Come rappresentante Automotive per ST ho avuto l’occasione di presentare dei casi reali nell’ambito automobilistico, dove siamo presenti con i nostri prodotti: ho conosciuto i maker e gli appassionati di tecnologia che li usano, ma soprattutto ho avuto modo di consolidare e tessere nuovi rapporti e collaborazioni con le diverse Squadre Corse universitarie presenti, ed ingaggiare nuovi partner interessati al loro utilizzo. Un’esperienza di grande valore da ripetere.
Exhibitors 2021
- FASHION & WEARABLES
- INTERNET OF THINGS
- PRODUCT DESIGN
- 3D PRINTING
- 3D SCANNING
- ART
- ARTIFICIAL INTELLIGENCE
- BIOLOGY
- EDUCATION
- HACKS
- KIDS & EDUCATION
- OPEN SOURCE
- ROBOTICS
- MUSIC & SOUND
- ARTISANS & NEW CRAFT
- RECYCLING & UPCYCLING
- STEAM PUNK
- GAMES
- SCIENCE
- YOUNG MAKERS (< 18)
- FOOD & AGRICULTURE
- CIRCULAR ECONOMY
- AEROSPACE
- HOME AUTOMATION
- NEW MANUFACTURING
- STARTUP
- WELLNESS & HEALTHCARE
- ENERGY & SUSTAINABILITY
- FABRICATION
- INDUSTRIAL AUTOMATION
- RETROCOMPUTING
- DRONES
- CULTURAL HERITAGE
- VIRTUAL REALITY
AI system for the optimization of online advertising campaigns
Adcube optimizes digital marketing campaigns across several advertising channels on one Platform. Its Machine Learning algorithms support marketers in making decisions and automatize tasks that impact on their business, like budget and targeting optimization. The platform provides the following tools:
- SpendOpt: it answers the hard question "How much should I invest?" that Advertisers ask themselves.
- BudOpt: it distributes the budget on a daily basis with the aim of maximizing revenues while respecting the business constraints defined by the customer.
- TargOpt: it allows to set campaigns directed to different classes of users, automatically creating them in the advertising platforms
Alessandro Nuara, CTO
Alessandro Nuara is a Ph.D. in Information Technology at the Department of Electronics, Information and Bioengineering of Politecnico di Milano and co-founder of ML-Cube. During his research, he gained a deep expertise on Online Machine Learning techniques and on their application to microeconomics environments, with a particular focus on online advertising and dynamic pricing. In 2019, he worked as an Applied Scientist Intern in the Machine Learning and Optimization team at Amazon (Seattle). He is currently teaching assistant of the course Data Intelligence Applications and he is working on industrial research projects as a research fellow at Politecnico di Milano.