Jack C P Cheng
Biographic Data
| ID | 6319676 |
|---|---|
| NAME | Jack C P Cheng |
| GIVEN NAMES | Jack C P |
| FAMILY NAME | Cheng |
| SIGNATURE | CHENG J C P |
| AFFILIATIONS | Hong Kong University of Science and Technology |
| ORCID | 0000-0002-1722-2617 |
| VERIFIED | Yes |
| TOTAL WORKS | 8 |
| TOTAL CITATIONS | 13 |
| AUTHOR COUNT | 8 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2009 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Enhancing geo-localization for crowdsourced flood imagery via LLM-guided attention
Large language model applications in disaster management: An interdisciplinary review
Disasters increasingly challenge urban resilience, demanding advanced computational approaches for effective information management and response coordination. This interdisciplinary review systematically assesses Large Language Model (LLM) applications in disaster management, analyzing 70 LLM-focused studies within the broader landscape of AI-driven disaster management. Our analysis establishes a phase-based framework spanning detection, tracking…
Developing Strategic and Collaborative Community–Academic Partnerships to Improve Community Health, From Moving Upstream to Getting at the Root
Community partners have experienced inequity and lack of transparency in funding practices. Funding for community partners is a critical component of community-engaged research, as it influences community trust and opportunities. We compared contextual and site-specific factors at 2 centers (in New York City; Los Angeles and Orange Counties, CA) with different community-funding approaches, which influence institutional capacity to partner with an…
Secure environmental, social, and governance (ESG) data management for construction projects using blockchain
Cost and environmental impact estimation methodology and potential impact factors in offshore oil and gas platform decommissioning: A review
A Lag-FLSTM deep learning network based on Bayesian Optimization for multi-sequential-variant PM2.5 prediction
Analyzing driving factors of land values in urban scale based on big data and non-linear machine learning techniques
Improving access to and understanding of regulations through taxonomies
Improving access to and understanding of regulations through taxonomies
A Lag-FLSTM deep learning network based on Bayesian Optimization for multi-sequential-variant PM2.5 prediction
Analyzing driving factors of land values in urban scale based on big data and non-linear machine learning techniques
Cost and environmental impact estimation methodology and potential impact factors in offshore oil and gas platform decommissioning: A review
Secure environmental, social, and governance (ESG) data management for construction projects using blockchain
Large language model applications in disaster management: An interdisciplinary review
Disasters increasingly challenge urban resilience, demanding advanced computational approaches for effective information management and response coordination. This interdisciplinary review systematically assesses Large Language Model (LLM) applications in disaster management, analyzing 70 LLM-focused studies within the broader landscape of AI-driven disaster management. Our analysis establishes a phase-based framework spanning detection, tracking…
Developing Strategic and Collaborative Community–Academic Partnerships to Improve Community Health, From Moving Upstream to Getting at the Root
Community partners have experienced inequity and lack of transparency in funding practices. Funding for community partners is a critical component of community-engaged research, as it influences community trust and opportunities. We compared contextual and site-specific factors at 2 centers (in New York City; Los Angeles and Orange Counties, CA) with different community-funding approaches, which influence institutional capacity to partner with an…
Enhancing geo-localization for crowdsourced flood imagery via LLM-guided attention
Computer Science (6 works) · Business (5 works) · Engineering (3 works) · Artificial Intelligence (2 works) · Environmental Science (2 works) · Machine learning (2 works) · Mathematics (2 works) · Political science (2 works) · Statistics (2 works) · Advanced Text Analysis Techniques (1 works)