- Improved picking accuracy by 23% by developing a custom computer-vision architecture with channel separation for RGB-D depth processing and expanding the training dataset
- Reduced labeling costs by $5,000 and accelerated turnaround time by developing a custom data-labeling wearable device
- Built production NLP pipeline processing 500K+ campaign messages daily using Python, spaCy, and AWS Lambda
- Fine-tuned BERT models for political sentiment classification, achieving 15% accuracy improvement over baseline
- Developed robotics control modules in C++ and Python within ROS/Linux environment to translate human grasping patterns into real-time autonomous manipulation routines
- Built modular data-collection systems that reduced preprocessing time by 40%, streamlining the mapping of human grasping patterns to robotic actuation
- Engineered high-performance backend for dynamic ad placement on streaming platforms using Go, AWS, and MySQL, reducing request latency by 23% in a latency-sensitive production environment
- Designed and implemented automated unit-testing pipeline in Go, improving API reliability and scalability for a system serving millions of daily requests
- Built a Python-based monitoring pipeline for simulated data center systems, applying AI-driven anomaly detection to sensor data (temperature, power, throughput)
- Deployed results to a Grafana dashboard with Prometheus and automated weekly reporting using Airflow, improving operational insights and reducing manual analysis
- Deployed IoT-enabled streetlights, driving energy savings and cost reductions
- Configured Intel hardware for Computex 2018 demos, showcasing advanced IoT solutions globally
