Research: My research focuses on modeling and simulation of IT services and business processes, with the goal of optimising their design, runtime control, and quality characteristics (performance, cost, reliability, …). In this context, I investigate advanced methods based on stochastic and probabilistic models (e.g., queueing models, caching models, hidden Markov models, agent-based formalisms, …), as well as statistical and machine learning techniques for mining and predicting system properties from monitoring data (e.g., likelihoods, MCMC, Variational inference, Bayesian optimization, …).
Prospective PhD/post-doc applicants: I am interested to supervise new students with a passion for machine learning and probabilistic modelling. My team offers a lively and friendly environment to carry out postgraduate studies. Please contact me if you wish to discuss opportunities.
Departmental PhD scholarships are available for prospective PhD students, check out the application deadlines. 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 areas of Cloud computing. I will soon start coordinating RADON (2019-21), a large collaborative project on serverless computing and Function-as-a-Service (FaaS). Recently completed projects include DICE (2015-18), OptiMAM (2015-16), iBids (2014-17), and MODAClouds (2012-15). I also co-maintain a number of research tools, such as JMT, LINE, and KPC-Toolbox.