Dr Alexandros Koliousis

About Dr Alexandros Koliousis

Alexandros Koliousis is an Associate Professor in computer science at Northeastern University London and a Senior Research Scientist at the Northeastern’s Institute for Experiential AI (EAI). He works on the design and implementation of scalable AI systems. Currently, Koliousis aims to develop a framework for the verification and testing of AI systems.

Koliousis has worked on high-performance data-parallel multi-GPU processing systems in the areas of deep learning and data stream processing. He has also researched topics including efficient natural language processing in hardware and complex event processing for network and system management.

Before joining Northeastern, Koliousis held an industry research position at the semiconductor company Graphcore and academic positions at the Imperial College London and the University of Glasgow. He earned his doctoral degree in computing science and his Master of Science in advanced computing science from the School of Computing Science at the University of Glasgow.

Qualifications

Alexandros received his PhD (Computing Science, 2010) and MSc (Advanced Computing Science, 2005) degrees from the School of Computing Science at the University of Glasgow.

He received his undergraduate degree (Computer Engineering, 2003) from the Alexander Technological Educational Institute of Thessaloniki, Greece.

Email: alexandros.koliousis@nchlondon.ac.uk

Website: akoliousis.com

Dr Alexandros Koliousis's Research

Alexandros’s research interests lie at the intersection of scalable data systems and deep learning. He has worked on the design and implementation of data-parallel processing systems that best utilise hardware accelerators with applications to deep learning (Crossbow, 2019) and data streaming (Saber, 2016).

He has also worked on complex event processing for home network management; and routing algorithms for wireless sensor networks, among other topics.

Selected publications

A. Koliousis, P. Watcharapichat, M. Weidlich, L. Mai, P. Costa, and P. Pietzuch • Crossbow: Scaling deep learning with small batch sizes on multi-GPU servers • Proc. VLDB Endow. 12, 11 • 2019 • DOI

A. Koliousis, M. Weildich, R. C. Fernandez, A. Wolf, P. Costa, and P. Pietzuch • Saber: Window-based hybrid stream processing for heterogeneous architectures • Proceedings of the 2016 ACM SIGMOD Conference on Management of Data • 2016 • DOI

A complete list of publications is available here.

Dr Alexandros Koliousis's Teaching

Alexandros is the Director of Graduate Studies in Computer and Data Science. He is teaching BA, MA and MSc courses on data and computer science. More information on teaching is available here.

He is always interested in supervising final year and Master’s projects related to his research.

Academic year 2020–2021

Course Leader • Foundations of Data Science • Level 4