Research: My research focuses on cloud computing. My goal is to develop rigorous methodologies to ensure that next-generation cloud services are scalable, reliable, and sustainable. Research topics I actively work on include: software engineering methods for cloud and Big Data applications, performance and reliability analysis, and DevOps. My personal and team’s recent research has received best paper awards at ACM SIGMETRICS 2017, IEEE/IFIP IM 2017, IEEE ICCAC 2016, ACM/SPEC ICPE 2016, and IEEE CLOUD 2015. A complete list of publications can be found in my CV, on DBLP and Google scholar.
Prospective PhD/post-doc applicants: check out the openings page if you are a prospective PhD, post-doc or intern. My team offers a lively and friendly environment to carry out postgraduate research, with weekly meetings and diverse research topics being carried out in parallel by doctoral and postgraduate students. Several departmental PhD scholarships are available for prospective PhD students, check out the application deadlines. Please contact me directly if you wish to apply for a PhD under my supervision.
Service: I am actively engaged in several international research communities, primarily in ACM SIGMETRICS, for which I am an executive board officer and an enthusiastic supporter, but also in the IFIP Working Group 7.3, and in the IEEE COMSOC management community. I serve as associate editor for IEEE TNSM. My service record includes conference chairing for venues such as SIGMETRICS/Performance, MASCOTS, ICPE, QEST, VALUETOOLS, and ICAC. I am also an organiser of the QUDOS workshop series on DevOps.
Projects: I recently coordinated the EU Horizon 2020 project DICE (2015-18) on Big data software engineering. My team also recently participated to the EU FP7 project MODAClouds (2012-15) on multi-cloud applications and to the ESPRC OptiMAM project on service design and business processes. I co-maintain research software projects such as LINE, KPC-Toolbox and Java Modelling Tools (JMT), a suite of applications for performance engineering based on queueing models. JMT is used in academic courses worldwide and in the IT industry.