Jiahuan Xia
Los Angeles, California,United States
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Dr. Jiahuan Xia is an Assistant Professor in the Department of Statistics and Data Sciences and Department of Computer Science (by courtesy) at The University of Texas at Austin. Her research interests lie at the intersection of statistics, machine learning, and optimization. She focuses on developing statistically sound and computationally efficient methods for modern complex data, with particular emphasis on high-dimensional statistics, reinforcement learning, causal inference, and trustworthy AI. Dr. Xia is committed to advancing data-driven decision-making and extracting meaningful insights from large-scale datasets across various scientific and engineering domains.
Professional Summary
Jiahuan Xia's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Notable Achievements
NSF CAREER Award Recipient
Awarded the prestigious National Science Foundation (NSF) CAREER award for her research on 'Principled Reinforcement Learning with General Function Approximation: Towards Trustworthy Sequential Decision-Making'.
Simons-Berkeley Research Fellow
Participated as a Research Fellow at the Simons Institute for the Theory of Computing, contributing to programs on the foundations of data science and deep learning.
Multiple Publications in Top-tier Venues
Authored and co-authored numerous papers in leading statistics, machine learning, and operations research journals and conferences, such as JASA, NeurIPS, ICML, and Management Science.
PhD from University of California, Berkeley
Completed her doctoral studies in Statistics from UC Berkeley, where she developed foundational work in high-dimensional statistical inference.
Educational Background
Bachelor of Science (BS), Economics/Business
Brandeis University - Year 2011
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Company Overview
Milly Rock GroupMilly Rock Group is an entity for which detailed public information regarding its operations, employee count, founding details, specific location, funding, and stock market presence is not readily available through standard web searches. It does not appear to be a publicly-traded company or have publicly disclosed significant funding rounds. The name is more commonly associated with a popular dance move.
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