András István Nagy
Solution Architect at EPAM
Bio:
Andras is a hands-on Solution Architect who likes building usable software. He is interested in the challenges of scalability and distributed data processing, and working on cloud-native software. Used to work on the development of the LMAX (UK) low-latency exchange, on the data platform and data products for the German mobility startup FlixBus, on Smart City solutions for a US vendor, and various other international projects. Focusing on machine learning lately, Andras enjoys Functional Programming and a good tea.
Talk:
Finding bad bees in the hive
What are the challenges of building an anomaly detection solution for a large-scale IoT platform that manages tens of millions of devices? How are we using machine learning to detect when devices start behaving differently than they used to? Andras will talk about the design of a system for detecting anomalies in the network usage of IoT devices.