–2030 (expected)

B.S. Computer Science (AI track), Stanford University

Studying Computer Science with a focus on Artificial Intelligence, pursuing a CS + Mathematics co-terminal master's. Interested in AI safety research and building tools that make advanced AI systems more trustworthy.

High School & Early Research

2024–2024

Summer Research Intern, Stanford AIMI Center

Spent a summer at Stanford's Artificial Intelligence for Medical Imaging Center building a multi-label chest radiograph classifier (F1 0.69, AUROC 0.86 on CheXpert) with RadGraph-based report parsing and GradCAM interpretability.

2023–2023

Published Researcher, IEEE BIBE

Presented "Towards Real-time Polyp Segmentation during Colonoscopy using an EfficientNet-based UNet Architecture" at an MIT research conference, later published and presented at IEEE BIBE 2023.

2022–2026 (expected)

Student, Lambert High School

Pursued a full load of Advanced Placement coursework alongside independent research in medical imaging and brain-computer interfaces. Served as an officer in Future Business Leaders of America (FBLA) and as President of Students Against Destructive Decisions (SADD).