基本信息
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职业迁徙
个人简介
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 later helped found the Applied Machine Learning group at Facebook, where Ilead a team focusing on bringing machine learning to all of Facebook.
I am now at Branch Metrics, where I head up the data and analytics org, focusing on everything from building out data infrastructure to managing their data and making sense of it, to business analytics.
Service:
Editorial Board:
Data Mining and Knowledge Discovery (2015-present)
Machine Learning (2011-present)
Journal of Artificial Intelligence Research (2012-present)
Organizing committee:
KDD-2014 (General Chair), ECML/PKDD-2013, SIGKDD-2012, ICWSM-2012, SIGKDD-2011, MLG-2010, WSDM-2010, Fourth workshop on evaluation methods in machine learning (2009), Third workshop on evaluation methods in machine learning (2008), Second Workshop on Evaluation Methods for Machine Learning (2007), The Third Workshop on ROC Analysis in ML (2006), Second workshop on ROC Analysis in ML (2005), Second ML, IR and UM Workshop (2003), Third ML4UM Workshop (2001)
Area Chair or Senior PC:
SIGKDD-2015, SDM-2013, AAAI-2012 (AI & Web), ICWSM-2011, AAAI-2011 (AI & Web), ICML-2009
Program Committee:
KDD-2013, ICML-2013, ICML-2012, ECML/PKDD-2012, ICWSM-2012, AAAI-2012, Appification of the Web (AppWeb2012), IJCAI-2011, ICML-2011, AAAI-2011, ILP-2010, WWW-2010, KDD-2009 (research and industrial track), SRL-2009, Workshop on Grand Challenges for Reasoning from Experiences, CNIKM-2009, KDD-2008 (research and industrial track), K-CAP 2007, WPRSIUI-2007, AAAI-2006, WPRSIUI-2006, WPRSIUI-2005, ICML-2003
Journal Reviewer:
I am a regular reviewer at various journals, including:
Journal of Machine Learning Research (JMLR), IEEE Transactions on Knowledge and Data Engineering (TKDE), IEEE Intelligent Systems, ACM Transactions on Information Systems (TOIS), User Modeling and User-Adapted Interaction (UMUAI), Machine Learning Journal (ML), International Journal of Pattern Recognition and Artificial Intelligence (IJPRAI), Data Mining and Knowledge Discovery (DMKD), Decision Support Systems (DSS), International Conference Information Systems (ICIS), International Journal of Business Intelligence and Data Mining (IJBIDM).
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.
研究兴趣
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ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (2014)
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user-61447a76e55422cecdaf7d19(2014)
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ICML'14: Proceedings of the 31st International Conference on International Conference on Machine Learning - Volume 32 (2014): 874-882
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semanticscholar(2012)
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