Work Experience

Shipped an end-to-end AI system to detect anomalies on floor plans, cutting manual effort up to 80% and processing 10× more orders per month.
Built Nasiwak Studio, an end-to-end vision AI system to detect 85+ small electrical symbols on blueprints, automating manual invoice generation up to 100%.
Created an AI karaoke pipeline (yt-dlp, UVR, Whisper, FFmpeg) that renders videos in <5s; engineered a C++ autotune backend with ±1ms latency and 80% noise reduction for live audio.

Incubated at Harvard Innovation Labs, mentored by ex-IIT and ex-Harvard founders on production-grade ML delivery.
Engineered scalable time-series forecasting pipelines on Azure Databricks (PySpark, ETL) to ingest and model sales data in cloud data lakes.
Built an XGBoost model achieving 92.81% accuracy on regular sales and 86.79% on promotional sales, using features from inventory, logistics, historical sales, and regional weather.
Benchmarked ARIMA and SARIMA auto-regression baselines to strengthen forecast confidence for planning teams.
Wrote BigQuery analytics to surface trends from large datasets; contributed to time-series, computer vision, and LLM application prototypes.

Led a team to design and deploy RPA solutions that replaced repetitive manual workflows across the business.
Automated web scraping, online data collection, and Excel reporting, improving task efficiency 30%.
Reduced operational drag by turning fragile, hand-run processes into reliable, repeatable automations.

Led a developer team to deliver a dynamic full-stack website, owning frontend, backend, and release coordination.
Designed the database schema and real-time client-server connectivity with phpMyAdmin and Wamp Server.
Shipped a production-ready site that gave the business a stable digital presence instead of static brochure pages.