Giuliano Casale

I am an academic in the Department of Computing at Imperial College London. I lead the Quality of Service Research Lab (QORE), which focuses on quality assurance and resource management in distributed software systems and services.

Contact: Giuliano Casale Photo, Dept. of Computing, Imperial College London, Office: Huxley 432 [Getting here], g.casale (at) imperial.ac.uk.

Prospective PhD/post-doc applicants: I am willing to supervise new students with an interest for applications of modelling and AI/ML to distributed software systems, in particular to engineer QoS management systems.

Most PhD projects I supervise involve techniques such as AI/ML-based classification, inference and regression, anomaly detection, system modelling, Markov processes, and queueing analysis.

My group offers a lively and friendly environment to carry out postgraduate studies. Feel free to contact me if you wish to discuss opportunities or alternatively apply directly for PhD indicating me as a potential PhD supervisor. I have a record of sponsoring successful applicants for the President’s, China Scholarship Council, and Commonwealth Council studentships.

Departmental PhD scholarships are available for prospective PhD students, check out the departmental deadlines and the application guidelines. I am also interested to sponsor prospective applicants for Marie-Curie actions, EPSRC postdoctoral fellowships, and the Imperial College Research Fellowship.

Projects: My ongoing and recent projects are in the area of cloud applications, with a focus both on system design and resource management.

I have recently coordinated RADON (2019-21) and DICE (2015-18), two large H2020 collaborative project on serverless Function-as-a-Service (FaaS) and Big data applications. I also co-maintain a number of modelling tools for queueing theory and Markov processes, such as JMT, LINE, and KPC-Toolbox.

Teaching: I teach three courses at undergraduate and Master’s levels: 50008 Probability and Statistics, 60020 Simulation and Modelling, 70068 Scheduling and Resource Allocation. Students interested to continue working on these subjects through a final project are welcome to approach me to discuss this further.