The “Science, Technology and Innovation Action Plan” is one of the most ambitious programmes launched by the Shanghai municipality over a decade ago, with the purpose of supporting local actors to expand scientific research and innovation activities in various sectors. The Plan follows the development priorities and objectives of the Shanghai municipality as outlined in the local 13th Five-year Plan for Science, Technology and Innovation.
The Plan is divided into several programmes focusing on specific sectors or activities, including one focusing on Artificial Intelligence.
Enterprises; universities; research institutes
Shanghai Municipal Science and Technology Commission
Fundamental theories of AI
- Ultra high-dimensional machine learning for commonsense knowledge
- New generation machine learning
Research and application of key core AI technologies
- Application of key AI technologies to empower the transports sector
- Application of key AI technologies to empower the healthcare sector
- Application of key AI technologies to empower the society
The specific amount of funding allocated is not specified
- Independent legal personality in Shanghai;
- The proposed PI should be a regular employee of the entity that submits the application. The proposed PI cannot have more than two ongoing municipal-level projects at the time of application;
- The applicant and the proposed PI should not have any negative records;
- Consortia are required to provide additional funding, generally at least half of the project budget;
- Priority granted to proposals which have already obtained commitment from district-level authorities to provide additional funding;
- Proposals that have already received funding from other channels at either the municipal or district level, are not eligible.
Date of publication
9 May 2019
Deadline for submitting applications
5 June 2019
Applications are submitted through the web portal of the Shanghai government. An official account should be created on the system in order to submit applications.
- Applied research