Building AI that thinks carefully
and ships cleanly.

Fine-tuning and optimizing LLM-powered agents with GPT-4o, Gemini, and Claude, cutting hallucinations, tightening response consistency, and wiring external tools into enterprise finance workflows.

Co-leading RAG benchmarks vs Open Deep Research and AutoGPT across retrieval quality, grounding, and hallucination rate. Multi-LLM pipelines with GPT-4o, Gemini, Llama, and Claude, with +9% answer accuracy via prompt and retrieval optimization.

Enhanced GenMobius enterprise AI MVP; intent-aware agents with Azure AI Search; proposal generation system; NASA C-MAPSS RUL predictive maintenance benchmarks.

Predictive failure detection for Flint bus systems; 100k+ synthetic records for rare events; Graph Neural Networks outperforming classical and deep baselines. Also fine-tuned YOLOv8 on 800+ dental radiographs to 91% mAP50.

Designed 10+ cloud & AI curriculum modules. Co-built an AI avatar & synthetic voice MVP (HeyGen-style) with generative APIs and audio synthesis in a deployable web app.

Built a real-time underwater object detection system with YOLOv8 on a custom dataset from proprietary camera footage and open-source data. Validated on physical hardware in live underwater environments; designed the full ingestion, annotation, and augmentation pipeline.

End-to-end deep learning pipeline for malware classification from opcode and API sequences across 20+ families. Decompiled 10k+ Windows binaries with IDA & Ghidra; transformer NLP reached 96.4% accuracy with SHAP-based interpretability.