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About Dr Alexandros Koliousis

Alexandros Koliousis is a Senior Lecturer in Computer Science. He joined NCH in 2020. Previously, he held research positions in industry (Graphcore, 2019-2020) and academia (Imperial College London, 2012-2019; University of Glasgow, 2010-2012).

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