Innovation at USP
Innovation ecosystem • Incubators CIETEC | SUPERA | ESALQTec | Habits | UNITec • Innovation observatory • Center for Entrepreneurship at USP (NEU) • Center for Technological Policy and Management (PGT) • 04 EMBRSPIIs Unities (federal core innovation centers) • 11 CEPIDs Unities (state core research and innovation centers) • InovaHC (Innovation Center of Medical Clinics Hospital) • InovaInCor (Innovation Center of Heart Institute)
Our estrategic vision
Multidisciplinar approach
Governance model Corporate executive administration Superior Council Result-oriented representing society management
Excellence and transparency • Mobilization of the best teams and infrastructure, of companies and research institutions, from Brazil or abroad • Easy access to entire USP expertise and infrastructure • Transparent management of resources and projects • Permanent communication with the scientific community, focusing on full dissemination of results to society
Push for startups • Encourage and promote the development of companies that have innovation as the basis of their business • Pre-accelaration tutoring
digital technologies • gaming technology • user experience • factory of future • industry 4.0 • digital solutions • artificial intelligence • machine learning
• development of new pathways for the production of molecules from biotechnological pathways, ie the development of a new chemical industry from the biomass. • analysis and modeling of biological systems (omic techniques)
• It is an initiative that aims to promote the development of solutions for high-impact problems in science, economy and society • interdisciplinary approach with multidisciplinary teams in collaboration with the public and private sector
• science as major • freshmen students from any course can join in • multi and interdisciplinary education focused on scientific research and technological advances
• advanced prototyping shop • support for designing, inventing and building
• USP center of entrepreneurship • support for the development of high-tec startups • place for networking and collaboration
• development and use of computational tools and analysis of high-throughput data • hypotheses raised by analyzing big data (data- driven research)
• improve decision-making and diagnostic processes • use of large databases using machine learning techniques • development of artificial intelligence
Thank you inova@usp.br catalani@usp.br
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