Yang Feng (he/him/his)

Synopsis of Research in Shanghai (July 1 - July 26) :

Professor Yang Feng’s research project, specializing in high-dimensional multi- task and transfer learning inference, is a natural complement to NYU Shanghai's commitment to advanced data science and artificial intelligence. The project is structured around three pivotal goals. First, Professor Feng is  focused on developing innovative manifold-based multi-task learning algorithms, which are crucial for understanding and processing complex data structures. This aligns with NYU Shanghai's cutting-edge research in AI. Second, he aims to advance the field by clustering multi-task data in high-dimensional spaces, a challenging task given the presence of noise and outliers. This aspect of Professor Feng’s research is particularly relevant to the real- world applications of machine learning, an area NYU Shanghai is deeply invested in. Third, his work delves into exploring adaptive, robust learning and transfer techniques. These are essential for the development of flexible AI systems that can adjust to various scenarios and data environments, mirroring the dynamic nature of research at NYU Shanghai. Professor Feng’s potential collaboration with Dr. Christina Wang, an esteemed expert in deep reinforcement learning and large language models at NYU Shanghai, is an exciting prospect. This partnership stands to significantly enhance the depth and breadth of Professor Feng’s research. Dr. Wang's expertise in these areas will not only provide valuable insights into his project but also bridge the gap between theoretical research and practical, real-world applications. Together, their collaborative efforts are poised to contribute substantially to the fields of machine learning and AI.