Artificial Intelligence Driving the Future of Connected Cars
The emergence of Big Data, machine learning and advanced algorithms to imitate the cognitive functions of the human mind, has begun to simplify and enhance even the simplest aspects of our everyday experiences — and the automotive industry is no exception. Machine learning in the automotive industry has a remarkable ability to bring out hidden relationships among data sets and make predictions, which can lead to an increased level of accuracy in decision-making and improved performance. In this talk, we will be focusing on how machine learning algorithms can aid in effective planning and execution of predictive maintenance; predicting what is likely to fail and when it is going to happen. How it can accurately incorporate analysis results of customer feedback which helps in building vehicle and sub-systems performance for guiding future product design, and so forth.
Maggie Mhanna is a Data Scientist at Renault Digital, and a part-time university professor Leonardo da Vinci Engineering School. Her work now focuses on the application of data science and machine learning in the connected cars industry. Before joining Renault Digital, Maggie was doing a PhD at Centrale-Supélec in France allowing her to publish various articles in the area of machine learning, signal processing and information theory. Her thesis topic was entitled : "Privacy-Preserving Quantization Learning for Distributed Detection & Estimation with Applications to Smart Meters". Maggie earned a masters of science in renewable energies from Ecole Polytechnique, and an engineering degree in computer and communication from the Lebanese University.