• LOGIN

MLBio+ Laboratory - Machine Learning in Biomedical Informatics

Home › MLBio+ Laboratory › People › Huzefa Rangwala

Navigation

  • MLBio+ Laboratory
    • People
      • Huzefa Rangwala
        • Education
        • Publications
        • Software/Web Servers
        • Service
        • Talks
        • Book: Protein Structure Prediction
    • Collaborators
  • Classes
  • Feed aggregator

Contact Me

Office: 4423 Engr Building
Office Hours: T 4:00-5:00 pm
rangwala@cs.gmu.edu
703-993-3826

Education

I graduated with a PhD. in June 2008 from the Computer Science Department at the University of Minnesota in the wonderful Minneapolis/St. Paul Area. My dissertation adviser was Prof. George Karypis.

My thesis was Protein Structure and Function Prediction using Kernel Methods , and dealt with development of machine-learning methods for predicting the structure and function of proteins using sequence information only.

I also got my Masters in Computer Science with a minor in Bioinformatics in December 2005 from the University of Minnesota.

I grew up in the city of Mumbai, India with an undergraduate degree in Computer Engineering at Veermata Jeejabai Technological Institute (V.J.T.I) in June 2003.

News Highlights

  • Syed F to join the Lab.
  • Paper Accepted at Journal of Chemical Information & Modeling
  • Huzefa to serve on program committee for SIAM Data Mining Conference 2010 (SDM 2010)
  • Huzefa to serve on program committee for HiCOMB 2010
  • New funding received from NSF IIS for bridging chemical and biological spaces.
  • Two open positions for graduate students (MLBio+ Laboratory)
  • Ammar submits his 1st paper!
  • Salman's paper accepted at WISM-AICI 2009.
  • Huzefa presents 2 posters at ISMB 2009
  • Sheng Li and Anveshi join the lab this Fall
more

Bioinformatics & Data Mining

  • PrePrint: Skewed Rotation Symmetry Group Detection
  • PrePrint: Object Detection with Discriminatively Trained Part Based Models
  • PrePrint: Large Scale Discovery of Spatially Related Images
  • PrePrint: Epitomic Location Recognition
  • PrePrint: Class Conditional Nearest Neighbor for Large Margin Instance Selection
more

(c) Rangwala 2008, George Mason University, Fairfax, VA