MBZUAI visiting professor of computer vision, Xiaojun Chang, has been named to Clarivate’s 2024 Highly Cited Researchers list, placing him in the top 1% of researchers worldwide. Chang has accumulated over 18,000 citations from around 200 papers, with his research focusing on multimodal foundation models and their applications to embodied AI and healthcare. Chang also holds positions at the University of Technology Sydney and RMIT University in Australia. Why it matters: This recognition highlights MBZUAI's growing impact and its role in fostering interdisciplinary collaboration and innovation in AI research, attracting further opportunities and collaborations.
KAUST Associate Professor Xiangliang Zhang presented her work on mining streaming and temporal data at the International Joint Conference on Artificial Intelligence and the European Conference on Artificial Intelligence (IJCAI-ECAI-18) in Stockholm. Her talk, "Mining Streaming and Temporal Data: from Representation to Knowledge," summarized her research on mining data streams. Zhang directs the KAUST Machine Intelligence and kNowledge Engineering (MINE) group, which focuses on knowledge discovery from large-scale data. Why it matters: Showcases KAUST's contributions to AI research and highlights the university's growing recognition within the international AI community.
Xiaohang Li has joined the Computer, Electrical and Mathematical Science and Engineering Division at KAUST as an assistant professor of electrical engineering. He will focus on research and teaching within the electrical engineering domain. Why it matters: The appointment strengthens KAUST's faculty expertise in electrical engineering and related areas.
KAUST Assistant Professor Xiaohang Li has won the 2018 Harold M. Manasevit Young Investigator Award for his work in metal-organic chemical vapor deposition (MOCVD) growth of semiconductors. Li will receive the award at the 19th International Conference on Metalorganic Vapor Phase Epitaxy in Japan. The award recognizes Li's contributions to deep UV lasers, B-III-N alloys, III-oxides, and blue and green emitters. Why it matters: This award highlights KAUST's growing prominence in advanced semiconductor research and its potential impact on the optoelectronics industry.
Dr. Tony Chan has assumed the role of President of KAUST on September 1st. He previously led the Hong Kong University of Science and Technology (HKUST) for a decade. Prior to that, he had a distinguished career in computational mathematics and held leadership positions at the U.S. National Science Foundation and the University of California, Los Angeles. Why it matters: Chan's appointment signals KAUST's continued focus on advancing its global research agenda and contributing to Saudi Arabia's Vision 2030.
Chuan Xia, a Ph.D. student at KAUST, won the best poster award at the International Conference on Materials for Advanced Technologies (ICMAT) 2017. The poster's topic is not specified in the provided text. Why it matters: Recognition at ICMAT highlights KAUST's contributions to materials science and engineering.
Dr. Kun Zhang from Carnegie Mellon University will spend 2022 as a Visiting Associate Professor in the Machine Learning Department at MBZUAI. Zhang's research focuses on causal discovery and causality-based learning, with applications in neuroscience, computer vision, computational finance, and climate analysis. He aims to develop methods for automated causal discovery from various kinds of data. Why it matters: This appointment strengthens MBZUAI's machine learning department and promotes research in causal AI, which is crucial for understanding and predicting complex systems.
MBZUAI Professor Kun Zhang received a Test of Time Award Honorable Mention at ICML 2022 for his 2012 paper “On causal and anticausal learning." The paper, co-authored with researchers from the Max-Planck Institute, is considered foundational for causal learning in machine learning. Zhang's work demonstrated the importance of causality for machine learning tasks, helping to shift views in the field. Why it matters: This award highlights the growing recognition of causal AI research and MBZUAI's role in advancing the field.