Allen Liu

Allen Liu is an Assistant Professor of Computer Science at New York University Courant. His research spans algorithms and machine learning theory, with a focus on the foundations of machine learning and language models. He has also explored inverse problems in the sciences, particularly in quantum information. Liu completed his PhD in EECS at MIT, advised by Ankur Moitra, and was a Miller postdoctoral fellow at UC Berkeley. His work has been supported by several fellowships, including the NSF Graduate Research Fellowship, Hertz Fellowship, and Citadel GQS Fellowship. He earned his undergraduate degree in mathematics at MIT.

Allen Liu is a researcher at the Massachusetts Institute of Technology, focusing on Theoretical Machine Learning, Algorithms, and Quantum Computing. His work explores the intersection of machine learning and quantum information, with an emphasis on developing efficient algorithms for quantum state learning, Hamiltonian learning, and robust statistical methods. Liu's research also addresses challenges in tensor decomposition, community detection, and learning mixtures of models, often with a focus on adaptivity and computational efficiency. His contributions span both theoretical and applied aspects of machine learning, with a strong emphasis on algorithmic design and analysis.