Advanced Search   
  Look in
       Name    Email
  Include
       Former RI Members 
 
 
Fernando De la Torre Frade
Associate Research Professor, RI
Email:
Office: EDSH 211
Phone: (412) 268-4706
  Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
Administrative Assistant: Peggy A. Martin
Affiliated Center(s):
 Quality of Life Technology Center (QoLT)
Personal Homepage
Research Interests

Dr. De la Torre's research interests include machine learning, signal processing and computer vision, with a focus on understanding human behavior from multimodal sensors (e.g. video, body sensors). I am particularly interested in three main topics:

  • Component Analysis (CA):
    CA methods (e.g. kernel PCA, Normalized Cuts, Multidimensional Scaling) are a set of algebraic techniques that decompose a signal into relevant components for classification, clustering, modeling, or visualization. I am interested in using CA methods to efficiently and robustly learn models from large amounts of high dimensional data. The theoretical focus of my work is to develop a unification theory for many component analysis methods. I lead the Component Analysis Lab at CMU, which can be found at http://ca.cs.cmu.edu.

  • Human Sensing:
    Modeling and understanding human behavior from sensory data (e.g. video, motion capture, audio). This work is motivated by applications in the fields of human health, computer graphics, machine vision, biometrics, and human-machine interfacing. I co-lead the Human Sensing Lab at CMU, for more information see
    http://www.humansensing.cs.cmu.edu.

  • Face Analysis:
    Developing algorithms for real-time face tracking, recognition, and expression/emotion analysis.

Research Interest Keywords
artificial intelligencecomputer visiondata miningdata visualizationgesture recognitionimage compressionimage processinginformation fusionmachine learningmachine understanding of video and human behaviorneural networkspattern recognitionquality-of-life technologysensor fusionstatistics