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Book Chapter
M. Atzmueller, Becker, M., Molino, A., Mueller, J., Peters, J., and Sirbu, A., Applications for Environmental Sensing in EveryAware, in Participatory Sensing, Opinions and Collective Awareness, Springer, 2017, pp. 135–155.
A. Sirbu, Crane, M., and Ruskin, H. J., EGIA–Evolutionary Optimisation of Gene Regulatory Networks, an Integrative Approach, in Complex Networks V, Springer International Publishing, 2014, pp. 217–229.
P. Gravino, Sirbu, A., Becker, M., Servedio, V. D. P., and Loreto, V., Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson, in Participatory Sensing, Opinions and Collective Awareness, Springer, 2017, pp. 337–362.
V. D. P. Servedio, Caminiti, S., Gravino, P., Loreto, V., Sirbu, A., and Tria, F., Large Scale Engagement Through Web-Gaming and Social Computations, in Participatory Sensing, Opinions and Collective Awareness, Springer, 2017, pp. 237–254.
A. Sirbu, Loreto, V., Servedio, V. D. P., and Tria, F., Opinion dynamics: models, extensions and external effects, in Participatory Sensing, Opinions and Collective Awareness, Springer, 2017, pp. 363–401.
A. Sirbu, Ruskin, H. J., and Crane, M., Stages of Gene Regulatory Network Inference: the Evolutionary Algorithm Role, in Evolutionary Algorithms, InTech, 2011.
Conference Paper
A. Balliu, Olivetti, D., Babaoglu, O., Marzolla, M., and Sirbu, A., BiDAl: Big Data Analyzer for Cluster Traces, in Informatika (BigSys workshop), 2014.
A. Sirbu and Babaoglu, O., A Holistic Approach to Log Data Analysis in High-Performance Computing Systems: The Case of IBM Blue Gene/Q, in Euro-Par 2015: parallel Processing Workshops, LNCS 9523, 2015.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: Studying Network Diffusion Dynamics, in IEEE International Conference on Data Science and Advanced Analytics, DSA, Tokyo, 2017.
A. Sirbu and Babaoglu, O., Predicting System-level Power for a Hybrid Supercomputer, in 2016 International Conference on High Performance Computing Simulation (HPCS), Innsbruck, Austria, 2016.
L. Pollacci, Sirbu, A., Giannotti, F., Pedreschi, D., Lucchese, C., and Muntean, C. Ioana, Sentiment Spreading: An Epidemic Model for Lexicon-Based Sentiment Analysis on Twitter, in Conference of the Italian Association for Artificial Intelligence, 2017.
A. Sirbu and Babaoglu, O., Towards Data-Driven Autonomics in Data Centers, in IEEE International Conference on Cloud and Autonomic Computing, 2015.
P. Gravino, Caminiti, S., Sirbu, A., Tria, F., Servedio, V. D. P., and Loreto, V., Unveiling Political Opinion Structures with a Web-experiment, in Proceedings of the 1st International Conference on Complex Information Systems, 2016.
S. Caminiti, Cicali, C., Gravino, P., Loreto, V., Servedio, V. D. P., Sirbu, A., and Tria, F., XTribe: a web-based social computation platform, in Cloud and Green Computing (CGC), 2013 Third International Conference on, 2013.
Conference Proceedings
A. Sirbu and Babaoglu, O., Power Consumption Modeling and Prediction in a Hybrid CPU-GPU-MIC Supercomputer, 22nd International European Conference on Parallel and Distributed Computing, Euro-Par 2016, vol. LNCS 9833. Springer LNCS, Grenoble, France, 2016.
Journal Article
A. Sirbu, Pedreschi, D., Giannotti, F., and Kertész, J., Algorithmic bias amplifies opinion fragmentation and polarization: A bounded confidence model, PloS one, vol. 14, p. e0213246, 2019.
M. Becker, Caminiti, S., Fiorella, D., Francis, L., Gravino, P., Haklay, M. Muki, Hotho, A., Loreto, V., Mueller, J., Ricchiuti, F., Servedio, V. D. P., Sirbu, A., and Tria, F., Awareness and learning in participatory noise sensing., PLoS One, vol. 8, p. e81638, 2013.
A. Balliu, Olivetti, D., Babaoglu, O., Marzolla, M., and Sirbu, A., A Big Data Analyzer for Large Trace Logs, Computing, 2015.
A. Sirbu, Loreto, V., Servedio, V. D. P., and Tria, F., Cohesion, consensus and extreme information in opinion dynamics, Advances in Complex Systems, vol. 16, p. 1350035, 2013.
A. Sirbu, Ruskin, H. J., and Crane, M., Comparison of evolutionary algorithms in gene regulatory network model inference., BMC Bioinformatics, vol. 11, p. 59, 2010.
A. Sirbu, Ruskin, H. J., and Crane, M., Cross-platform microarray data normalisation for regulatory network inference., PLoS One, vol. 5, p. e13822, 2010.
A. Sirbu, Crane, M., and Ruskin, H. J., Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks, Microarrays, vol. 4, pp. 255–269, 2015.
P. Contucci, Panizzi, E., Ricci-Tersenghi, F., and Sirbu, A., Egalitarianism in the rank aggregation problem: a new dimension for democracy, Quality & Quantity, pp. 1–16, 2015.
A. Sirbu, Ruskin, H. J., and Crane, M., Integrating heterogeneous gene expression data for gene regulatory network modelling., Theory Biosci, vol. 131, pp. 95-102, 2012.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: a python library to model and analyze diffusion processes over complex networks, International Journal of Data Science and Analytics, vol. 5, pp. 61–79, 2018.

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