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Georgiou Chryssis
Department of Computer Science,
University of Cyprus,

1 Panepistimou Avenue

(+357) 22892745
(+357) 22892701

Miscellaneous Information

Ph.D., University of Connecticut, USA, 2003
Professor. Undergraduate studies at the University of Cyprus, Cyprus (B.Sc. in Mathematics, 1998). Graduate studies at the University of Connecticut, USA (M.Sc., 2002; Ph.D., 2003, both in Computer Science and Engineering). Before joining the University of Cyprus in 2004, he worked as a Teaching and Research Assistant at the University of Connecticut, USA (1998-2003). His research interests span the Theory and Practice of Fault-tolerant Distributed and Parallel Computing with a focus on Algorithms and Complexity. He has published more than 110 articles in journals and conference proceedings in his area of study and he has co-authored two books on Robust Distributed Cooperative Computing. In August 2021, he co-edited a book on the Principles of Blockchain Systems. Prof. Georgiou has served on several Program Committees of conferences in Distributed and Parallel Computing and on the Steering Committees of the International Symposium on Distributed Computing-DISC (2008-2010, 2010-2012) and the ACM Symposium on the Principles of Distributed Computing-PODC (2014-2015). He is currently chairing the Steering Committee of ACM PODC (2021-2024). In 2015 he served as the General Chair of PODC 2015, in 2017 he served as the Track Program Committee co-Chair (Stabilizing Systems: Theory and Practice Track) of SSS 2017. In 2018, 2019 and 2021 he served as the co-Chair of the workshop ApPLIED. In 2020 he served as the PC co-Chair of NETYS 2020. As of January 2018, he is on the Editorial Board of Information Processing Letters (subject area: Distributed Computing). Prof. Georgiou’s research has been funded by the University of Cyprus, the Cyprus Research and Innovation Foundation, and the European Commission.
Algorithms and Complexity, Parallel and Distributed Computing, Fault-tolerance and Dependability, Algorithmic Mechanism Design, and Machine Learning.