Current NYU Shanghai Global Research Initiatives Fellows

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.

Synopsis of Research in Shanghai (September 23 - December 13):

Focusing on the Qing dynasty (1644-1912), Jinyi Liu’s dissertation examines the court production of marble quarried from Fangshan, a county at the southwest corner of Beijing. Stones extracted from this region have been mainly known as hanbaiyu (Chinese white jade) and qingbaishi (blue-white stone). Rather than focusing on static, finished artifacts, Liu explores the ever-evolving life of the material, tracing the transformations of the stone from a block of freshly extracted raw material to an intricately carved sculpture. This project offers new insights into the studies of Qing and East Asian art through experimenting with a conceptual framework that places the material, the environment, and human labor as agents in a network of shared authorship. 

Synopsis of Research in Shanghai (July 5 - July 26):

The primary goal of Charlene Chou’s research project is to enhance the discovery of East Asian e-journal collections by loading title-level resource descriptions into the library system Alma. This will make these e-resources more easily accessible in the NYU Shanghai Library catalog, supporting research, teaching, and learning within the NYU community. For instance, the Dacheng Old Journal Full-Text Database contains 1.3 million journal articles from over 7,000 journals. In the current catalog, only the database titles can be found,not individual journal titles. However, with the improvement, students or users will be able to locate articles needed for research in the Dacheng database by finding the catalog record for the specific journal title, as cited in the primary source. While conducting this research project at NYU Shanghai, Chou will be able to communicate and collaborate with her colleagues to review and streamline workflows in Alma, the new library system, which recently migrated and went live on January 4, 2024. 

Synopsis of Research in Shanghai (September 16 - December 15):

Véronique Mickisch’s dissertation explores the emergence of what she calls Stalinist economics in the Soviet Union in the 1920s and 1930s. Mickisch defines Stalinist economics as a particular form of economics that was rooted in the traditions of statism and economic autarky. Mickisch places the shift in the USSR in the 1920s in the context of the international trend toward economic autarky that was initiated by World War I.  At the same time, the Soviet example shows that alternatives to economic autarky did exist. Soviet economics had a variety of faces, but Stalinist economics was enforced through increasingly violent suppression of those who challenged it, culminating in the Terror of the 1930s. Mickisch’s research has significant implications for our understanding of the development not only of economics in the West but also in China. Here, political and economic thought after 1949 developed under significant influence of the trends that had emerged and become dominant in the Soviet Union. Meanwhile, alternative, internationalist approaches to Marxist economics whose proponents were murdered in the Great Terror remained unknown. 

Synopsis of Research in Shanghai (April 14 - May 16):

Prof. Jiang’s research falls into the general fields of control and dynamical networks, with a special focus on problems at the interface of AI/machine learning, nonlinear control and distributed feedback optimization for autonomous systems. His current research is focused on the following topics: Learning-based control aimed at learning adaptive optimal controllers directly from data with stability and robustness guarantees; Distributed feedback optimization for large-scale networks, such as robotic networks; Safe and resilient control for learning-enabled systems under uncertainty and DoS attacks.