Tracy Becker

Vice Chair for Research & Technical Support
Ed & Diane Wilson Presidential Chair in Structural Engineering
Associate Professor
Research Interests
Structural dynamics and design, Earthquake engineering, Isolation & high-performance systems, Use of novel materials in design

781 Davis Hall

Office Hours

Monday 2-3pm

Wednesday 1-3pm

Becker headshot

Tracy Becker is an Associate Professor of Civil and Environmental Engineering at UC Berkeley. Becker’s research focus is structural dynamics and design and using novel materials in design. Her research group is developing a more comprehensive understanding of these systems that protect structural integrity in natural or man-made disasters, causing the least possible amount of damage


Ph.D., Civil and Environmental Engineering (SEMM) - University of California, Berkeley, 2011

M.S., Civil and Environmental Engineering (SEMM), University of California, Berkeley, 2007

B.S., Structural Engineering, University of California, San Diego, 2006

Becker’s research focuses on increasing the reliability of communities by facilitating the adoption of advanced structural systems. Her current research projects include the collapse behavior of isolated buildings, modeling updating in hybrid simulation, inverse structural design through ML, and the innovative design of steel components,  Here are a few of the research projects Becker is currently working on below:

isolated buildings pic

Collapse behavior of isolated buildings

While isolation performs outstandingly under design level motions, performance under extreme earthquakes is less well understood. Becker’s research group explores how design choices affect near-collapse performance through dynamic experimental friction tests pendulums bearing up to their limits and numerical incremental dynamic analysis to compare the effects of various isolation systems.

modeling pic

Modeling updating in hybrid simulation

Hybrid simulation, a method in which a poorly component of the structure is physically tested while the remainder is numerically modeled, has become a promising solution to the costs and physical limitations of large-size tests. However, this single test cannot represent the demands and behavior of the components’ class across the structure under extreme loading. Becker’s research in this area involves developing an enhanced model update to integrate information into the numerical model as it is learned over the course of the hybrid test.

ML picture

Inverse structural design through ML

While isolated structures offer enhanced, predictable behavior under typical ground motions, their behavior under extreme motions is complex and may not reach targeted goals as currently outlined in various codes. To address this design issue, Becker’s research group uses Gaussian process surrogate modeling to associate the probability of building limit states with the input design parameters.




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