Now
GenAI & Agents
The GenAI Epoch
Building with large language models, retrieval-augmented generation, tool-using agents, and orchestrated multi-agent systems.
Technology Evolution Across Three Decades of Applied AI
Over three decades, my work has followed the evolution of software and AI systems: from native algorithm development and multimedia systems to classical machine learning, deep learning at scale, and today's GenAI and agentic architectures. Here are some technologies I have used extensively across industry roles, applied research, and teaching.
2020s
ML at Scale
Deep Learning and Data Science at Scale
Distributed training on Spark clusters, model lifecycle management with MLflow, and production deployment across AWS and Azure.
2010s
ML & Deep Learning
Transition from Classical ML to Deep Learning
Moving from statistical models and gradient boosting to neural networks, applying both to finance, public safety, and automotive domains.
2000s
Multimedia & Vision
Computer Vision and Multimedia for Video Streaming and Client-Server Architectures
Integrating real-time video capture, codec pipelines, and vision algorithms into client-server systems for education, content delivery, and surveillance.
1990s
Systems & Algorithms
Native Algorithm Development
Algorithm design in C++ for signal processing, handwriting recognition, and network protocols on desktop and embedded platforms.