I am an academic in the Department of Computing at Imperial College London. My research focuses on modelling 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 together with my team advanced methods based on stochastic and probabilistic models (e.g., queueing models, caching models, hidden Markov models, stochastic agents, …), as well as statistical, AI and machine learning techniques (e.g., maximum likelihood estimation, Markov Chain Monte Carlo, Variational inference, Reinforcement learning / Gaussian processes, …) for mining, predicting, and optimizing system characteristics.
Prospective PhD/post-doc applicants: I am willing to supervise new students with an interest for machine learning and probabilistic modelling. My team offers a lively and friendly environment to carry out postgraduate studies. Feel free to 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 area of Cloud computing, where modeling and simulation is used for both system design and runtime control. 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.
PhD admissions: for general inquiries related to PhD admissions in our department, please contact the PhD programme administrator, Dr Amani El-Kholy.