Hi! I am Stelios and I enjoy working with algorithms that improve performance of large scale systems, exploring data science techniques that span the areas of distributed computing systems including Cloud & Internet of Things and applications of statistical learning algorithms for real time big data analytics.
My research directions are shaped around design and implementation of new tehcniques and adoption of existing trends for the current systems to become more efficient, interoperable, and reliable and to operate on massive data sets.
I am always looking for PhD students, so if you are interested to work in the area of distributed computing system drop me an email!
I am a lecturer performing research and teaching on large scale systems, data analytics and software engineering modules. I enjoy working on statistical learning applications for performance optimization for real time resource usage detection.
I worked on Cloud and big data analytics platforms to develop algorithms and platforms that span the areas of anomaly detection, virtual machine scheduling and Internet of Things. I awarded with a Mitacs Elevate fellowship in collaboration with Autodesk Canada.
I worked on European Union FP7 Projects (e.g. FI-STAR) for large scale Cloud federations and healthcare application development.
I also focused on Cloud scheduling for large scale distributed systems and techniques for virtual machine management.
Full list of publications in Google scholar
ADON 2018: International Workshop on Anomaly Detection ON the Cloud and the Internet of Things
Website: ADON 2018
December 10, 2018, as part of IEEE CloudCom 2018,
11-13 December 2018, Hilton Cyprus, Nicosia, Cyprus