A delegation from the Indonesian Embassy visited MBZUAI on November 23, 2021, to learn about the university. Attendees included Dr. Hosni Ghedira, Ms. Reem Al Orfali, and Mr. Yaqoob Al Blooshi from MBZUAI, and Dr. Ir. Hammam Riza and Mr. Gatot Dwianto from the Indonesian National Agency for Research and Innovation. The visit aimed to establish closer relations and explore future collaboration opportunities. Why it matters: Such visits foster international partnerships in AI research and education, strengthening MBZUAI's global presence and potentially leading to joint projects and knowledge exchange.
The World AI Show Indonesia 2025 will be held in Jakarta, aiming to boost AI adoption across Southeast Asia. The event will feature AI experts, startups, and investors. Discussions will cover AI applications in various sectors including finance, healthcare, and smart cities. Why it matters: The conference highlights the growing importance of AI in Southeast Asia's economic development and digital transformation.
MBZUAI hosted a senior delegation from Indonesia to explore future cooperation. The delegation toured the MBZUAI campus in Masdar City and the Visitor Center. Professor Eric Xing presented the university’s objectives and strategic plans. Why it matters: This visit indicates MBZUAI's growing role in international AI education and collaboration, particularly with countries seeking to develop their AI capabilities.
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 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.
KAUST's Discovery Week featured a gala and awards ceremony. Professor Gilles Lubineau opened the proceedings at the 2017 WEP Final Gala. A Javanese shadow puppet performance of the “Ramayana Epic” was also part of the event. Why it matters: Showcases KAUST's commitment to cultural exchange alongside its research activities.
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.
A study investigated language shift from Tibetan to Arabic among Tibetan families who migrated to Saudi Arabia 70 years ago. Data from 96 participants across three age groups revealed significant intergenerational differences in language use. Younger members rarely used Tibetan, while older members used it slightly more, with a p-value of .001 indicating statistical significance.