Carlotta Orsenigo
Carlotta Orsenigo is associate professor of Computer Science at
Politecnico di Milano, where she teaches courses in Machine Learning and Optimization.
After her graduation in Management Engineering at Politecnico di Milano in 2003, she started working as a research
fellow at the Dep. of Management, Economics and Industrial Engineering. In 2005 she became assistant professor
at the University of Milan, at the Dep. of Economics, Management and Quantitative Methods,
where she was in charge of courses in Mathematics, Financial Mathematics and Business and Marketing Intelligence.
From 2007 to 2013 she co-founded and was the scientific research responsible of the Business Intelligence Observatory (now Big Data & Business Analytics) of
the School of Management at Politecnico di Milano. From 2015 she is director of the International Master in Business Analytics and Data Science at MIP-Politecnico di Milano.
In 2018 she founded Aiblooms, a spin-off of Politecnico di Milano devoted to the development of software based on machine learning and artificial intelligence. In the same year, she founded the Milan chapter of Women in Machine Learning and Data Science (WiMLDS).
Her research activity has been focused on the development of novel models and methods for machine learning and pattern recognition and their application in several domains, ranging from biolife sciences to marketing and finance. Two major research strands were explored. From one side, the development of classification algorithms in the context of statistical learning theory. From the other, the design of nonlinear dimensionality reduction techniques for high-dimensional data embedding.
More recently, research efforts have been focused on two areas.
The first is the development of novel supervised learning methods in the context of affective computing. The second is the design and application of deep learning techniques for fault diagnosis and preventive mantainance.
Download the CV
Link to Google Scholar
Contact
Dipartimento di Ingegneria Gestionale - Politecnico di Milano
Room: 2.02 - Phone: (+39)02-23993970