A collection of software projects across machine learning, infrastructure, and web development.
Built the company’s core platform from zero to production, covering backend services, frontend applications, cloud infrastructure, and CI/CD workflows for AI-driven questionnaire and reporting products. Supports 20 client companies, 600+ respondents, and 50k+ WhatsApp Chatbot interactions.
Designed and built a full WhatsApp chatbot platform in 2 weeks, including backend, frontend, database, Dockerized services, and ECS/Fargate deployment. The system delivers questionnaires, automates follow-ups, and handles high-volume interaction flows.
Built asynchronous workflows for data ingestion, notification delivery, AI-assisted analysis, and automated report generation. Refactored a failing monolithic workflow into 3 focused services, improving observability, retries, and long-term maintainability.
Designed and maintained data warehouse and data lake components for analytics workloads using S3, Athena, Glue, Python, and SQL. Supported asynchronous processing, reporting, and machine-learning-oriented data workflows.
Developed and optimized Python and R pipelines for large-scale genomic and epigenomic datasets, including scRNA-seq, ATAC-seq, Hi-C, and ChIP-seq, with emphasis on reproducibility, performance, and scientific rigor.
Refactored and extended scientific simulation software in computational physics, using Python, C++, Fortran, and parallel computing techniques to reduce runtimes from hours to seconds and support high-throughput analytical workflows.