Kode was established as an innovative start-up in 2012, by experts who have combined their skills in the fields of information technology, statistics and open data. Kode provides scientific advice and specific products in the field of data science: data mining, machine learning, omics and clinical sciences, chemoinformatics, industry 4.0, big data, socio-economic research. It also provides support to companies, institutions and public and private research organizations helping them, through data analysis, to maximize their know-how by developing predictive models, graphic displays and ad-hoc analysis tools.
WEB site: https://www.kode-solutions.net
Role of Kode Solutions in the project INGENE
Kode will participate in the development of software modules for the collection and storage of genetic data, of the measurements produced by imaging tests and of indices collected from the device for motion measurements. Furthermore, it will analyze data collected and will define the algorithms that will be implemented in the platform developed during the project. Concerning the device for motion measurements, Kode will collaborate in defining the functional and technical specifications of the interface software modules for its management, developing the software for processing data from the device. Following the analysis phase, the algorithms for studying movements will be implemented in the system.
Profile of staff engaged in the project
Marco Calderisi Graduated in Chemistry, PhD in Metabolomics, Research Fellow at the University of Modena and Reggio Emilia within the European Project “Drugs And PreCUrsor Sensing By ComplemenTing Low COst Multiple Techniques – CUSTOM” (VII Framework Program, Collaborative Project, 2010 -2013). He has an experience of more than 15 years as a consultant in research projects and projects in the industrial, clinical/pharmaceutical and environmental fields, as a lecturer in the field of chemometrics and of statistical programming. Author of more than 40 publications in national and international scientific journals, speaker at international scientific congresses. Specialized in data mining and machine learning, his main fields of interest include: industrial process control, experimental design for both process/product optimization and analytical methodologies, multivariate spectroscopic and spectrophotometric data processing, data management and modeling of data extracted from sensor networks in real-time or near real-time, in both outdoor and indoor systems.
Ilaria Ceppa is data scientist and software developer for Kode since 2014. She graduated in Computer Science with honors from the University of Pisa, where she specialized in Machine Learning, Data Mining and Natural Language Processing. Within Kode, she followed several data analytics and machine learning projects in many fields, including industrial process control and sensor data analysis. As part of these projects, she achieved a wide knowledge of several tools for data analysis and visualization, mainly based on R, Python and Javascript.