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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 and Babaoglu, O., Predicting System-level Power for a Hybrid Supercomputer, in 2016 International Conference on High Performance Computing Simulation (HPCS), Innsbruck, Austria, 2016.
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.
A. Sirbu and Babaoglu, O., Towards Data-Driven Autonomics in Data Centers, in IEEE International Conference on Cloud and Autonomic Computing, 2015.
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.
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.
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.
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., Stages of Gene Regulatory Network Inference: the Evolutionary Algorithm Role, in Evolutionary Algorithms, InTech, 2011.
A. Sirbu, Ruskin, H. J., and Crane, M., Regulatory network modelling: Correlation for structure and parameter optimisation, Proceedings of The IASTED Technology Conferences (International Conference on Computational Bioscience), Cambridge, Massachusetts, pp. 3473–3481, 2010.
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.
A. Sirbu, Giannotti, F., Pedreschi, D., and Kertész, J., Public opinion and Algorithmic bias, ERCIM News, 2019.
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R. Trasarti, Baglioni, M., and Renso, C., DAMSEL: A System for Progressive Querying and Reasoning on Movement Data, in DEXA Workshops, 2009, pp. 452-456.
R. Trasarti, Bonchi, F., and Goethals, B., A new technique for sequential pattern mining under regular expressions, in SEBD, 2009, pp. 325-332.
R. Trasarti, Pinelli, F., Nanni, M., and Giannotti, F., Individual Mobility Profiles: Methods and Application on Vehicle Sharing, in Twentieth Italian Symposium on Advanced Database Systems, {SEBD} 2012, Venice, Italy, June 24-27, 2012, Proceedings, 2012.
R. Trasarti, Olteanu-Raimond, A. - M., Nanni, M., Couronné, T., Furletti, B., Giannotti, F., Smoreda, Z., and Ziemlicki, C., Discovering urban and country dynamics from mobile phone data with spatial correlation patterns, Telecommunications Policy, p. -, 2014.
R. Trasarti, Pinelli, F., Nanni, M., and Giannotti, F., Mining mobility user profiles for car pooling, in KDD, 2011, pp. 1190-1198.
R. Trasarti, Giannotti, F., Nanni, M., Pedreschi, D., and Renso, C., A Query Language for Mobility Data Mining, IJDWM, vol. 7, pp. 24-45, 2011.
R. Trasarti, Rinzivillo, S., Pinelli, F., Nanni, M., Monreale, A., Renso, C., Pedreschi, D., and Giannotti, F., Exploring Real Mobility Data with M-Atlas, in ECML/PKDD (3), 2010, pp. 624-627.
R. Trasarti, Guidotti, R., Monreale, A., and Giannotti, F., MyWay: Location prediction via mobility profiling, Information Systems, vol. 64, pp. 350–367, 2017.
F. Turini, Baglioni, M., Furletti, B., and Rinzivillo, S., Examples of Integration of Induction and Deduction in Knowledge Discovery, in Reasoning, Action and Interaction in AI Theories and Systems, vol. 4155, 2006, pp. 307-326.
F. Turini, Furletti, B., Baglioni, M., Spinsanti, L., and Bellandi, A., Ontology-Based Business Plan Classification, in Enterprise Distributed Object Computing Conference (EDOC), 2008.
F. Turini and Furletti, B., What else can be extracted from ontologies? Influence Rules, in Software and Data Technologies, Springer, 2012.
F. Turini, Baglioni, M., Furletti, B., and Rinzivillo, S., Examples of Integration of Induction and Deduction in Knowledge Discovery, in Reasoning, Action and Interaction in AI Theories and Systems, 2006, pp. 307-326.

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