Khalid El-Arini
Ph.D. Student, Computer Science Department
School of Computer Science
Carnegie Mellon University

Khalid
I am a Ph.D. student working in the field of machine learning.  Specifically, I am interested in the ways that the power of computer science and statistics can be harnessed to extract meaningful information from large, real-world datasets.  I am particularly interested in looking at problems in the social sciences that would benefit from machine learning methodology.

My advisor is Carlos Guestrin, and I am currently working on new machine learning algorithms for analyzing blogs and online news.  I am a member of the SELECT Lab.

From February 2007 through August 2008, I took a leave of absence from the Ph.D. program in order to spend some time in industry. I spent three months at Google in Manhattan, where I worked on Personalized Search. This was followed by a year at MITRE in McLean, Virginia, where I applied machine learning to national policy problems, primarily working with the Securities and Exchange Commission and the United States Army.

Prior to my leave of absence, I was fortunate to work with Tom Mitchell on human brain image analysis and with Andrew Moore on interpretable classification algorithms.

Publications

Khalid El-Arini, Gaurav Veda, Dafna Shahaf and Carlos Guestrin.  Turning Down the Noise in the Blogosphere.   In Proc. of 15th International Conference on Knowledge Discovery and Data Mining (KDD 2009), June 2009, Paris, France.
[pdf] [demo] Longer version published as Carnegie Mellon Technical Report CMU-ML-09-103 [pdf]


Khalid El-Arini, Andrew W. Moore and Ting Liu.  Autonomous Visualization.  In Proc. European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2006), September 2006, Berlin, Germany.
[pdf] Full version published as Carnegie Mellon Technical Report CMU-CS-06-137 [pdf]


Khalid El-Arini and Kevin Killourhy.  Bayesian Detection of Router Configuration Anomalies.  In Proc. ACM SIGCOMM Workshop on Mining Network Data (MineNet-05), August 2005, Philadelphia, Pennsylvania.
[pdf] [longer version available here] [slides]


Talks

 An introductory tutorial on Dirichlet process mixture models (November 2005, updated October 2008). [pdf]

Teaching

 I was a teaching assistant for Probabilistic Graphical Models in Fall 2006, and am currently TAing the undergraduate algorithms course.
Office: Gates 8127
Phone: (412) 268-2993
Email: Click here
Mailing Address:
Computer Science Department
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA  15213



Education:

M.S. Computer Science
Carnegie Mellon University (2006)

B.S. Computer Science
B.S. Electrical and Computer Engineering
Carnegie Mellon University (2004)