Luisa Cutillo Email & Phone Number

Leeds, Gb

Leeds, England, United Kingdom

Leeds, United Kingdom

I am Programme Manager for the following Masters programmes in the School of Mathematics:Data Science and Analytics MScStatistics MScStatistics with Applications to Finance MSc

London, England, United Kingdom

Project Title: " Data Skills Literacy for Educators"

Naples, Italy

As last relevant step of my career as Academic, before my MSC fellowship, I gained a position as assistant professor at the University of Naples Parthenope, at the faculty of Economics. Here I could start networking in the field of Mathematics applied to the Economy and experienced teaching Mathematics and Informatics.I was affiliated to the Department of Quantitative and Economic Sciences (DISAQ).I took academic leave from this position to pursue my lecturship at the University of… Show more As last relevant step of my career as Academic, before my MSC fellowship, I gained a position as assistant professor at the University of Naples Parthenope, at the faculty of Economics. Here I could start networking in the field of Mathematics applied to the Economy and experienced teaching Mathematics and Informatics.I was affiliated to the Department of Quantitative and Economic Sciences (DISAQ).I took academic leave from this position to pursue my lecturship at the University of Leeds. Show less

Manchester, Regno Unito

Collaboration with the Research team leaded by Professor Magnus Rattray.Main research areas: modelling genes co-oscillations, building biological networks

Sheffield, Regno Unito

European Project Under Horizon 2020.The aim of this project is to develop methods for analysis of time-series based on count data. l broaden the target of my project to general analysis of count time-series data such as clustering, classification, perturbations inference and machine learning over sequential count data. The project focus is on count data sets from ribonucleic acid sequencing (RNA-seq) time course experiments. Potential promising applications are in a variety of… Show more European Project Under Horizon 2020.The aim of this project is to develop methods for analysis of time-series based on count data. l broaden the target of my project to general analysis of count time-series data such as clustering, classification, perturbations inference and machine learning over sequential count data. The project focus is on count data sets from ribonucleic acid sequencing (RNA-seq) time course experiments. Potential promising applications are in a variety of multidisciplinary fields where event-counting is required, such as economics and biology. In economics, examples include the number of applicants for a job, or the number of labour strikes during a year. In biology, recent examples include high- throughput sequencing, such as RNA-seq and chromatin immunoprecipitation sequencing (ChIP-seq) analyses. The host for the fellowship is Professor Neil Lawrence at the University of Sheffield, United Kingdom, whose laboratory is essentially a multidisciplinary collaboration between the University’s Departments of Computer Science and the Sheffield Institute for Translational Neuroscience (SITraN). Professor Lawrence has a dual appointment across the two Departments and is uniquely placed to have access to live real time biological data being used in neurodegenerative research. Show less

Pozzuoli, Italy.

My work at TIGEM is the essence of my research inspiration. It is very challenging to deal with rare diseases providing and developing effective tools for data analysis and interpretation. The work at Tigem was very productive and I have and ongoing fruitful collaboration with them, under the supervision of Professor Diego Dibernardo.

Naples, Italy

I developed Models for image data analysis and classification.

Phd Computational Science And Informatics, Mathematics And Statistics

Activities and Societies: During My PhD I developed my research in the field of Statistics and Applied Mathematics under the supervision.

Laurea In Mathematics, Mathematics, 110/110 Cum Laude