Alberto Urban Email & Phone Number

Soon after my M.Sc graduation in Biomedical Engineering I started to work for a R&D project in a small company, concerning the development of a brand new medical device for breast tumor screening Since November 2013 this is my main activity (even if meanwhile I had been handling other activities for the same company, such as FSR for Abbott hematology devices in northern Italy). In all these years I covered several scientific aspects of the project: 1) Study the state of the art of Breast Optical Imaging in literature.2) Realization of simple electrical and pneumatic circuits for the first prototypes of the device.3) Definition of procedures for measuring the performances of the device, mainly concerning pneumatic aspects (i.e.: measuring pressures with sensors and analyzing the curves obtained).4) Development and testing of Optical Phantoms in collaboration with Chemistry Department of Politecnico di Milano.5) Development of the Imaging Elaboration SW (in Matlab environment) in collaboration with Math Department of Università degli Studi di Milano.6) Optimization of the code in collaboration with consultant companies (i.e: Moxoff spa, Deix srl).7) Analysis of data from clinical trials using self-made GUI tools (still in Matlab environment). Matlab is the main programming language I have worked with. Nevertheless, my curiosity and the will of improving let me start in July 2022 a couple of courses on Codecademy platform concerning Data Analysis and Machine Learning, where I learnt how to use also SQL and Python language.Apart from the fundamentals of Python, thanks to those courses I entered in contact with a lot of libraries in Python, such as Numpy, Pandas, Matplotlib, Seaborn, Scikit-learn. In particular, with the latter I have learnt several Machine Learning algorithms, both supervised (Linear regression, Logistic regression, K-nearest neighbors, Decision tree, Random Forest, etc) and unsupervised (PCA, K-means clustering), together with other important concepts such as “Exploratory Data Analysis” and “Feature Engineering”. In addition, I also started to deepen my knowledge in Deep Learning studying by myself books such as “Deep Learning with Python” by François Chollet and “Probabilistic Deep Learning” by Olivier Dürr and others, entering in contact with TensorFlow and Keras libraries.