Writing
Technical writing on industrial software engineering — air-gapped deployment, event-driven architecture, MQTT and Kafka, and applied AI in constrained environments.
A deep dive into building VAE-LSTM pipelines for predictive maintenance — the architecture, the engineering trade-offs, and what it takes to deploy industrial ML into constrained environments.
How a dual-head neural network on an EfficientNetB0 backbone reaches 93.2% accuracy in brain tumor classification. Complete methodology and evaluation from the study.
Why causal inference beats correlation for industrial anomaly detection — identifying root causes instead of just flagging symptoms, and moving from reactive alerts toward proactive diagnosis.
Practical guide to adapting LLMs for specialized business use cases. From data preparation to deployment strategies and performance optimization.
Transitioning from batch processing to real-time ML inference using Apache Kafka and FastAPI. Architecture patterns and production lessons learned.