Dr. Pengtao Xie joins MBZUAI as an assistant professor focusing on healthcare and machine learning, inspired by human learning. He is developing automated machine learning methods for healthcare, such as neural architectures for pneumonia detection from chest X-rays. His method achieves state-of-the-art performance with 95% accuracy and is under review by Nature Scientific Report. Why it matters: This appointment strengthens MBZUAI's research capabilities in healthcare AI and signals the university's commitment to attracting top global talent to Abu Dhabi.
Dr. Zeke Xie from HKUST(GZ) presented research on noise initialization and sampling strategies for diffusion models. The talk covered golden noise for text-to-image models, zigzag diffusion sampling, smooth initializations for video diffusion, and leveraging image diffusion for video synthesis. Xie leads the xLeaF Lab, focusing on optimization, inference, and generative AI, with previous experience at Baidu Research. Why it matters: The work addresses core challenges in improving the quality and diversity of generated content from diffusion models, a key area of advancement for AI applications in the region.
This article summarizes a talk by Erci Xu on doing computer systems research, focusing on idea generation and paper writing. Xu shares experiences on developing research ideas and provides a tutorial on academic writing principles. He has published 20 papers in venues like OSDI, FAST, ATC, and Eurosys and received awards including two FAST Best Paper Awards. Why it matters: The talk and summary offer valuable guidance for researchers in the Middle East, particularly those at institutions like MBZUAI, on how to conduct impactful computer systems research and effectively communicate their findings in top-tier academic publications.
Dr. Hao Dong from Peking University presented research on addressing the challenge of limited large-scale training data in embodied AI, particularly for manipulation, task planning, and navigation. The presentation covered simulation learning and large models. Dr. Dong is a chief scientist of China's National Key Research and Development Program and an area chair/associate editor for NeurIPS, CVPR, AAAI, and ICRA. Why it matters: Overcoming data scarcity is crucial for advancing embodied AI research and enabling more sophisticated robotic applications in the region.
This alumni focus piece highlights Pedro De La Torre, a 2014 Ph.D. graduate in Marine Science from KAUST. The content includes a KAUST logo, the phrase "KAUST Discovery", and a copyright notice. Why it matters: This is a routine alumni highlight, showcasing the impact of KAUST's Marine Science program.
Prof. Chun Jason Xue from the City University of Hong Kong presented research on optimizing mobile memory and storage by analyzing mobile application characteristics, noting their differences from server applications. The research explores system software designs inherited from the Linux kernel and identifies optimization opportunities in mobile memory and storage management. Xue's work aims to enhance user experience on mobile devices through mobile application characterization, focusing on non-volatile and flash memories. Why it matters: Optimizing mobile systems based on the unique characteristics of mobile applications can significantly improve device performance and user experience in the region.
MBZUAI President Eric Xing delivered a talk at Carnegie Mellon University on May 13, 2022, titled “From Learning, to Meta-Learning, to Lego-Learning — theory, systems, and engineering.” Xing discussed the development of a standard model for learning, inspired by the standard model in physics, which aims to unify various machine learning paradigms. Before joining MBZUAI, Xing was a professor at CMU and founder of Petuum Inc., an AI development platform company. Why it matters: This talk highlights MBZUAI's leadership in advancing theoretical frameworks for machine learning and its commitment to unifying different AI approaches.
Munther Dahleh, director at the MIT Institute for Data, Systems, and Society (IDSS), discussed his group's research on network systems at the KAUST 2018 Winter Enrichment Program. The research focuses on the fragility of large networked systems, like highway systems, in response to disruptions that may lead to catastrophic failures. Dahleh's team studies transportation networks, electrical grids, and financial markets to understand system interconnection in causing systemic risk. Why it matters: Understanding networked systems is crucial for building resilient infrastructure and mitigating risks in critical sectors across the GCC region.