Thamar Solorio from the University of Houston will discuss machine learning approaches for spontaneous human language processing. The talk will cover adapting multilingual transformers to code-switching data and using data augmentation for domain adaptation in sequence labeling tasks. Solorio will also provide an overview of other research projects at the RiTUAL lab, focusing on the scarcity of labeled data. Why it matters: This presentation addresses key challenges in Arabic NLP related to data scarcity, which is a persistent obstacle in developing effective AI applications for the region.
Thamar Solorio of MBZUAI served as general chair of EMNLP 2024, which hosted over 4,000 attendees. MBZUAI researchers presented nearly 50 studies, including one co-authored by Solorio and Monojit Choudhury that received an Outstanding Paper Award. Key themes included cultural awareness, machine-generated content detection, and LLM empathy and cultural representation. Why it matters: MBZUAI's strong presence at EMNLP highlights its growing influence in the international NLP research community and its focus on culturally aware AI.
Thamar Solorio from the University of Houston presented preliminary work on multimodal representation learning for detecting objectionable content in videos at MBZUAI. The research investigates two multimodal pretraining mechanisms, finding contrastive learning more effective than unimodal representation prediction. The study also assesses the value of common multimodal corpora for this task. Why it matters: This research contributes to the development of AI techniques for content moderation, an important issue for online platforms in the Middle East and globally.
Google.org is providing $1 million to MBZUAI to fund a research initiative led by Professor Thamar Solorio focused on addressing the “data divide” in AI for underrepresented languages, especially those in the MENA region. The project aims to create resource-lean AI models tailored to the sociocultural and linguistic realities of MENA, requiring less data and computational power. This initiative will also support the training of postdoctoral and early-career researchers at MBZUAI. Why it matters: The funding will help create AI technologies grounded in the linguistic nuances of the MENA region, rather than adapting Western models, while also democratizing AI development by lowering resource requirements.
An MBZUAI team led by Thamar Solorio and Monojit Choudhury received a Google Academic Research Award to study how AI can better understand and respond to human loneliness in digital spaces. The project will examine how loneliness is expressed online, how conversational agents can detect it, and what healthier AI companionship could look like in collaboration with Georgia Tech. The team aims to define digital loneliness and its expression in online conversations with AI. Why it matters: This research addresses a growing global issue by exploring the ethical and psychological implications of AI companionship, potentially leading to safer and more beneficial AI interactions.
MBZUAI has received a Google Academic Research Award to study how AI can better understand and respond to human loneliness in digital spaces. The project will examine how loneliness is expressed online, how conversational agents can detect it, and what healthier AI companionship could look like. The research aims to define digital loneliness and address the potential negative impacts of AI chatbots on users.
Former Saudi Research Science Institute (SRSI) student Abdullatif, now a junior at Berkeley, published a paper in the Journal of the American Chemical Society (JACS). The paper, "Isomerically Pure Tetramethylrhodamine Voltage Reporters," details the design, synthesis, and application of Rhodamine Voltage Reporters (RhoVRs). Abdullatif, who worked at KAUST during her SRSI program on carbon dioxide capture, plans to return for advanced studies. Why it matters: This highlights KAUST's role in nurturing young Saudi talent in STEM and contributing to high-impact scientific research.
Eduardo da Veiga Beltrame, bioinformatics lead at ImYoo (a Caltech spinout), presented on scalable methods for single-cell omics data analysis, including kallisto|bustools and scvi-tools. He highlighted their use in ImYoo's decentralized longitudinal study on Inflammatory Bowel Disease (IBD), where patients self-collect capillary blood samples. Beltrame also discussed his research on STEM education programs in Brazil as a visiting scholar at UC Berkeley. Why it matters: This highlights the growing trend of decentralized clinical studies leveraging advanced single-cell technologies for precision medicine, showcasing the potential of remote data collection and analysis in understanding complex diseases.