Update: I am now living the dream as a Software Engineer at Google in Pittsburgh. I work on Google Shopping.
I completed my thesis in the Machine Learning Department at
CMU's School of Computer Science.
My advisors were Christos Faloutsos and
Alan Montgomery. My thesis research was on finding
patterns of network formation, evolution, and diffusion in real networks and applying these patterns
to anomaly detection and consumer product reviews.
While at CMU I also engaged in various stunts, such as participating in fake protests and fake conferences.
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.
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
- Mary McGlohon. Structural Analysis of Networks: Observations and Applications. Ph.D. Thesis. Machine Learning Department, Carnegie Mellon University, December 2010. [pdf]
In reverse chronological order:
- U Kang, M. McGlohon, L. Akoglu, and C. Faloutsos. Patterns on the Connected Components of Terabyte-Scale Graphs. IEEE International Conference on Data Mining (ICDM10). Sydney, Australia, December 2010. [pdf]
- R. Kumar, M. Mahdian, M. McGlohon. Dynamics of Conversations ACM Special Interest Group on Knowledge Discovery and Data Mining (KDD10). Washington DC, July 2010. [pdf]
- M. McGlohon, N. Glance, and Z. Reiter. Star Quality: Aggregating Reviews to Rank Products and Merchants. AAAI International Conference on Weblogs and Social Media (ICWSM10). Washington DC, May 2010. [pdf].
- L. Akoglu, M, McGlohon, C. Faloutsos. OddBall: Spotting Anomalies in Weighted Graphs. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD10) Hyderabad, India, June 2010. Winner of Best Research Paper Award. [pdf].
- M. McGlohon, S. Bay, M. Anderle, D. Steier, and C. Faloutsos. SNARE: A Link Analytic System for Graph Labeling and Risk Detection ACM Special Interest Group on Knowledge Discovery and Data Mining (KDD10). Paris, France. June 2009. [pdf]
- M. McGlohon and M. Hurst. Community Structure and Information Flow in Usenet: Improving analysis with a thread ownership model. AAAI International Conference on Weblogs and Social Media (ICWSM09). San Jose, Calif. May 2009. [pdf]
- M. McGlohon and M. Hurst. Considering the Sources: Comparing linking patterns in Usenet and blogs. AAAI International Conference on Weblogs and Social Media (ICWSM09). San Jose, Cali. May 2009. [pdf]
- M. Goetz, J. Leskovec, M. McGlohon, and C. Faloutsos. Modeling Blog Dynamics. AAAI International Conference on Weblogs and Social Media (ICWSM09). San Jose, Cali. May 2009. [pdf]
- L. Akoglu. M. McGlohon, and C. Faloutsos. RTM: Laws and a Recursive Generator for Weighted Time-Evolving Graphs. IEEE Int'l Conference on Data Mining (ICDM08) Pisa, Italy, Dec. 2008. [pdf]
- M. McGlohon, L. Akoglu, and C. Faloutsos. Weighted Graphs and Disconnected Components: Patterns and a Generator. ACM Special Interest Group on Knowledge Discovery and Data Mining (KDD08)
Las Vegas, Nev., August 2008. [pdf][video (videolectures.net)]
- 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. [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. (SDM07)
Minneapolis, Minn., April 2007. [pdf] Tech report (12 pgs): CMU-ML-06-113 [full-pdf]
- 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.
- 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]
Feel free to re-use parts of these presentations. My policies for re-using them are 1) please credit me, and 2) don't change my fonts to Comic Sans.
- (new, under construction) Cascades code. Code for working with the structures of conversations in online social media.
- (old) ADAGE, Matlab add-in for analyzing evolving graphs. [tar.gz] See tech report for documentation: [pdf]
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
I was TA for two courses while at CMU:
I also served as an undergraduate TA at University of Tulsa for several lower-level math classes:
- 15-381: Intro to Artificial Intelligence, Profs. Manuela Veloso and Luis von Ahn
- 10-601: Machine Learning, Profs. William Cohen and Tom Mitchell
- MATH 1093: Math with Applications (algebra and calculus for non-majors), Fall 2003
- MATH 1083: Contemporary Mathematics (problem solving class for non-majors), Spring 2004, Summer 2004
- MATH 2014: Calculus I (taught weekly quiz section), Fall 2004
In reverse chronological order. * indicates core MLD PhD curriculum.
- 36-462: Topics in Statistics: Chaos, Complexity, and Inference, SP09
- 99-701: College/University Teaching, FA08
- 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
I have performed a number of service- and otherwise-related roles for SCS. They include:
I have also enjoyed some stunts that were tangentially-related to my research.
- Databases group, lab manager. Page for Machines: (local)
- Dec/5 (TGs, maintenance of the grad lounge coke machine, various other SCS social events)
- Machine Learning Dept. Recruiting (Open House, maintaining contact with prospective students)
- SIGBOVIK 2007, 2008, 2009 program committee
I was part of the Machine Learning Protesters, who appeared during the G20 People's March, in September 2009. That is me in the blue data mining helmet. For the complete set of photos see this Flicker Set.
I have been on the SIGBOVIK PC since 2007. It is a "fake" conference, in that it contains research that is meant to be humorous or whimsical rather than technically rigorous. But it is not fake in that it does take submissions (via EasyChair), is peer-reviewed (albeit with a high acceptance rate), and has real presentations and proceedings. Here are my contributions to this conference.
Other fun facts
- M. McGlohon. MapReuse and MapRecycle: Two More Frameworks for Eco-Friendly Data Processing. SIGBOVIK Pittsburgh, Penn., April 2009. Paper: [pdf] "Bypassing the Filters" Award for Paper Most Likely to be Cited by a Real Paper. Which means you should cite it.
- M. McGlohon and Robert 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] Talk: [ppt] 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] Y.J. Ringard Golden Broccolo Award for Culinary Excellence
- I enjoy puzzles. I once spent 36 straight hours (Saturday morning through Sunday afternoon) on a puzzle scavenger hunt while at Microsoft, one of the few grad interns nuts enough to participate.
- I maintained the departmental Coke machine. Diet Dr. Pepper is the most popular pop in the Gates-Hillman Center.
- I drove with Austin from Pittsburgh to Seattle, a journey of 2500 miles, and back, in summer 2008. It took 3.5 days to get there (a little longer to get back, as we made a stop or so).
- I ran the 2009 Pittsburgh marathon, with a lightning-fast time of 4:17:27. Nels, who took this photo at mile 23, says I was the happiest runner he saw.
- I can do a back handspring on an appropriately soft surface.
- I make some mean fried okra, a traditional Oklahoman dish.