Dr. Arash Amini

Biography

Arash Amini is an Associate Professor at the University of California, Los Angeles (UCLA), specializing in Statistics. He completed his PhD at the University of California, Berkeley, and subsequently undertook a post-doctoral fellowship at the University of Michigan, collaborating with noted researchers Martin Wainwright, Liza Levina, and Long Nguyen. His research primarily focuses on high-dimensional statistics, network models, and methods of optimization. Additionally, Amini has extensive interests in unsupervised and semi-supervised learning, clustering, community detection, causal graphical models, kernel methods, representation learning, and quantitative finance. His work often addresses complex statistical problems and the development of new statistical methodologies. Amini is actively engaged in the academic community, recently participating as a panelist at NeurIPS 2023, discussing the challenges of overfitting in over-parameterized models. His contributions include several R packages, notably in Bayesian community detection and hierarchical network clustering, contributing valuable tools for researchers in the field.

Research Interests

Experience