I am a Senior Lecturer (Associate Prof.) in Data Science at Manchester Metropolitan University.
My research spans from extracting hidden patterns and forming predictions on data from a variety of domains to engineering and optimising systems software for delivering maximum performance and efficiency.
Recently I have been working on implementing and optimising Big Data systems as well as applying data analytic techniques in the healthcare domain while working in close collaboration with industrial partners and the public sector.
For an up-to-date list of publications, visit my google scholar profile.
P. Yiapanis, G. Brown, M. Lujan (2016). Compiler-driven software speculation for thread-level parallelism. ACM Transactions on Programming Languages and Systems. 38(2),
A-K. Koliopoulos, P. Yiapanis, F. Tekiner, G. Nenadic, JA. Keane (2015). A Parallel Distributed Weka Framework for Big Data Mining Using Spark. In: BigData Congress. 27/6/2015. pp.9-16.
P. Yiapanis, D. Rosas-Ham, G. Brown, M. Luján (2013). Optimizing software runtime systems for speculative parallelization. ACM Transactions on Architecture and Code Optimization. 9(4),
P. Yiapanis, G. Brown, M. Lujan (2016). Compiler-driven software speculation for thread-level parallelism. ACM Transactions on Programming Languages and Systems. 38(2),
P. Yiapanis, D. Rosas-Ham, G. Brown, M. Luján (2013). Optimizing software runtime systems for speculative parallelization. ACM Transactions on Architecture and Code Optimization. 9(4),
J. Singer, G. Brown, M. Luján, AC. Pocock, P. Yiapanis (2009). Fundamental Nano-Patterns to Characterize and Classify Java Methods. LDTA. 253(7), pp.191-204.
R. Salehnejad, R. Allmendinger, Y-W. Chen, M. Ali, A. Shahgholian, et al. P. Yiapanis, M. Mansur. (2017). Leveraging data mining techniques to understand drivers of obesity. In: 2017 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). 23/8/2017.
A-K. Koliopoulos, P. Yiapanis, F. Tekiner, G. Nenadic, JA. Keane (2015). A Parallel Distributed Weka Framework for Big Data Mining Using Spark. In: BigData Congress. 27/6/2015. pp.9-16.
D. Rosas-Ham, I. Herath, P. Yiapanis, M. Luján, I. Watson (2012). Architectural Support for Exploiting Fine Grain Parallelism. In: HPCC-ICESS. Liverpool, ENGLAND, 25/6/2012. pp.61-70.
N. Ioannou, J. Singer, S. Khan, P. Xekalakis, P. Yiapanis, et al. AC. Pocock, G. Brown, M. Luján, I. Watson, M. Cintra. (2010). Toward a more accurate understanding of the limits of the TLS execution paradigm. In: IISWC. 2/12/2010. pp.1-12.
A. Pocock, P. Yiapanis, J. Singer, M. Luján, G. Brown (2010). Online Non-stationary Boosting. In: MULTIPLE CLASSIFIER SYSTEMS, PROCEEDINGS. Cairo, EGYPT, 7/4/2010. pp.205-214.
AC. Pocock, P. Yiapanis, J. Singer, M. Luján, G. Brown (2010). Online Non-stationary Boosting. In: MCS. pp.205-214.
P. Yiapanis, DJ. Haglin, AM. Manning, K. Mayes, JA. Keane (2008). Variable-grain and dynamic work generation for Minimal Unique Itemset mining. In: CLUSTER. Tsukuba, JAPAN, 29/9/2008. pp.33-41.
Current project involvement:
Past project involvement: