I'm a Full Stack Developer currently working at UNM Health Sciences, where I build and maintain production research platforms used daily by 20+ scientists. My work sits at the intersection of backend engineering, cloud infrastructure, and scientific software.

• 🔭 Currently: Full Stack Developer at UNM Health Sciences – IM Translational Informatics
• 🎓 Education: B.S. Computer Science + Minor in Mathematics, University of New Mexico (Dec 2026)
• 🌏 Background: Nepal → New Mexico
• ⚙️ Focus: Reliable, production-grade systems — not just prototypes
• 🏆 Recognition: NIH CFDE Summer Fellow (2024) | Engineering Success Scholar | 3.6 GPA

• Architecting full-stack research platforms serving multiple active projects simultaneously
• Building and maintaining REST APIs used in production cheminformatics workflows
• Leading system design decisions and collaborating with research scientists on requirements

• Managed Linux server infrastructure for 20–30 active researchers
• Migrated 10+ production services from direct Nginx execution to Docker-based deployments
• Maintained AWS infrastructure (EC2, S3, RDS) across production workloads

FastAPI · React · Recharts · PostgreSQL · Docker

Full-stack biomedical research platform aggregating 190,000+ clinical trials to score and rank drug-target associations. Built the complete frontend, backend, and REST API from scratch.

• Interactive scatter plots, evidence tables, and drill-down views
• Direct source links to ClinicalTrials.gov and PubMed for traceability
• Deployed in production at UNM Health Sciences

React · Flask · PostgreSQL · Redis · Docker

Production web application enabling researchers to apply SMARTS chemical filters to large batch datasets — no coding required.

• Handles large-scale concurrent dataset analysis in production
• Result caching for repeated queries
• Used actively by UNM cheminformatics research team

FastAPI · React · PyTorch · Celery · Redis · PostgreSQL · Docker

Production-architecture media forensics platform for detecting AI-manipulated images and videos.

• Grad-CAM heatmap explainability showing which image regions triggered detection
• Async video processing pipeline with frame-by-frame analysis via Celery workers
• Downloadable PDF forensic reports with metadata and confidence scores
• Full CI/CD pipeline via GitHub Actions; Dockerized multi-service deployment

Java · Sockets · Multithreading

Distributed system with a central bank, multiple auction servers, and concurrent bidding agents — real-time transactional settlement across concurrent threads.

Open to full-stack, backend, and research engineering roles. I'm especially interested in teams building data-intensive platforms, developer tooling, or applied ML systems.