Baris Yildirim

I studied Computer Science and Classics at Dartmouth, and I work as a healthcare data analyst. In my own time I make software for reading and learning.

Email LinkedIn GitHub

Selected work2024 – now

PurpleSearch

Kemeny Prize

Graph-RAG code search across 300K+ lines of code: Neo4j code graphs, embedding retrieval and LLM synthesis. I architected it and designed the evaluation benchmark (team of 5).

Neo4j · embeddings · RAG · evaluation

Context-Dynamic Prompting

Research

An LLM adapter that combines LoRA with dynamic prompt embeddings via cross-attention (team of 2). Beat Alpaca-LoRA on PIQA and WinoGrande, and trains in about 5.5 hours on two RTX 4090s.

PyTorch · LoRA · PEFT · LLaMA

Daimonion

In progress

Write-up coming soon.

Background

About

I came to computing through Classics, and most of what I build comes out of that: tools for reading difficult texts and remembering what you read.

Experience

  • Founder & full-stack developer, antiQ.ai Jun 2024 – now

    Product, engineering, model pipeline, deployment and user acquisition, end to end.

  • Healthcare data analyst Aug 2025 – now

    Cost modeling and reporting for pharmacy-benefit clients.

Education

  • Dartmouth College 2025

    B.A., Computer Science modified with Classical Languages. Henry C. Beck Jr. 1938 Scholar.

    Kemeny Computing Prize (System Design) · Atherton 1883 Greek Prize · Magnuson Center for Entrepreneurship grant for antiQ.ai · Academic Excellence Citation, Multi-Modalities Generative AI

  • Tuck Business Bridge Program 2024

    Financial modeling, valuation, accounting and corporate finance.

Skills

AI / ML
PyTorch, fine-tuning (LoRA, PEFT), RAG, embeddings, synthetic data, model evaluation, agent orchestration
Full-stack
Next.js, React, TypeScript, Node.js, PostgreSQL
Programming
Python, TypeScript/JavaScript, SQL, Bash, Java
Languages
Turkish (native), English (fluent), Latin and Ancient Greek (reading), Italian, French and Russian (conversational).