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Mary McGlohon
Graduate Assistant
Machine Learning Department
Carnegie Mellon University
5000 Forbes Ave., Pittsburgh, PA 15213
Office: Wean 7110-
412.268.7670
Fax: 412.268.5576
Email: mmcgloho+www@cs.cmu.edu
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I am a Ph.D. student in the Machine Learning Department at
CMU's School of Computer Science.
My advisors are Christos Faloutsos and
Alan Montgomery. My current research involves finding
the structure of information propagation using data from blogs and optimizing pricing strategies using
these findings. My primary research goal is to efficiently discover patterns in real-world data and find
useful applications of these patterns. I am receiving support from a NSF Graduate Research Fellowship.
I graduated from the University of Tulsa with Bachelor's degrees
in Computer Science and Mathematics. I worked on AI research in Sandip Sen's lab, and also did research in
applied math with Christian Constanda.
Research Interests
My field-related interests include the following:
- Knowledge discovery for the Web
- Link analysis
- Evolving networks
- Social networks
- Data mining applications to epidemiology and public health
- Data mining applications to marketing
- Anomaly detection in graphs
Research and Publications
Conference Papers
In reverse chronological order:
- M. McGlohon, L. Akoglu, and C. Faloutsos. Weighted Graphs and Disconnected Components: Patterns and a Generator. SIG-KDD
Las Vegas, Nev., August 2008. [pdf]
- M. McGlohon, J. Leskovec, C. Faloutsos, N. Glance, and M. Hurst. Finding patterns in blog
shapes and blog evolution. International Conference on Weblogs and Social Media. Boulder, Colo., March 2007. January 2007. [pdf] Tech Report (identical): CMU-ML-07-100.
- J. Leskovec, J, M. McGlohon, C. Faloutsos, N. Glance, and M. Hurst. Patterns of Cascading
Behavior in Large Blog Graphs. Society of Industrial and Applied Mathematics- Data Mining.
Minneapolis, Minn., April 2007. [pdf] Tech report (12 pgs): CMU-ML-06-113 [local]
- McGlohon, M. and S. Sen. Learning to cooperate in multi-agent systems by combining Q-
learning and evolutionary strategy. World Conference on Lateral Computing, December
2004. [pdf] Best Student Paper Award.
Non-Refereed Publications
- M. McGlohon, J. Leskovec,C. Faloutsos, N. Glance, M. Hurst. Information Propagation and Network Evolution on the Web. DA Project, Machine Learning Dept. Carnegie Mellon University. [pdf]
- M. McGlohon and C. Faloutsos. ADAGE: A Software Package for Analyzing Graph Evolution. Tech Report. CMU-ML-07-112. [pdf][software]
Talks
- Tutorial at ICWSM, Graph Mining Techniques for Social Media Analysis [link to VIDEO] [gzipped pdfs]. (If you would like PPT version, please email me)
- Talk at Microsoft Live Labs over work on blogs: [ppt]
- Presentation in Analysis of Social Media seminar over graph mining techniques applied to blogs: [ppt]
- Talk at Sandia Labs over SDM07 work: [ppt]
Software
- ADAGE, Matlab add-in for analyzing evolving graphs. [tar.gz] See tech report for documentation: [pdf]
Data
I have compiled data from the U.S. Federal Election Commission, representing federal electoral campaign
donations from individuals to committees and committees to candidates. A description, and the files, are located
here.
CV
Last updated February 2008: [pdf].
Graduate Coursework
In reverse chronological order. * indicates core MLD PhD curriculum.
- 36-835: Models and Methods for Networks, FA07
- 10-802: Analysis of Social Media, FA07
- 15-853: *Algorithms in the Real World, FA07
- 10-702: *Statistical Machine Learning, SP07
- 10-708: Probabilistic Graphical Models, FA06
- 36-728: Time Series Analysis, FA06Q1
- 36-720: Discrete Multivariate Analysis, FA06Q2
- 15-826: *Multimedia Databases and Data Mining, SP06
- 36-626: Mathematical Statistics II, SP06
- 10-701: *Machine Learning, FA05
- 10-705: *Intermediate Statistics, FA05
Other Activities
I have performed a number of service- and otherwise-related roles for SCS. They include:
- Databases group, lab manager. Page for Machines: (local)
- Dec/5 (TG's, various other SCS social events)
- Machine Learning Dept. Recruiting (Open House, maintaining contact with prospective students)
- SIGBOVIK 2007, 2008 programming committee
Links
- Tensor Toolbox- From Tamara Kolda and team at Sandia National Labs.
A tool for multidimensional arrays in MATLAB. I've found sptensor, the sparse tensor functions, especially useful.
- BlogPulse- Several tools for blog tracking and analysis. Developed by Nielsen Buzzmetrics, some friends in industry.
- Upcoming Conferences and Workshops- a handy reference for upcoming conference deadlines in AI, Data Mining, Machine Learning, and related fields.
Misc.
SIGBOVIK
For a sample of my more creative writing, please refer to my embarrassingly numerous SIGBOVIK publications:
- M. McGlohon and R.J. Simmons. Towards a Frequentist's Approach to Pascal's Wager. SIGBOVIK. Pittsburgh, Penn., April 2008. Paper: [pdf]
- M. McGlohon. Data Mining Disasters: A Report. SIGBOVIK. Pittsburgh, Penn., April 2008. Paper: [pdf] Most-Least-In-Box Award
- (authors redacted) Optimal Censor Placement in Wireless Censor Networks. SIGBOVIK. Pittsburgh, Penn., April 2008. Paper: [pdf]
- M. McGlohon. Methods and Uses of Demoralizing Graphs. SIGBOVIK. Pittsburgh, Penn., April 2007. Paper: [pdf] Talk: [ppt]
- M. McGlohon. Fried Chicken Bucket Processes. SIGBOVIK. Pittsburgh, Penn., April 2007. [pdf]
My Erdös number: <=4
Paul Erdös - Noga M. Alon - Phillip B. Gibbons - Christos Faloutsos - Mary McGlohon