KAUST held a research workshop on Optimization and Big Data, gathering researchers to discuss challenges and opportunities in the field. Speakers presented novel optimization algorithms and distributed systems for handling large datasets. The workshop featured 20 speakers from KAUST, global universities, and Microsoft Research. Why it matters: The event highlights KAUST's role as a regional hub for advancing research and development in big data and optimization, crucial for AI and various computational fields.
Dr. Jindong Wang from Microsoft Research Asia gave a talk at MBZUAI about the limitations of large foundation models, including adapting to real-world unpredictability and security concerns. He also discussed the need for interdisciplinary collaboration to evaluate the benefits and risks of these models. Dr. Wang shared his research and insights on how to harness the power of large foundation models while addressing their constraints and fostering responsible AI integration. Why it matters: This highlights MBZUAI's role in hosting discussions about responsible AI development and the challenges of deploying foundation models.
Eyal Ofek of Microsoft Research is researching how to augment users' senses and use scene understanding to create more inclusive workspaces, especially for remote work. His work involves designing applications flexible to changing environments and personalized to each user. Ofek's background includes computer vision, augmented reality, and leading research groups at Microsoft. Why it matters: This research aims to improve remote collaboration and adapt technology to individual user needs, which could enhance productivity and inclusivity in the evolving work landscape of the GCC region.
MBZUAI has placed over 90 master's and PhD students in internships at public, private, and multinational organizations globally. The internships span various AI disciplines, including computer science, CV, ML, NLP, and robotics. Students are undertaking placements at institutions like the Technical University of Darmstadt, Johns Hopkins University, and Microsoft Research Lab – Asia, as well as UAE entities like ADNOC and Dubai Police. Why it matters: This initiative strengthens the UAE's AI ecosystem by providing hands-on experience for students and addressing the growing demand for AI expertise in the region.
Monojit Choudhury, formerly of Microsoft Research and Project Turing, has joined MBZUAI as a professor of natural language processing. Choudhury's work at Microsoft involved developing NLP applications and responsible AI, including manually programming LLMs to prevent toxic or biased content. He was impressed by GPT-4's capabilities and believes academia is the best place for deep research in NLP. Why it matters: Choudhury's experience at Microsoft, including his work on responsible AI and LLMs, could contribute to MBZUAI's NLP research and the development of more inclusive LLMs.
Dr. Xinwei Sun from Microsoft Research Asia presented research on trustworthy AI, focusing on statistical learning with theoretical guarantees. The work covers methods for sparse recovery with false-discovery rate analysis and causal inference tools for robustness and explainability. Consistency and identifiability were addressed theoretically, with applications shown in medical imaging analysis. Why it matters: The research contributes to addressing key limitations of current AI models regarding explainability, reproducibility, robustness, and fairness, which are crucial for real-world applications in sensitive fields like healthcare.