San Jose State University
Software developer(Contract) – Caltrans (California Department of Transportation), San Jose, CA
Project: Real-Real Time Traffic Analytics and Safety Monitoring System
Conducted applied research on computer vision and multimodal traffic datasets, designing and
fine-tuning deep learning models in Python + OpenCV to identify accident patterns and traffic anomalies.
• Designed structured evaluation frameworks to compare model performance across distributed inference pipelines, improving interpretability and reproducibility of results.
• Developed data ingestion and synchronization workflows using Kafka, Redis, and PostgreSQL,
enabling controlled experiments on large-scale video streams.
• Documented findings and system behaviors throughexperiment reports, error analysis summaries,
and annotation logs to support data-driven decision-making.
• Integratedvision-language embeddings (CLIP)with object tracking methods (ByteTrack) for occlusionhandling research, producing measurable accuracy gains in context-aware tracking.
• Collaborated with faculty researchers to prepare briefs summarizing key metrics, drift patterns, and
improvement strategies for model retraining cycles.