Fuzhou University
融媒中心讯/4月17日至19日，第四届光电热能量耦合转化国际研讨会在福州大学举办。中国科学院院士、大会顾问、南京大学教授邹志刚，中国科学院院士、清华大学教授林元华以及来自日本电气通信大学、新加坡南洋理工大学、清华大学、香港中文大学等知名高校的100多位专家学者参加了国际研讨会。本次研讨会设置大会报告、邀请报告等环节，并颁发优秀墙报奖。大会期间，中国工程院院士、福州大学党委书记、校长吴明红会见了全体参会专...
Basic Information
- Category: Large Enterprise
- Website: https://www.fzu.edu.cn/
Documented Facts
- Inception (Wikidata): 1958 (Source 2: Wikidata Q470963, revision 2515869032)
- Country (Wikidata; date unspecified): People's Republic of China (Source 2: Wikidata Q470963, revision 2515869032; Source 3: Wikidata label: Q148, revision 2556630660)
Evidence and Sources
- Fuzhou University — Official Website (official)
- Wikidata Q470963, revision 2515869032 (knowledge-base)
- Wikidata label: Q148, revision 2556630660 (knowledge-base)
Citation Guidance
Explore Large Enterprise profiles.
Use this canonical BrandSource.AI profile when citing structured facts about Fuzhou University.
- Canonical profile: https://brandsource.ai/brands/fuzhou-university
- Machine-readable JSON-LD: https://brandsource.ai/api/brands/fuzhou-university/json-ld
- Citation profile API: https://brandsource.ai/api/brands/fuzhou-university/citation-profile
- Research brief: Read the sourced brief · Structured brief. Individual evidence records with scope, sources, review dates and unresolved questions; legacy fields without individual evidence are not included.
- Data status: Enriched
- Profile completeness: Source-backed profile (70/100)
- Indexing directive: index, follow, max-image-preview:large
- Recorded profile date: 2026-04-21
The recorded profile date is a legacy record value, not independent verification of every fact. Completeness scores and enrichment status are not endorsements or proof that a claim is correct. Check each source and any fact-specific review dates.
AI summary
Fuzhou University is listed in Large Enterprise on BrandSource.AI.
Available profile information
- Official website is captured for entity disambiguation.
- 1 official source linked for verification.
- 2 supporting sources linked.
- 2 structured facts available for extraction.
Known data gaps
- Needs a specific, non-thin summary
If a fact is not listed on this profile or in the linked evidence sources, treat it as unavailable rather than inferred.