معرفی
Bin Gu is a professor at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), specializing in machine learning and artificial intelligence. Previously affiliated with institutions including Nanjing University of Information Science and Technology (former position) and Nanjing University of Aeronautics and Astronautics (PhD 2011). His research focuses on optimization algorithms, spiking neural networks, federated learning, kernel methods, adversarial robustness, and neuromorphic computing.
Education: PhD in Computer Science (2011) from Nanjing University of Aeronautics and Astronautics. Prior affiliations include Tianjin University, Boston University, University of Science and Technology of China, and Southeast University.
Research Interests: Extensive work on machine learning theory and applications, including robust learning, federated systems, neural architecture design, and privacy-preserving techniques. Over 200 publications in top venues such as AAAI, NeurIPS, ICLR, ICML, KDD, and IEEE journals.
Publications Trends: Recent focus on spiking neural networks (SNNs), federated learning frameworks, and optimization methods for handling adversarial attacks and privacy constraints. Notable contributions include scalable algorithms for kernel-based learning, robust SVM formulations, and neuromorphic computing architectures.
Labs/Teams: Active in AI research groups focused on neural networks, optimization, and distributed learning systems. Collaborates with industry and academic partners on applied AI solutions.
