A KAUST-led study published in PNAS quantifies the potential for increased food supply through coral reef restoration. Analyzing over 1,200 reef sites, the research estimates that rebuilding depleted fish populations could increase sustainable yields by nearly 50%. For Indonesia, this could translate to 162 million additional servings of reef fish annually. Why it matters: The study provides crucial evidence for governments to strengthen food security and ecosystem resilience through fisheries management, especially in regions facing high malnutrition.
KAUST is playing a central role in the G20 Coral Research and Development Accelerator Platform (CORDAP) to protect and restore corals globally. KAUST co-organized a G20 workshop with the UN Global Fund for Coral Reefs in Indonesia in August 2022. The workshop aimed to deliver policy recommendations on coral conservation to G20 Environment Deputy Ministers. Why it matters: This initiative highlights Saudi Arabia's commitment to addressing climate change and marine ecosystem preservation through international collaboration.
MBZUAI is developing AI-powered applications to help reduce malaria's impact in Indonesia, supported by Sheikh Mohamed bin Zayed Al Nahyan's Reaching the Last Mile initiative. The applications use sensory data fusion to create "digital twins" for precise weather forecasting and real-time environmental representation. AI and clustering analysis identify recurring features contributing to malaria outbreaks, enabling preventative measures and early treatment. Why it matters: This project demonstrates AI's potential in combating climate-sensitive diseases and improving public health in vulnerable regions.
MBZUAI's Dr. Fajri Koto presented research on overcoming challenges in NLP for underrepresented languages. His work includes creating multilingual datasets for Indonesian languages by engaging native speakers and finding that direct composition yields better results than translation. He also discussed vocabulary adaptation and zero-shot learning to address computational resource limitations, and emphasized the importance of datasets with local context for evaluating LLMs. Why it matters: This research addresses critical gaps in NLP for low-resource languages, providing insights and techniques to improve performance and cultural relevance in multilingual AI models within the region and globally.
MBZUAI researchers are developing AI applications for malaria prevention in Indonesia using sensory data fusion and digital twins. Another MBZUAI team is using machine learning and computer vision to detect cardiovascular disease from CT scans in collaboration with the University of Oxford. AI-powered remote patient monitoring is also being explored for proactive interventions and chronic disease management. Why it matters: These projects demonstrate the potential of AI to address healthcare challenges in underserved communities and improve disease prevention and management in the region.
MBZUAI faculty won two awards and published eight papers at the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (IJCNLP-AACL 2023). Alham Fikri Aji and Fajri Koto won the Best Resource Award for NusaWrites, a paper on constructing high-quality corpora for low-resource Indonesian languages by engaging speaker communities. Muhammad Abdul-Mageed won an Area Chair award for ProMap, a method for constructing bilingual dictionaries via language model prompting. Why it matters: This highlights MBZUAI's contribution to NLP research, particularly in low-resource languages and bilingual lexicon induction, and strengthens its position as a hub for AI research in the region.
MBZUAI faculty Alham Fikri Aji, Timothy Baldwin, and Fajri Koto won an Outstanding Paper Award at EACL 2023 for their paper "NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages." The paper introduces the first parallel resource for 10 Indonesian low-resource languages to boost performance in sentiment analysis and machine translation. The dataset is available on HuggingFace. Why it matters: This work highlights MBZUAI's commitment to advancing NLP research in low-resource languages, which can help preserve linguistic diversity and improve access to digital resources for speakers of underrepresented languages.
MBZUAI Professor Timothy Baldwin delivered the presidential keynote at the 60th Annual Meeting of the Association for Computational Linguistics (ACL). Baldwin also published three papers at the conference, including work on biomedical literature summarization, NLP for Indonesian languages, and understanding procedural texts. The papers address challenges such as reducing human effort in reviewing medical documents and digitally preserving Indonesian indigenous languages. Why it matters: Baldwin's contributions and leadership role at ACL highlight the growing prominence of MBZUAI and GCC-based researchers in the global NLP community.