Open to opportunities

Daniel Gallagher

@danielgallagher

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Computer science student building AI systems and full‑stack applications.

United States

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What I'm looking for

I am seeking hands‑on roles building AI/ML systems or full‑stack applications where I can contribute to production projects, learn from experienced engineers, and grow in a collaborative, impact‑driven team.

I am a computer science student focused on building AI-driven systems and full‑stack web applications that solve real problems.

My hands‑on experience includes developing multi‑agent AI workflows for vulnerability-based honeypot generation and building an AI-powered goal planning app with React, Next.js, TypeScript and LiteLLM integration.

I have applied machine learning to applied problems — from agricultural yield prediction using Random Forest and Gradient Boosting to neural modeling in computational neurobiology — and presented research findings in academic settings.

I also have strong outreach and teaching experience designing Python and Java curricula, leading community partnerships, and mentoring students, and I bring collaborative, production-minded development practices to every project.

Experience

Work history, roles, and key accomplishments

Software Developer

Duke Code+ Program

Jun 2025 - Aug 2025 (2 months)

Contributed to a multi-agent AI system that generated honeypots from real-world CVEs; designed agent workflows and prompts for task planning and code generation, and implemented frontend components to interact with backend AI agents and CVE APIs.

Prompt Engineering Frontend Development JavaScript React API Integration CVE LLMs LLM

Instructor & Outreach Director

Kid Coders 365

May 2022 - Jun 2024 (2 years 1 month)

Spearheaded external partnerships and communications with community organizations and designed/delivered Python and Java curriculum to 80+ students, improving retention through interactive teaching methods.

Curriculum Design Python Java Outreach Partnership Development Teaching

Researcher

Boston University RISE Program

Jun 2023 - Aug 2023 (2 months)

Developed computational neural models simulating propranolol’s effects on memory reconsolidation and identified a significant linear correlation between dosage and fear memory attenuation; presented findings at a university poster symposium.

Python Data Analysis Statistical Correlation Presentation Synaptic Plasticity