Tianyao is a PhD student advised by Professor Gus Xia. His current research focuses on data-driven symbolist machine learning methods for music representation learning. He believes that the fractal structures introduced by logic systems in which recursion is enabled are vital for learning compositionally generalizable features from data. Before joining NYU Shanghai, he was an undergraduate student at ACM Honored Class at Shanghai Jiao Tong University.
Junyan Jiang is a PhD student at New York University Shanghai advised by Prof. Gus Xia. His research focuses on music understanding, topics including music information retrieval, music representation learning, and audio signal processing. Before attending the PhD program, he was a master student in the Machine Learning Department at Carnegie Mellon University. He is also a fan of logic puzzle games and programming contests.
Che (Watcher) Wang is a PhD student at New York University, advised by Professor Keith Ross. His current research focuses on improving sample efficiency and achieving a better understanding of deep reinforcement learning. He has been working as a teaching assistant for Machine Learning and Reinforcement Learning class. Before becoming a PhD student, Watcher was an undergraduate student at New York University Shanghai, as a member of the inaugural class of 2017. In addition to deep learning, he has also been interested in other topics such as game design, robotics and data visualization and have created a number of related projects during undergraduate study.
Ziyu Wang is a PhD student in GSAS Computer Science program. He is doing research under the advice of Prof. Gus Xia at NYU Shanghai. His research interest lies in the intersection of artificial intelligence and computer music, with special interest in understanding the creativity inside music composition and performance. Currently, he is working on deep generative models and music representation learning. He is also a musician, with plenty of experience in piano and Chinese Erhu performance and conducting.
Yanqiu Wu is a fourth-year PhD student, and she received her Bachelor’s degree in Computer Science from New York University Shanghai in 2017. Yanqiu is conducting research in the field of deep reinforcement learning, with an emphasis on topics related to off-policy DRL algorithms, such as sample efficiency, extrapolation error in batch setting and squashing exploration problem.
Yiming is a 5th year PhD student in computer science working in machine learning under the direction of Prof. Keith Ross. Previously he received a BS and MS in statistics. Yiming's main research interest is in reinforcement learning with a focus on sample-efficient policy optimization and exploration under safety constraints.