Diane Oyen

 
 

Multivariate time series data compiled from the USGS Streamflow database.

http://www.cs.unm.edu/~doyen/data/streamflow/

 

PhD Candidate

Advisor, Terran Lane

Department of Computer Science

University of New Mexico

Albuquerque, NM 87131

doyen at cs dot unm dot edu


Research InterestS

I develop machine learning methods that help scientists to understand complex data.  Much of my work involves analyzing fMRI brain imaging data to understand the effect of disease and treatment on the functional activation network of the brain.

Data

Professional Activities

  1. •Board Member, New Mexico Network for Women in Science and Engineering

  2. •Senior Program Committee Member, AAAI-13

  3. •Scholar, National Security Studies Program (NSSP)

  4. •past Organizer, Women in Machine Learning Workshop

  5. •past Vice President, Computer Science Graduate Student Association

  6. •past Program Chair, Computer Science @ UNM Student Conference

Select Publications

D. Oyen and T. Lane, “Leveraging Domain Knowledge in Multitask Bayesian Network Structure Learning,” AAAI, 2012.

D. Oyen, E. Eaton and T. Lane, “Inferring Tasks for Improved Network Structure Discovery”, The Learning Workshop, Snowbird, 2012.

D. Oyen, “Active Learning of Transfer Relationships for Multiple Related Bayesian Network Structures,” IEEE ICDM Workshops, 2011.

D. Oyen and T. Lane, “Exploiting Task Relatedness for Multitask Learning of Bayesian Network Structures,” Technical Report , www.cs.unm.edu/~treport/tr/10-04/paper-2011-02.pdf, 2011.

D. Oyen and T. Lane, “Exploiting Task Relatedness to Learn Multiple Bayesian Network Structures,” Technical Report, www.cs.unm.edu/~treport/tr/10-04/paper-2010-08.pdf, 2010.

E. Besada-Portas and D. Oyen, “Redes Bayesianas,” in Aprendizaje Automatico: Un Enfoque Practico, Ra-Ma, 2010.  

Current Courses Taught at UNM

Honors 302-005: How to Lie with Statistics: Uses and Misuses of Numbers in Argument

    Course website