Founder & CTO, OneAdmissions
From Stanford Code in Place to building production AI systems
As Founder and Chief Technology Officer of OneAdmissions, I've built and deployed multiple AI-powered applications that serve thousands of students and professionals. My technical expertise spans AI/ML infrastructure, database architecture, API integrations, and full-stack development.
5+ years of continuous technical growth: From academic AI foundations to building privacy-first production systems.
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🏛️ Stanford Code in Place 2025 - Current Cohort (Active)
- Advanced Python programming
- Computer science fundamentals
- Collaborative software development
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🧠 Elements of AI Certification - University of Helsinki (2020)
- Machine learning foundations
- AI ethics and implementation
- Data science principles
- Production AI Systems (2024-2025)
- Database Architecture (2023-2025)
- DevOps & Infrastructure (2024-2025)
- Local LLM Deployment: Managed multi-model AI infrastructure with Ollama
- Model Architecture: Deployed qwen2.5:14b, mistral-small, phi4, deepseek-r1:8b, codestral
- Privacy-First AI: Built 100% local processing pipeline (zero external API dependencies)
- Multi-Model Strategy: Different models optimized for specific tasks (reasoning, code generation, extraction)
- Storage Architecture: 65GB+ distributed model management across hybrid storage systems
- Notion API Integration: Complex 23-field database schema management
- JSON Data Modeling: Structured data transformation and validation
- Multi-Database Coordination: Job tracking, grant management, fundraising intelligence
- API Authentication: Secure environment variable management and credential handling
- Multi-Drive Architecture: Hybrid laptop/T7 storage system optimization
- Environment Management: Shell configuration, dependency management, system optimization
- Command Line Mastery: Terminal operations, debugging, system monitoring
- Project Coordination: 7+ concurrent technical projects with dependency management
- Python: Advanced (Production applications, AI integration, web scraping)
- FastAPI: Backend development and API creation
- JavaScript/HTML/CSS: Frontend development
- Shell Scripting: System automation and configuration
- SQL: Database management and optimization
Advanced VC/Investor Research Automation
- Repository: fundraising-intelligence
- Tech Stack: Python, Ollama, Notion API, BeautifulSoup, Local LLMs
- Features:
- Auto-extraction from VC websites and databases
- Smart deduplication against existing 23-field database
- Multi-source enrichment (AngelList, Crunchbase, LinkedIn)
- Confidence scoring and validation
- Architecture: Privacy-first local AI processing with complex data modeling
- Innovation: Zero external API calls for sensitive fundraising data
Automated Job Posting Analysis & Tracking
- Repository: job-extractor
- Tech Stack: Python, qwen2.5:14b, Notion integration, web scraping
- Features:
- Legal credential detection and classification
- Intelligent salary parsing and normalization
- Automated deadline tracking and management
- JD vs non-JD position categorization
- Impact: Streamlined job application workflow for legal professionals
- Innovation: Context-aware extraction with legal industry specialization
Grant Opportunity Discovery & Management
- Repository: grant-extractor
- Tech Stack: Python, local LLM processing, structured data extraction
- Features:
- Automated grant discovery and categorization
- Eligibility analysis and matching
- Deadline management and notification
- Amount parsing and budget planning
- Architecture: Integrated with existing task management database
- Innovation: AI-powered grant-to-applicant matching algorithms
AI Coaching Assistant Platform
- Repository: mini-donna-mvp
- Tech Stack: FastAPI, async operations, multi-AI provider architecture
- Features:
- Local Ollama integration with OpenAI fallback
- Document analysis and feedback generation
- Personalized coaching recommendations
- Real-time chat interface
- Architecture: Microservices approach with AI service abstraction
- Innovation: Hybrid local/cloud AI processing with privacy controls
Enterprise-Grade Next.js Portfolio Website
- Repository: concepts-by-coleman
- Live Site: conceptsbycoleman.com
- Tech Stack: Next.js 15, TypeScript, Tailwind CSS v4, Vercel deployment
- Features:
- Responsive design with mobile-first approach
- Custom component architecture (ProjectCard, config-driven content)
- WCAG accessibility compliance and SEO optimization
- Embedded integrations (Zcal booking, Tally contact forms)
- Performance optimized (Lighthouse 95+ scores)
- Development Time: Built and deployed in 1 day
- Innovation: Modern React patterns with TypeScript and cutting-edge CSS framework
- Architecture: Component-based design with centralized configuration
Intelligent Note-Taking and Analysis
- Repository: oneadmissions-ai-notes
- Tech Stack: Python, AI integration, document processing
- Features: AI-powered note organization and analysis
- Impact: Enhanced productivity for education professionals
- Built 100% local AI processing infrastructure for sensitive data
- Zero external API calls for confidential business information
- Multi-model optimization for different use cases and performance requirements
- Advanced storage management across distributed systems
- Auto-enrichment algorithms for missing data completion using multiple sources
- Smart deduplication with fuzzy matching against existing databases
- Confidence scoring for extraction quality assessment and validation
- Multi-source data aggregation with conflict resolution
- Complex schema management with 20+ field relational structures
- Dynamic property mapping for flexible API integrations
- Cross-platform data synchronization with conflict resolution
- Automated relationship management and data integrity
- Model selection algorithms for task-specific AI processing
- Parallel processing for large-scale data operations
- Memory management for 65GB+ model deployments
- Storage optimization across multiple drives and systems
- 🏗️ Built 6+ production applications (AI systems + full-stack web apps) serving real users
- 🤖 Deployed enterprise-grade AI infrastructure processing sensitive business data
- 📊 Designed complex database architectures with 20+ field relationships
- 🔧 Mastered full development lifecycle from conception to deployment
- 🛡️ Implemented enterprise security with environment management and credentials
- ⚡ Optimized system performance with multi-drive storage architecture
- 🔄 Coordinated multiple concurrent projects with dependency management
- 🎓 Active Stanford Code in Place participant (2025 Cohort)
- Status: Active Development
- Scope: Multi-source data aggregation, AI-powered analysis, automated enrichment
- Tech Challenges: Large-scale web scraping, AI model optimization, real-time deduplication
- Innovation: Privacy-first architecture for sensitive fundraising data
- Status: Ongoing Optimization
- Scope: Model performance tuning, storage architecture optimization
- Innovation: Local-first AI processing at enterprise scale
- Status: Active (2025 Cohort)
- Scope: Advanced computer science concepts and collaborative development
- Application: Applying CS fundamentals to production systems
"Build privacy-first, AI-powered solutions that scale."
I believe in:
- 🛡️ Privacy-first architecture - Keep sensitive data local and secure
- 🧠 AI-augmented workflows - Use AI to enhance human decision-making
- ⚡ Performance optimization - Build systems that scale efficiently
- 🔄 Iterative development - Ship fast, learn, and improve continuously
- 🎓 Continuous learning - From Stanford coursework to production deployment
2020: Elements of AI (University of Helsinki) - AI foundations
2021-2023: Self-directed learning and business development
2024: First production AI applications deployment
2025: Stanford Code in Place + Advanced AI infrastructure
Future: Scaling to serve 10,000+ users with enterprise-grade systems
Scaling OneAdmissions' technical infrastructure to serve 10,000+ users while maintaining:
- Zero-downtime deployments with robust CI/CD pipelines
- Enterprise-grade security with advanced threat protection
- AI-powered automation across all business workflows
- Industry-leading privacy standards for educational data
Immediate Goals:
- Complete Stanford Code in Place 2025 with honors
- Deploy GPT-OSS integration for enhanced local AI processing
- Launch advanced fundraising intelligence platform
- Build scalable infrastructure for 10x user growth
GitHub: @OneC0de
OneAdmissions: oneadmissions.com
LinkedIn: https://www.linkedin.com/in/donnascaffidi
Email: [email protected]
"From academic foundations to production systems - building the future of AI-powered education technology."
⭐ Star this repo if you're interested in privacy-first AI development!