MBZUAI is hosting a short course on developing open-source machine learning packages. The course will be led by Chih-Jen Lin, an affiliated professor at MBZUAI and distinguished professor at National Taiwan University, who has developed widely used ML packages like LIBSVM and LibMultiLabel. The course will cover topics such as starting a project, choosing functionalities, and identifying research problems from user feedback. Why it matters: This course can help improve the quality and usability of open-source machine learning tools coming from the region's research institutions.
KAUST, in collaboration with the Ministry of Communications and Information Technology (MCIT), will host the second edition of the MENA Machine Learning Winter School (MenaML) from January 24-29, 2026. The program will cover the latest developments in intelligent model engineering, AI for science, and high-efficiency computing technologies with representatives from 16 international institutions. 300 researchers will be selected from over 2,300 applicants to participate in the intensive academic program. Why it matters: The MenaML winter school strengthens KAUST's role as a regional hub for AI research and contributes to human capital development in AI across the MENA region.
KAUST is launching the Lifelong Learning Initiative (LLI), offering short, hands-on courses in areas like cybersecurity, food security, and semiconductors. The inaugural AI courses, designed for those with basic coding skills, will start with a "Machine Learning Bootcamp" in Riyadh from May 10-12. The KAUST Artificial Intelligence Initiative (AII) is developing AI class material in partnership with SDAIA. Why it matters: This initiative will upskill Saudi nationals and residents in critical areas like AI, supporting the Kingdom's development objectives and mobilization of the labor market.
MBZUAI hosted a panel discussion in collaboration with the Manara Center for Coexistence and Dialogue. Chaoyang He, co-founder of FedML, presented on federated learning (FL), covering privacy/security, resource constraints, label scarcity, and scalable system design. FedML is a platform for zero-code, cross-platform, secure federated learning across industries like healthcare and finance. Why it matters: Federated learning is an important subfield for the GCC region, allowing privacy-preserving model training across distributed data sources.
KAUST's Center of Excellence for Generative AI will host the fourth annual "Rising Stars in AI" Symposium from April 7-10, 2025. The symposium is designed for emerging researchers (PhD students, PostDocs, and early career faculty) to discuss AI research. Selected speakers will have their flights and hotel expenses covered. Why it matters: This event provides a platform for young AI researchers to present their work and network with peers, fostering innovation and collaboration in the field.