This thesis is devoted to experiment numerical optimization techniques on the D-Wave quantum computer We will simulate some combinatorial optimization problems and try to find innovative problem mapping in order to fully exploit the capacity of the quantum annealing machine.
Optimal decision trees
Based on a paper by D. Bertsimas, we experimented on discrete optimization algorithms for the optimal training of a decision tree. Assigned: July 2018, discussed December 2018 Student: Francesca Del Lungo
Scheduling staff in an hospital ward
This thesis dealt with developing an optimization algorithm for health care staff planning, based on a real ward requirements. Required skills: linear programming, possibly python, Java or C++ Student: Giulia Forasassi (based on an initial model prepared by Ayca Sarikaya,
Predicting drug consumption
Hospital wards are faced with day-to-day necessity to accurately forecast the consumption of drugs in order not to under stock nor to have too large inventories. This thesis explores the capabilities of some time series and some machine learning tools
Predicting the results of soccer matches via machine learning
How to use information collected during past matches in order to be able to predict the final result of a match? This thesis explores machine learning methods and features extraction towards the goal of being able to anticipate the final result.
Methods for epileptic seizures prediction based on features extraction from time series
Despite the progress of medicine in recent decades, epilepsy is a disease whose knowledge is still limited. About one third of patients with this disease continue to present crises despite pharmacological treatments, surgical interventions, and the medical assistance. The most
Clustering and feature selection methods for interplanetary space trajectory optimization
by Cosimo Casini Planning the optimal trajectory of an interplanetary space mission allows to save large amounts of fuel and time. Such a task can be modelled as a constrained global optimization problem. However, solving the resulting model is extremely
Data mining on students careers
We have got some data on students’ careers in the Engineerring school. We would like to apply some machine learning technique to find useful information inside. E.g., which part of the pre-admission test is correlated with the career? How to
Global Optimization on the GPU
Nvidia just donated a Titan X Pascal GPU to our Laboratory – we would like to experiment global optimization algorithms on this architecture. Skills required: python, possibly Cuda Candidate: Samuele Tamburi
Python Global optimization for space trajectories
Numerical experiments with global optimization for space trajectory planning, using a library developed at ESA Candidate: Tommaso Aldinucci Graduated: april 2017