"What I cannot create,
I do not understand."

Building on CPC-OS, the firm's AI platform on Azure: shipping deal lifecycle modules that write to DealCloud CRM through API + MCP integrations, every write behind a human-confirmation gate. Designing CPC-OS thesis modules that put thesis research and the full deal pipeline in one view, from sourcing through diligence.

Architecting RelGraph, a PostgreSQL knowledge graph spanning 22,000+ business owners and 1,500+ M&A targets, with BFS pathfinding up to 4 hops to surface warm introduction paths to acquisition targets.

Built a scientific content analysis pipeline: MinerU-based PDF extraction across 3,000+ pages, Qwen3-Embedding for 17,000+ dense vectors, and BERTopic with HDBSCAN discovering 493 topics at 0.9791 mean cosine similarity.

Mapped prerequisite knowledge chains with Gemma topic labeling and hierarchical clustering. This work lays the foundation for Sparse Autoencoder training and LLM interpretability research.

Trained YOLOv7/v8 defect detection models for manufacturing QC. Deployed on NVIDIA Jetson with DeepStream SDK and TensorRT (FP16/INT8) achieving 3x inference speedup and 25% reduced detection latency.

Designed Flask REST APIs for real-time inference across 3 production lines. Built multi-threaded Docker backend with AWS/Azure data pipelines, CI/CD, and 85% test coverage.

Built K-Means clustering to identify 5 customer personas. Designed Grafana dashboards tracking 15+ KPIs: revenue, churn, CAC, and operational efficiency.

Conducted EDA on 100K+ transactions using Python and SQL. Automated reporting pipelines, reducing manual work by 40% and enhancing operational visibility by 30%.