Full-stack engineer building equitable AI and SaaS tools. Next.js, React, Node.js, and real infrastructure.
Full-stack engineer & CS undergrad building equitable AI and SaaS tools. Built infrastructure handling 2,000+ concurrent users on a Minecraft server—proving real-world scale experience. Currently pursuing CS at North South University while shipping production systems.
Built multi-tenant SaaS systems, real-time collaborative tools, and AI-driven fairness systems. Worked with teams on production infrastructure.
Full-stack development with Next.js, React, Node.js, MongoDB, WebSockets, multi-agent AI systems, and performant infrastructure.
NSU marketing coordinator (quantifiable impact), Andrew Ng ML certification, Silver Medal at Genius Olympiad, IoT Country Champion.
Transparent about what I build and how I build it. Real projects, real scale, real outcomes. Every claim here is backed by something I can show you.
Each project is a full case study: problem → approach → outcome
Multi-tenant SaaS for real-time collaboration
Teams needed a collaborative CRM with real-time updates and multi-user editing.
Built with Next.js, WebSockets, and MongoDB. Architecture prioritized low-latency updates and seamless concurrent editing.
Production system handling complex workflows with real-time synchronization and VoIP integration.
Fairness metrics & clinical impact in healthcare AI
AI systems in healthcare had hidden biases affecting patient outcomes across demographic groups.
Used SHAP (explainability) to identify and measure unfairness. Built fairness-first ML pipelines with demographic parity metrics.
Demonstrable fairness improvements across protected groups. Presented findings on clinical impact.
Multi-agent AI system on AMD MI300X
Complex medical decisions needed AI-assisted reasoning across multiple specialties simultaneously.
Multi-agent AI on AMD MI300X. Each agent handles a domain (pathology, radiology, etc.) with a 70B LLM orchestrating consensus.
Real-time multi-perspective analysis for clinical decision support with full explainability.
2,000+ concurrent users at scale
Community server needed to scale from 100 to 2,000+ concurrent users without infrastructure meltdowns.
Optimized Linux kernel, MongoDB sharding, load balancing. Built monitoring and auto-scaling across a 20-member team.
2,000+ concurrent users sustained. 20-member dev team. Proved real-world DevOps chops.
Project philosophy: Each project demonstrates real-world problem solving — from building fairness into AI systems to managing infrastructure at scale. Focus on outcomes over outputs, credibility through specificity.
Organized by domain — every technology used in production.
5 technologies
6 technologies
6 technologies
Skills are only as good as their output. Every technology here has been used in production — from handling 2,000+ concurrent users to building fairness-aware AI pipelines.
Key milestones across achievements, education, and experience.
Recognized for innovative STEM project at international competition in New York.
Led IoT project to national championship, representing the country.
Started building production systems with Next.js and Node.js. First real SaaS product launched.
Built and scaled infrastructure to handle massive concurrent user base with a 20-member team.
Secured quantifiable sponsorship impact for university initiative at North South University.
Completed advanced machine learning certification from DeepLearning.AI.
Built multi-agent AI system on AMD MI300X for clinical decision support.