Sofus' Home Page

Static Email: sofmac@gmail.com

Sofus Attila Macskassy
Manager, Applied Machine Learning, Facebook

Social Networking related: I have a LinkedIn and a Facebook account.

Research Interests:

Statistical Relational Learning, Semi-supervised learning on networked data (aka. within-network learning), Machine Learning, Information Integration/Aggregation/Filtering/Ranking, Text Mining, User Profiling and Personalized Information Management.


About me:

Haym Hirsh was my advisor in my thesis work on Intelligent Information Filtering. I was a member of the Rutgers Machine Learning Research Group, while at Rutgers.

I went to NYU Stern School of Business as a Research Scientist after I graduated, working with Foster Provost.

I next went to Fetch Technologies where I was the Director of Fetch Labs, the research division within Fetch. I helped bring in government funding and I ran the division for the latter half of my tenure at Fetch.

After I left Fetch, I went back to academia, where I was a Project Leader at the Information Sciences Institute and an Assistant Research Professor in Computer Science, at the University of Southern California.

I left academia again to join Facebook, first in their Core Data Science team, where I lead a team focusing on User Modeling. I recently joined the Applied Machine Learning group at Facebook, where I now lead a team focusing on bringing machine learning to all of Facebook.


Service:


Selected Talks and Presentations:

  • Invited talk, "Mining Social Media: The Importance of Combining Network and Content," The 8th International Conference on Data Mining (DMIN), July 2012.
  • Invited talk, "Social Media Analytics: links, user generated content, and more.", Information Sciences Institute, USC, February 2011.
  • Invited talk, "Social Media Analytics: links, user generated content, and more.", Rutgers University, September 2010.
  • Invited talk/workshop, "Efficient Machine Learning on Large Networks by Leveraging Homophily," Networks and Network Analysis for the Humanities Workshop at UCLA, August 2010.
  • Invited speaker, "Learning with Networked Data," Navy Research Labs, May 2010.
  • Invited speaker, "Efficient Machine Learning on Large Networks by Leveraging Homophily," Lawrence Livermore National Labs, November 2009.
  • Invited speaker, "Semi-supervised Learning in the context of networked data," University of Washington, April 2008.
  • Invited speaker, "Semi-supervised Learning in the context of networked data," University of California, Irvine, October 2007.
  • Invited speaker, "Improving learning in networked data by combining explicit and mined links," NASA Ames Research Center, August 2007.
  • Invited speaker, "NetKit-SRL: A Toolkit for Network Learning and Inference," USC Information Sciences Institute AI Seminar Series, November, 2005.
  • Invited speaker, "NetKit-SRL: A Toolkit for Network Learning and Inference," Google Mountain View, November, 2005.

Teaching:

I taught on a regular basis at the Computer Science Department, at the University of Southern California.