Technology Innovation Institute (TII) has appointed Dr. Hakim Hacid as Chief Researcher of its AI and Digital Science Research Center (AIDRC), the home of the Falcon LLM series. Dr. Hacid previously served as Executive Director and Acting Chief Researcher at TII, after joining in 2022 from Zayed University. He brings expertise in AI, ML, data science, and information retrieval, with prior experience at Bell Labs and Macquarie University. Why it matters: The appointment strengthens TII's leadership in AI research and development, particularly for the Falcon series of open-source LLMs that have gained global recognition.
MBZUAI master's student Sayed Hashim is applying machine learning to improve cancer diagnosis and treatment, motivated by personal loss. He and fellow student Muhammad Ali developed algorithms for cancer type classification from multi-omics data, achieving over 96% accuracy. Their work, supervised by MBZUAI faculty, resulted in a published paper on multi-omics data representation learning. Why it matters: This research demonstrates the potential of AI and machine learning to advance cancer research and personalized medicine in the region.
MBZUAI researcher Karima Kadaoui is using AI to assist disadvantaged communities and languages, with a focus on democratizing NLP tasks for Arabic dialects. Her master's thesis focused on impaired speech recognition, converting disfluencies of individuals with speech disabilities into clear speech. She emphasizes the importance of diversity and inclusion in AI to avoid bias and ensure systems reflect the user distribution. Why it matters: This highlights MBZUAI's commitment to gender equity in STEM and the development of AI solutions tailored to the nuances of the Arabic language.
Hassan Sajjad from Dalhousie University presented research on exploring the latent space of AI models to assess their safety and trustworthiness. He discussed use cases where analyzing latent space helps understand the robustness-generalization tradeoff in adversarial training and evaluate language comprehension. Sajjad's work aims to build better AI models and increase trust in their capabilities by looking at model internals. Why it matters: Intrinsic evaluation of model internals will become important to improving AI safety and robustness.
The Symposium on Data Mining and Applications (SDMA 2014) was organized by MEGDAM to foster collaboration among data mining and machine learning researchers in Saudi Arabia, GCC countries, and the Middle East. The symposium covered areas such as statistics, computational intelligence, pattern recognition, databases, Big Data Mining and visualization. Acceptance was based on originality, significance and quality of contribution.
MBZUAI Adjunct Professor Mérouane Debbah was named a Highly Cited Researcher by Clarivate, placing him in the top 1% of researchers globally. Debbah, who joined MBZUAI's machine learning department in 2021, also serves as chief researcher at the Technology Innovation Institute (TII) in Abu Dhabi. His research focuses on multi-agent reinforcement learning, distributed AI, and applying AI to improve telecommunications, including reducing dead spots and improving energy efficiency. Why it matters: This recognition highlights the UAE's growing prominence in AI research, particularly in leveraging AI for advancements in telecommunications infrastructure and multi-agent systems.