Led cutting-edge research and development initiatives focused on applying modern AI and machine learning technologies to real business challenges. Explored emerging patterns, evaluated new frameworks, and built functional prototypes that demonstrated the practical value of AI-driven solutions across multiple domains.
Worked extensively with Semantic Kernel, ONNX, Microsoft Lobe, GenAI, LLMs, and traditional machine learning techniques. Designed and validated proof-of-concepts showcasing enterprise AI integration.
Trained custom image classification models using Microsoft Lobe. Exported to ONNX format for portable, cross-platform deployment. Performed local inference using ONNX Runtime for efficient, low-latency classification without cloud connectivity.
Integrated Azure AI Search for advanced semantic search capabilities. Added Semantic Search lookup controls to ASP.NET applications enabling natural language queries instead of rigid keyword matching.
Implemented AI Function Plugins via Semantic Kernel to dynamically enrich application responses with relevant contextual information. Built extensible plugin architectures for enterprise AI integration.
Leveraged AI Agents to dramatically increase unit test coverage across existing applications. Used AI Agents to generate front-end components and visual UI elements, accelerating development cycles.
Built person detection software using ML.NET applying classical ML techniques to real-time detection scenarios. Demonstrated practical applications of traditional machine learning beyond LLM-based approaches.
Developed prototypes for intelligent classification systems, semantic search experiences, automated code generation and testing, and AI-enhanced user interfaces serving as foundational accelerators for product development.