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Faculty

 

Hongjing Lu

hongjing@ucla.edu

Associate Professor, Department of Psychology

The University of California, Los Angeles

6552 Franz Hall, Office #: 310-206-2587

Hongjing's Curriculum Vitae

Postdocs

 

 

Steven Thurman

I am currently a Post-Doc in Dr. Hongjing Lu's Laboratory at UCLA. I received a Bachelor's degree from UCSD in 2006 and a PhD from UCI in 2011 studying Psychology (with a concentration in Cognitive Neuroscience). The focus of my research has been human visual perception, and specifically motion perception. Even more specifically I study the perception of other moving humans, or "biological motion" as we call it in the field. Humans are quite adept at perceiving complex human actions, even when the human body is represented sparsely by dots (aka "point-lights") located on the major joints of the body (ankles, knees...etc.). My PhD thesis centered on investigating the relative roles that motion and form-based computational analyses play in the perceptual construction of human action from these sparse point-light displays. I am currently still interested in furthering this line of research, as well as developing new behavioral and statistical methods to investigate perceptual processes such as biological motion. Finally, we plan to develop a quantitative model of human action perception using Bayesian probabilistic methods. <webpage>

Graduate Students

 

Junzhu Su

I studied visual perception for my master degree at Peking University, focusing on the nerual mechanisms of perceptual learning. Now, I am working on action recognitionand inference. My research topics include action prediction, and how action inference interacts with attention/awareness. I am also fascinated about higher cognition such as decision making and complex reasoning using imaging techniques and quantitative modeling. <webpage>

 

 

 

James Kubricht

While working toward my B. S. in physics from the University of Texas at Austin, I pursued research in cognitive psychology, specifically machine learning and computational approaches to category leaarning. At UCLA, I'm pursuing research in analogical reasoning from a computational perspective. I am interested in developing a computational framework of analogy which explains how knowledge of a source system is generated from basic perceptual inputs, and how depth of source knowledge affects implicit and explicit analogical transer. Furthermore, I am interested in how the quality of source representation is influenced by the method of source instruction, i.e., are animated source display more intuitive than verbal/diagram displays, and if so, do transfer rates to novel target problems reflect this increase in apparent source understanding

 

 

 

Undergraduate Students

 

Janice Lau; Michael Finch; Kimson Nguyen; Steven Gomedi; Nikola Lazovich; Matthew Weiden; Timothy Tanaka; Shawna Kim; Jonny Chan; Nora Hamadan; Thach Nguyen; Jennifer Chng; Kevin Ruiz; Perla Saldivar; Mike Kim

 

Alumini

Jeroen J. A. van Boxtel Associate Professor, Monash University, Australia <webpage>
Alan Lee Postdoc, Université Paris Descartes <webpage>
Randall R. Rojas Department of Economics, UCLA
Shuang Wu Dataist Company
Xuming He Senior Researcher, Computer Vision Group, NICTA, Australia
Matt Weiden UCSB CS Graduate Program